Berndt, Emily

Blankenship, Clay

Naeger, Aaron R.

Srikishen, Jayanthi

NASA Technical Reports Server

Using Multi-Sensor Aerosol Optical Depth Retrievals to Improve Infrared 
Radiance Assimilation
Aaron R. Naeger1 , Clay Blankenship2, Jayanthi Srikishen2, and Emily Berndt3
1University of Alabama in Huntsville, Earth System Science Center, Huntsville, AL, 2USRA Space Technology Institute (STI), Huntsville, AL, 3NASA Marshall Space Flight Center, Huntsville, AL 
aaron.naeger@nasa.gov
AR
P685
Motivation Evaluation of Dust Impact on Infrared Radiances from CRTM
We provide accurate dust optical and physical properties into the CRTM via CALIOP vertical profiles and AERONET ground-based retrievals, which led to an overall better agreement between the 
observed and simulated VIIRS, MODIS, and AHI infrared brightness temperatures. However, the 8.6 µm channel of VIIRS and AHI shows a notable warm bias in the simulated brightness temperatures 
even when accounting for the accurate aerosol information within Asian dust plumes. We modify the prescribed CRTM dust properties according those specifically for Asian dust shown in Sokolik et al. 
(1998), which significantly reduces the warm bias at this channel. This bias is not observed for Saharan dust plumes. We are currently investigating the impact of aerosol-affected infrared radiance 
assimilation using the GEOS-5 framework. We plan to extend this work to assess the impact of dust aerosols on hyperspectral measurements from CrIS.* This work is supported by grant NNX17AE97G
Summary and Future Work
• Space-borne satellite sensors measure varying aerosol mass 
concentrations and particle sizes throughout the globe 
• Coarse dust particles are capable of scattering and absorbing infrared 
radiation, which have been shown to lead to heating rates > 1 K d-1
within dust layers and cooling rates > 1.5 K d-1 near top when 
composed of particles > 2 µm in radius
Figure 1. (left) CALIOP transect over a Saharan dust layer on 21 June 2007 showing L1 attenuated 
backscatter measurements, (right) RTM LW heating/cooling rates within the Saharan dust layer over 
the Eastern Atlantic Ocean.
• Motivational Questions in this study:
1. How well can current aerosol modules in the CRTM simulate the 
satellite infrared radiances of coarse dust aerosols?  
2. What is the overall impact of dust on satellite infrared radiances from 
the CRTM?
3. Does the assimilation of aerosol-affected radiances lead to a reduction 
in error in the model analysis fields? What is the overall impact on 
the forecast?
Methodology
1. Use CALIOP and AERONET aerosol retrievals within dust storms 
along with meteorology from reanalysis data for providing accurate 
aerosol and meteorology profiles into the Community Radiative 
Transfer Model (CRTM)
2. Validate simulated dust aerosol-affected infrared radiances against 
multiple satellite sensor measurements from channels with central 
wavelengths ranging from 8.5 to 12.5 µm 
3. Quantify dust impact on satellite infrared radiances by comparing 
CRTM simulated brightness temperatures to observations
4. Use GSI to assimilate aerosol-affected infrared radiances into the 
GEOS-5 model and evaluate impact on dust impact on forecast fields.
• Dust can impact clear-sky satellite radiances, which can introduce 
significant biases in temperature, moisture, and wind fields of model 
analysis, and consequently, reduce the forecast skill
• Modules accounting for aerosol impacts on radiation have been 
implemented into CRTM framework (Liu and Boukabara, 2014), but 
operational centers continue to assume aerosol-free conditions when 
assimilating infrared radiances into NWP models.
Figure 2. 2-m temperature from 
control and experimental runs over 
(left) Mongolia and (right) Taklimakan 
deserts.   
• CALIOP measurements show 
moderately high backscatter 
and high depolarization ratio 
within aerosol plume over 
Yellow Sea. 
• Coarse aerosols with 
moderately high AOD 
measured by AERONET.
• CALIOP and AERONET 
retrievals as input into CRTM 
lead to improved simulation of 
VIIRS and AHI infrared 
brightness temperatures.  
30 March 2018 Dust 
Event
Figure 4. (far left) Suomi-NPP VIIRS true-color red-green-blue (RGB) image at ~0400 UTC 30 March 2018 
with AERONET Ieodo Station site (red star) and CALIOP transect (orange line) also shown. AERONET 
Version 3 Level 1.5 retrievals of AOD (center left), 440-870 nm Angstrom exponent (center right), and size 
distribution (far right) around time period of dust event.
Figure 3. Mass extinction (top) 
and single scatter albedo (bottom) 
prescribed within CRTM GOCART 
aerosol module for dust aerosols. 
Colors indicate effective radius 
bins with values ranging from 0.01 
(bluish) to 8 µm (reddish).
Figure 6. Difference between observed and simulated satellite brightness 
temperatures along CALIOP transect. (top left) VIIRS no aerosol and dust aerosol 
simulations, (top right) AHI no aerosol and dust aerosol simulations. (bottom left 
to right) Mean and standard deviation of VIIRS no aerosol, VIIRS dust, AHI no 
aerosol, and AHI dust simulations.
5 May 2017 Dust Event
Figure 5. Nighttime CALIOP L1 attenuated backscatter at ~1750 UTC (left), depolarization ratio (center), and L2 
extinction coefficient retrievals (right) along transect in Fig. 4.
8.55 micron (11) 11.0 micron (14)
12.0 micron (15)
8.6 micron (11)
10.4 micron (13)
11.2 micron (14)
12.4 micron (15)
Figure 7. (left) Suomi-NPP VIIRS true-color RGB image 
at ~0440 UTC 5 May 2017 with AERONET Yonsei
University site (red star) and CALIOP transect (orange 
line) shown. (right) HYSPLIT forward trajectory 
ensemble for 12-h forecast beginning at 1800 UTC. 
Figure 8. AERONET Version 3 Level 2 retrievals of AOD (left), 440-870 nm 
Angstrom exponent (center), and size distribution (right) around time period of 
dust event at Yonsei University site in Fig. 7. 
Figure 9. 
Nighttime CALIOP 
L2 extinction 
coefficient 
retrievals at ~1750 
UTC 5 May along 
transect in Fig. 7.
Figure 10. Same as Fig. 6, except valid for 5 May 2017 at ~18 UTC.  
8.55 micron (11) 11.0 micron (14)
12.0 micron (15)
8.6 micron (11)
10.4 micron (13)
11.2 micron (14)
12.4 micron (15)
Sensitivity / 
Experimental 
Simulations
• CALIOP and nearby AERONET observe 
coarse dust aerosols over Yellow Sea.
• Dust layer observed by CALIOP 
advected over AERONET site according 
to short-term HYSPLIT forecast.
• Aerosol retrievals as input into CRTM 
lead to improved brightness 
temperatures, but too warm compared to 
observations, particularly at 8.6 µm.  
Figure 11. Same as Fig. 3, except 
modified dust properties within 
CRTM aerosol module specific for 
Asian dust.
Saharan Dust
8.55 micron (11) 11.0 micron (14)
12.0 micron (15)
8.6 micron (11)
10.4 micron (13)
11.2 micron (14)
12.4 micron (15)
Figure 12. Similar to Fig. 6, except for VIIRS (top) and AHI 
(center) simulated brightness temperatures for 30 March 
2018 using modified dust aerosols within CRTM.  
Figure 13. Similar to 
Fig. 12, except only 
AHI brightness 
temperatures for 5 
May 2017 using 
modified dust aerosols 
and 30% larger re.
8.55 micron (11) 11.0 micron (14)
12.0 micron (15)
Figure 14. (top left to 
right) MODIS RGB 
image at ~1600 UTC 30 
March 2017. AERONET 
size distribution and 
440-870 nm Angstrom 
exponent. (bottom) 
CALIOP L2 extinction 
coefficient.
Figure 15. Similar to Fig. 10, except valid for Saharan 
dust on 30 March 2017. 
CLEAN CLEAN DUST DUST 
CLEAN 
DUST
Modified 
DUST
Modified 
DUST
CLEAN CLEAN DUST DUST 
CLEAN 
DUST 
CLEAN 
DUST 
CLEAN 
DUST 
CLEAN 
DUST 
Modified DUST 
+ 30% Re
Re = 0.89 µm  
Re = 0.6 µm  
Re = 0.74 µm  
Re = 1.16 µm  
Modified DUST
Modified DUST
CLEAN 
DUST 
https://ntrs.nasa.gov/search.jsp?R=20190000420 2019-08-30T08:44:38+00:00Z


Using Multi-Sensor Aerosol Optical Depth Retrievals to Improve Infrared Radiance Assimilation

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