GOES-R Progress Report for July-September 2005
Cooperative Institute for Research in the Atmosphere/Colorado State University
Fort Collins, CO
Project Title:
Principal Investigator:
Co-Investigators:
Date:
FY2005 Funding:
Research and Development for GOES-R Risk Reduction
Thomas H. Vonder Haar, CIRA/CSU
Mark DeMaria and Debra Molenar, NESDIS/ORA
October 14, 2005
$285,000 (received Aug 2005)
July-September 2005 Accomplishments
Task 1. Mesoscale Weather Database
The GOES-R webpage, http://rammb.cira.colostate.edu/projects/goes_r/ , continues to be
updated with new results and information, including updates to the proposed Advanced
Baseline Imager bands. In addition, a new case was added to the Case Study Database.
Volcano Reventador (Ecuador) erupted 3-5 November 2002. A multitude of satellite
loops, images, and products are available which monitor the eruption and resulting ash
plume, including those from GOES, MODIS, and AIRS. In the coming months, any
interesting new cases will be added to the Mesoscale Weather Database.
Task 2. Synthetic GOES-R data generation and analysis
Last quarter we began work on publications for peer reviewed journals. We are
continuing this work this quarter. In addition, several abstracts were submitted and
accepted for presentation at the AMS 2006 annual meeting to be held in Atlanta, Georgia.
Additional processing of data from the 8 May 2003 simulation continued this quarter.
Specifically, synthetic GOES-R sounder soundings were generated at different vertical
footprint sizes. Several observed 12 Z sounding were acquired around the country. To
produce synthetic sounder soundings, the discrete Fourier transform was applied to a
sounding. In frequency space, filtering was done to remove a specific vertical footprint
and all smaller footprint sizes. The inverse transform was then applied to produce a
synthetic sounder sounding at a specific vertical footprint. Several vertical footprint sizes
were chosen: 6 km, 5 km, 4 km, 3 km, 2 km, and 1 km. Below is an example of this
procedure applied to the Dallas Fort Worth, Texas sounding. Included are the six
synthetic sounder soundings along with the current GOES sounding for the same
location. The 3 km vertical resolution is the approximate vertical resolution of the current
GOES sounder, and 1 km resolution is the approximate HES resolution. Comparing the 3
km and 1 km soundings shows the advancement that HES will provide. The actual
current GOES sounding for this case is shown in the lower right, which helps to confirm
that the current vertical resolution of the retrieval is similar to the 3 km filtered case.
Figure 2.1 Results from vertical filtering of a Dallas/Fort Worth sounding to simulate the
resolution that will be available from the HES (1 km vertical resolution) compared with
the current GOES (3 km vertical resolution). The observed sounding is in the upper-left
and the actual GOES retrieval is in the lower right. The remaining diagrams show the
results for simululated vertical resolutions of 6, 5, 4, 3, 2 and 1 km.
Task 3.Prototype product development for fog, smoke and volcanic ash analysis
New Three-Color Fog/Stratus Product: A new daytime fog/stratus discrimination
product has been under development for use with future GOES-R ABI bands. The
product utilizes the ABI-equivalent MODIS bands in the visible and near-IR portions of
the spectrum, and has as its basis the Shortwave Albedo Product, which discriminates
fog/stratus through the reflective properties of water clouds in shortwave vs. longwave IR
imagery. The new product also utilizes a three-color technique such as used in the MSG
“natural color” (red: 1.6 µm, green: 0.86 µm, blue: 0.6 µm) product. In the new threecolor fog/stratus product (Figure 1), the 1.6 µm band was retained, but the Shortwave
Albedo replaces the 0.86 µm band, and the order of the bands/colors was switched. The
new product better discriminates clouds from land, and between different levels and types
of clouds. Note that in the new product that fog (on the ground) is whiter than either
cirrus or low-level stratus/water clouds that are off the ground. Testing will continue
with several other cases gathered for the development of this ABI fog/stratus product.
Figure 3.1: New Three-Color Fog/Stratus Product that better discriminates clouds from
land, and between different levels and types of clouds, over southern Washington and
Oregon on 11 Feb 2005 at 1910 UTC. Snow is orange/red; high-level cirrus/ice clouds
are yellow/orange; low-level stratus/water clouds have a blue tint; and fog (on the
ground) is whiter than stratus clouds that are off the ground. Most land surfaces are
green, the color discrimination of land types sacrificed for cloud level and type
discrimination.
Volcanic Ash Detection: GOES, MODIS, and AIRS data for the Reventador Volcanic
eruption in Ecuador on 3-5 November 2002 have been added to the GOES-R Risk
Reduction Activity database
http://www.cira.colostate.edu/ramm/KFIntranet/GOES-R_IPO/GOESR_IPO_case_study_database.html
The combined characteristics of the satellite’s high temporal resolution, high spatial
resolution, and high spectral resolution allow for a more detailed look into volcanic ash
and aerosol detection for hazards mitigation. Figure 2 shows an example of imagery and
products from MODIS for identifying ash and aerosol compositions. Figure 2a is the
standard 11.0 µm imagery and shows that the eruption cloud looks like a convective
cloud. Figure 2b shows the typical “reverse absorption” product that has been used to
identify ash from many satellite platforms (GOES, AVHRR). Figure 2c uses a
combination of channels that will be available on GOES-R, which highlights ash and
aerosol. Figure 2d highlights detection of SO2. This case highlights the complicated
nature of volcanic ash/aerosol in the design of optimal methods for detection.
Figure 3.2: MODIS Aqua imagery and products for the Reventador Volcanic Eruption in
Ecuador (4 November 2002, 0625 UTC) a) Band 31 (11.0 µm), b) Brightness
Temperature (BT) difference Band 31-32 (BT11.0 – 12.0 µm), c) BT difference Band 2932 (8.5 -12.0 µm), and d) BT difference Band 28-27 (7.3 – 6.7 µm).
Task 4: Tropical cyclone product development
To better explore the information available through animation of the increased temporal
and spectral resolution of the GOES-R, Meteosat Second Generation (MSG) imagery has
been collected in a large tropical sector shown in Fig. 1 during the 2005 Atlantic
Hurricane Season (1 June to 30 November). The MSG 3-km imagery contains 11
spectral bands that are close to those of the ABI instrument on GOES-R. These data will
be used for future case studies and risk reduction activities.
Figure 4.1 MSG image at 10.8 um illustrating the sector that was collected during the
2005 Hurricane Season. The time of this image is 23 September 2005 at 12 UTC.
Task 5: Severe weather product development
An investigation into the utility of using multiple spectral bands from GOES and MODIS
to study thunderstorm top microphysical structure continues. A new product was added
to RAMSDIS online, http://www.cira.colostate.edu/RAMM/Rmsdsol/main.html, called
the Cloud Shortwave Albedo. This GOES product computes the 3.9 µm albedo of clouds
with 10.7 µm brightness temperatures less than -30 ˚C. New research results show that
larger 3.9 µm albedo values correspond to smaller cloud-top ice crystals, and smaller ice
crystals are correlated with updraft strength. An example of this product is shown in Fig.
5.1. In this example, thunderstorms in the eastern Texas panhandle have 3.9 µm albedo
values greater than 5%, indicating than an enhanced updraft in this portion of the storm is
ejecting small ice crystals into the anvil. Storms further east in Oklahoma have lower
values, suggesting weaker updrafts. A future nowcasting product will utilize this
relationship between shortwave reflectivity and updraft strength.
Figure 5.1: Cloud shortwave albedo product from 11 September 2005 from GOES-12.
Left-side of gray scale contains longwave window-band (10.7 µm) temperatures. Rightside contains cloud-top shortwave albedos, for temperatures colder than -30ºC.
Task 6: Information content analysis using Maximum Likelihood Ensemble Kalman Filter
(MLEF) data assimilation
During this period we have examined the impact of small (cloud resolving) scales within
the MLEF approach. This was done in collaboration with G. Carrio and W. Cotton, from
CSU/Atmospheric Science Department. The MLEF approach has been applied to the
Large Eddy Simulation (LES) version of the RAMS model, employing grid-pint
resolution of about 50m. The initial experiments, performed for a case of a mixed phase
Arctic boundary layer cloud, have indicated a good performance of the MLEF algorithm
in these small scales. For example, assimilation of liquid-water content and ice-water
content observations had a positive impact on the cloud simulations. The experience from
these LES-MLEF experiments will be used in the next stage of this GOES-R research
where we plan to evaluate the impact of different special and temporal resolution of the
simulated GOES-R observations.
Task 7: Training Activities
GOES, MODIS, and AIRS imagery were collected for training examples of 1) ship
tracks, stratus over the ocean, and clear ocean during the day and 2) fog, clear ground and
surface inversion in various regions along the eastern states. These cases will help
demonstrate what these features look like in product differences, particularly for the 3.9
and 10.7 mcombinations. Figure 7.1 shows the AIRS Aqua spectral curves of
brightness temperature vs. wavelength for clear ocean, a ship track, and low stratus. The
low-reflective surface of the ocean results in temperatures in the short wave region that
are not that different from those in the long wave region. The higher reflective surfaces
of the stratus and ship tracks reveal increasing temperatures in the short wave region as
compared to the long wave regions.
Figure 7.1 Spectral curves from AIRS Aqua data for brightness temperature versus
wavelength are shown for clear ocean (black open circle), ship track (brown closed
triangle), and stratus (green open square) during the day. Also shown are GOES
spectral bandwidths for various GOES channels.
Presentations and Publications:
Lindsey, D.T., 2005: Using Satellite Imagery to Improve On-air Forecasts and Nowcasts
AMS 34th Conference on Broadcast Meteorology, 1-5 August, Washington, DC.
Lindsey, D.T., L.D. Grasso, 2005: Reflective storm tops: A satellite method for inferring
thunderstorm top microphysical structure. AMS 21st Conference on Weather Analysis
and Forecasting and AMS 17th Conference on Numerical Weather Prediction, 1-5
August, Washington, DC.
Zupanski, D., M. Zupanski, M. DeMaria, L. Grasso, A. Y. Hou, S. Zhang, and D. Bikos,
2005: Ensemble data assimilation and information theory. AMS 21st Conference on
Weather Analysis and Forecasting and AMS 17th Conference on Numerical Weather
Prediction, Washington, D.C. 1-5 August 2005.
III. PLANS FOR THE NEXT THREE MONTHS:
Plans for Next Quarter:
Task 1
In the coming months, any interesting new cases will be added to the Mesoscale Weather
Database.
Task 2
Work will continue on publishing the results of the synthetic GOES-R data for the first
severe weather, tropical cyclone and lake effect snow case.
Task 3
Testing will continue with several other cases gathered for the development of this ABI
fog/stratus product.
Preparation of papers for the AMS Satellite Conference, in February 2006, on:
1) New Three-Color Fog/Stratus Product with additional examples.
2) Detection of volcanic ash and dust using GOES, MODIS and AIRS imagery.
Task 4
The MSG 3-km imagery contains 11 spectral bands that are close to those of the ABI
instrument on GOES-R. These data will be used for future case studies and risk
reduction activities. A new study is being initiated to study the utility of GOES-R for
tropical cyclone genesis forecasting. Also, hurricane eye soundings are being investigated
for a larger sample of cases.
Task 5
Storms further east in Oklahoma have lower values, suggesting weaker updrafts. A
future nowcasting product will utilize this relationship between shortwave reflectivity and
updraft strength.
Task 6
The experience from these LES-MLEF experiments will be used in the next stage of this
GOES-R research where we plan to evaluate the impact of different special and temporal
resolution of the simulated GOES-R observations.
Task 7
In the next quarter, the data will be added to the GOES-R database and a draft of
examples for training will be developed.
IV. SPENDING PLAN:
The FY03 and FY04 project funds have been spent. The FY05 funds of $285,000 arrived
at CIRA in July of 2005.
For the next three months, spending is estimated to be:
Oct 05 $20K Nov $25K Dec $25K