Project Title: Research and Development for goes-r risk Reduction Principal Investigator



Download 24.57 Kb.
Date18.10.2016
Size24.57 Kb.
GOES-R Progress Report for July-September 2005

Cooperative Institute for Research in the Atmosphere/Colorado State University

Fort Collins, CO
Project Title: Research and Development for GOES-R Risk Reduction

Principal Investigator: Thomas H. Vonder Haar, CIRA/CSU

Co-Investigators: Mark DeMaria and Debra Molenar, NESDIS/ORA

Date: October 14, 2005
FY2005 Funding: $285,000 (received Aug 2005)

  1. 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 three-color 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 29-32 (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. Right-side 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

Download 24.57 Kb.

Share with your friends:




The database is protected by copyright ©ininet.org 2020
send message

    Main page