GOES-R LAP Profiles Jun Li, Zhenglong Li, Yong-Keun Lee,

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Presentation transcript:

GOES-R LAP Profiles Jun Li, Zhenglong Li, Yong-Keun Lee, Scott Lindstrom University of Wisconsin-Madison CIMSS (Cooperative Institute for Meteorological Satellite Studies) Tim Schmit NOAA / NESDIS / ASPB This is the Satellite Foundation Course for GOES-R training on the Legacy Atmospheric Profiles. These satellite retrievals use ABI in lieu of Sounder Data. The authors are at the bottom of the slide – they all work at the Cooperative Institute for Meteorological Satellite Studies (CIMSS) in Madison Wisconsin

The subjects of this training are LAP products boxed in yellow The subjects of this training are LAP products boxed in yellow. They originate from atmospheric profiles of temperature and moisture. They include stability indices such as CAPE and Lifted Index, and Total Precipitable Water   http://www.goes-r.gov

Issue: No Sounder on GOES-R Considerable overlap between Sounder Channels and GOES-R Infrared Spectrum Present GOES Sounder is Spectrally Superior to GOES-R GOES-R is spatially superior to GOES Sounder Pixel resolution: 2 km on GOES-R, 10 km on Present GOES Sounder GOES-R scans full disk, GOES Sounder scans small region in Northern Hemisphere GOES-R is temporally superior to GOES Sounder (FD every 15 minutes v. Small Region of NH every hour) BUT!!!! http://www.goes-r.gov/resources/docs/GOES-R_GS_FPS.pdf Retrieved LAP FD Data created hourly, CONUS half-hourly, MESO every 5 minutes The Advanced Baseline Sounder (ABS) that then became the HES (Hyperspectral Environmental Suite) was initially planned to fly on GOES-R; in 2006, the HES was cut as a cost-savings move. Because GOES-13/-14/-15 Sounder and GOES-R ABI have considerable overlap in their spectra, ABI information can be used in lieu of the sounder. (The present GOES Sounder has better temperature-sensing abilities than ABI, but moisture-sensing abilities are similar) ABI also has better spatial resolution than the GOES Sounder – 2 km vs. 10 km. ABI scans the Full Disk much more quickly than the GOES Sounder, which scans only part of CONUS every hour. In the GOES-R era when ABI data are flowing, FD Data will be created hourly, data over CONUS will be created half-hourly, and MESO sector data will be created every 5 minutes.   Satellite Foundational Course - GOES-R

Satellite Foundational Course - GOES-R This figure shows channels for ABI, GOES-13 Sounder and GOES-13 Imager GOES Sounder does a better job of sensing temperature because of the abundance of channels around 4-4.5 microns, and around 14.4 microns. These extra CO2 channels allow for better temperature retrievals. There are two channels on ABI that aren't on the GOES Sounder: 8.5, which is in a region where SO2 absorption can be important and 10.3, the clean window channel. ABI channels are spectrally broad (compared to the more narrow GOES Sounder spectrum)…thus, ABI retrievals will smooth over features that have small vertical scales. The GOES Sounder with its more spectrally narrow windows is better able to resolve such features.   3.9 6.2 7.0 7.4 8.5 9.7 10.4 11.2 12.3 13.3 4.4 3.7 4.1 4.6 6.5 7.5 9.7 11.0 12.0 12.7 13.4 14.1 14.7 4.0 4.5 7.0 13.7 14.3 3.9 6.5 10.7 13.3 Satellite Foundational Course - GOES-R

Satellite Foundational Course - GOES-R GOES-15 Sounder Spectrum 14.7 14.1 13.4 14.4 13.7 12.7 12.0 11.0 9.7 4.5 7.4 7.0 6.5 4.6 4.4 4.1 4.0 3.7 This shows the spectral response function for the GOES-15 channels on top of the brightness temperature spectrum. The GOES Sounder has many channels longer than 13.4 microns and between 4 and 4.5 microns, and those channels help the Sounder’s Tempreature sounding abilities. Satellite Foundational Course - GOES-R

Satellite Foundational Course - GOES-R GOES-R Advanced Baseline Imager Spectrum 13.3 12.3 11.2 10.4 9.7 8.5 7.4 7.0 6.2 3.9 ABI does not have those CO2 channels. The ABI has an 8.5 channel – there is no SO2 channel on the Sounder. Again, these channels are fairly broad (compared to the GOES Sounder), and as such they will smooth over small-scale features in the LAP Vertical Profiles.   Satellite Foundational Course - GOES-R

Text Summary of previous slide This summarizes the previous slides. Note that ABI and GOES Sounder do have similar water vapor channels, so that Moisture retrievals from the two instruments have comparable skill. Note: ABI has fewer temperature channels than current GOES Sounder Water vapor channels are equivalent on the two instruments Satellite Foundational Course - GOES-R

The moisture content is similar between the ABI and the current GOES Sounder. ABI is not a sounder – it has very limited temperature information in the vertical so ABI retrievals need to use the NWP forecast as a background field. How many layers of information do you have when you use ABI? Forecast information added to ABI means you get comparable information as you get from the GOES Sounder plus forecast: about 5 layers in moisture, about 9 layers in temperature. Moisture information is most similar, temperature information from ABI is not as good as from the Sounder.  

Much improved spatial coverage (at more times) with ABI over the current Sounder CIMSS Current GOES Sounder coverage in one hour ABI provides more data than the GOES Sounder both spatially and temporally. This image compares the near-global coverage from ABI (up to 67 degrees local zenith angle) and the better temporal resolution. LAP products will give far better spatial coverage more frequently than can come from the GOES Sounder.   ABI in 15 minutes

Satellite Foundational Course - GOES-R LAP Profile Specs Created with a 5x5 footprint to match 10-km GOES Sounder Resolution Created Hourly (Full Disk), half-hourly (CONUS) or every 5 minutes (Mesoscale domain) GFS Information is used as a first guess Data produced up to Solar Zenith Angle of 67o (Just Poleward of the Arctic Circle) Vertical Resolution: 3-5 km Accuracy (How close to correct?) RH : ~20%; LI 2 K ; CAPE 1000 J/kg ; TPW 1 mm Precision (How close to repeatable?) RH : ~20%; LI 6.5 K ; CAPE 2500 J/kg ; TPW 3 mm Legacy Atmospheric Profiles are created with a 5x5 ABI footprint. Values are created hourly over the Globe, every 30 minutes for the CONUS scans, every 5 minutes for MESO scans. The first guess fields used in creating Legacy Atmospheric Profiles are from the GFS forecast; using the GFS data increases the number of useful layers of information in the product. The accuracy of the products is noted at the bottom. Similar to GOES Sounder DPI products available now, LAP Products are Clear-Sky only – but an All-Sky product that is valid in clear and cloudy regions has been developed.   The Baseline Product is Clear Sky Only. An ‘All-Sky’ Product has been developed Satellite Foundational Course - GOES-R

Satellite Foundational Course - GOES-R Regression Uses all (IR) wavelengths > 3.9 mm except 8.5 mm (8.5 mm has large fluctuations over deserts) Regression: Numerical Model Output – temporally and spatially interpolated to FORs Least Squares related ABI Radiances and Forecast Profiles. Regression coefficients are derived from a global radiosonde dataset. Function of Zenith Angle Retrieval: Compares observed radiances to those calculated in forward Radiative Transfer Model, minimizes the difference in the profile – adjusts temperature and moisture. The first step to produce Profiles: A Regression that uses coefficients that were trained to give the best statistical relationship between observed temperature, moisture, surface temperature & emissivity and ozone. First guess: GFS data. Then the retrieval uses a radiative transfer model; differences between the regression values and RTM values are minimized during the retrieval step.   Satellite Foundational Course - GOES-R

LAP from GOES-R AWG (Part 1 Overview) Graphical depiction of regression: Coefficients are the best, statistically, at producing a match. These are computed each time the regression is run. Regression flowchart

Variational iterative physical retrieval flowchart Regression step on left, to derive first guess into the Retrieval that is minimizing the difference in the middle triangle. Variational iterative physical retrieval flowchart

LAP Limitations LAP and derived products are available over “clear” FORs only (20 or more clear FOVs within the FOR) ABI IR band emissivities are from a monthly dataset. Temporal variability is negligible in those datasets. Surface roughness and skin temperature are assumed homogeneous The iterative physical retrieval is computationally expensive; an increase in FOR width could be necessary for large region processing Forecast temperature is hard to improve with ABI because ABI channels do not sense temperature at many different levels This slide notes limitations to the Legacy Atmospheric Profiles. ABI does not improve the temperature much in the GFS (Bias and standard deviation are barely nudged). There is much better improvement in the moisture field, as we'll see shortly. Note that "Clear" means that at least 20 of the 5x5 footprints have clear fields of view.   Weighting functions GOES-R ABI GOES-NOP Sounder

Clear Sky Results Data in AWIPS are All-Sky results. This figure shows clear sky results, comparing radiosondes and GFS and LAP Vertical Profiles. Temperature is on the left, moisture is on the right.

Clear Sky Results Satellite Retrievals do not improve temperature because temperature is already very accurate Satellite Retrievals do improve moisture between 700-300 mb – where observations occur These are Clear SKy only results. Bias improvement is largest for moisture in mid-upper troposphere. That's were satellite observations give the most added information. Reduction in the bias values is pretty small for temperatures.  

Clear Sky Results Satellite Retrievals do not improve temperature because temperature is already very accurate Satellite Retrievals do improve moisture between 700-300 mb – where observations occur (Think about Water Vapor Weighting Function!) Where the observations are giving information is described by the Weighting Function

Weighting Function Plot Most information from mid-troposphere Here we have a weighting function for the 3 Sounder water vapor Channels -- a plot for ABI would show very similar curves. Most of the information from the GOES Sounder Water Vapor Channels (or from the ABI/AHI water vapor channels) is coming from the region between 300 and 700 mb. Weighting functions for most of the other ABI and AHI channels peak near the surface.  

Dark Blue: Regions where CLR retrievals gave good data Clear-Sky CAPE Clear-Sky TPW The Baseline Products are clear Sky only – they should have a Familiar look because GOES Sounder DPI Products also are Clear sky only In AWIPS, Clear Sky products will show missing data where clouds are present Baseline Products are clear-sky only and should look familiar to forecasters who have used GOES Sounder DPI products. Examples of CAPE and Total Precipitable Water are shown here. The dark blue region is where the clear retrievals gave good data; yellow and cyan regions will not have data in the baseline products. A big display difference in AWIPS, however, for GOES-R Clear-Sky products is that Clear-Sky products will show no data where clouds are present, unlike the images on this page that blend cloud temperature information with the Clear-Sky product.   Dark Blue: Regions where CLR retrievals gave good data

What’s best about LAP Soundings Gradients Time Tendencies Quotes from HWT Evaluations: “While looking at the CAPE and Precipitable Water trends, we noticed the storm development in SD matches almost exactly with the leading edge of the gradient” “The overall gradient and orientation seems pretty good” (HWT Products were created using GOES Sounder) All-Sky LAP products have been demonstrated at the Hazardous Weather Testbed starting in 2014, and forecasters there found great utility in gradients and time tendencies because Convection frequently formed along gradients in the fields.   Satellite Foundational Course - GOES-R

LAP CAPE and convection Convection moving towards larger LAP CAPE values Here’s an example, with modest convection in a region that is a diagnosed minimum of CAPE, moving towards higher values of CAPE. What would you expect as the convection moves from a local minimum in the CAPE towards a larger value. 2035 UTC (All Sky Product created using GOES Sounder Data)

LAP CAPE and convection Convection intensifies! One hour later, the Convection had intensified   2119 UTC

Situational Awareness (All-Sky Product created from GOES Sounder Data) Situational Awareness LAP CAPE Visible Imagery 1900 UTC Here's a 4-panel with values of CAPE (upper left) and TPW from LAP (lower right), along with visible and IR. Would you expect that line of showers in the visible imagery to intensify as it traversed that WFO? Higher CAPE values do exist in the southern part of the WFO.   10.7 mm Imagery LAP TPW

Will this line develop? 1905 UTC Radar Imagery Here's the radar imagery at the same time. As it progressed eastward it did not intensify – however, the southern edge did strengthen as it reached the more unstable air along the southern edge of the WFO. You could see that less stable air in the CAPE image on the previous slide   1905 UTC Radar Imagery

Here’s a Total Precipitable Water field over the western Pacific (Guam is in this image) that was derived from Himawari data. This gives you an idea of what the All-Sky fields look like, and what kind of horizontal resolution is available. Can you infer where GFS data are used, or where satellite data are used?

Clear Cloud GFS CLR: 0 ; GFS: 1 ; CLD: 2 What is the source of the data in the previous All-Sky image? There are three 'Cloud Type' values provided in AWIPS so you know. 0 for results from the Clear Retrieval (purple), 1 for results from GFS (grey), 2 for results from cloudy retrieval (orange). CLR means that at least 20 of the Fields of Regard have clear fields of view. For a Baseline Clear-Sky products, data would only be available in purple regions.   GFS CLR: 0 ; GFS: 1 ; CLD: 2

Compare the Cloud Type to the visible image, above Compare the Cloud Type to the visible image, above. Cloudy retrieval values are normally confined to regions with very thin cirrus shields (that are difficult to view in this visible image).

Here’s the 6. 2 micron water vapor for the same time Here’s the 6.2 micron water vapor for the same time. Much less structure to the WV image than in the Precipitable water (and you can see, generally, where the GFS values are used in the regions of deep-ish clouds)

Clear GFS This is the same time as before, but zoomed in considerably – note Guam in the upper part of the image, and you can see the pixel sizes too! For reference: Guam is at most 19 km wide and 50 km long. So these pixels are around 10 km. Cloud

~0.97” ~1.00” There are subtle differences in this blown-up view between Cloudy Retrievals, Clear Retrievals and GFS values, although they’re all within 10% of each other. ~1.10”

You can see the faint wisp of the cirrus in this visible image view.

Cloudy retrievals used where cirrus is very thin The cirrus shows up more distinctly in this 11.2 micron image. Cloudy retrievals used where cirrus is very thin

Total Precipitable Water from LAP Algorithm (Himawari 8) 1400 UTC 11 February 2016 Here’s another example of total precipitable water over the western Pacific. How does it compare to other estimates? Satellite Foundational Course - GOES-R

Total Precipitable Water from LAP Algorithm (Himawari 8) 1400 UTC 11 February 2016 MIMIC TPW (Inset) is a microwave-only product derived from polar orbiting satellites. Satellite Foundational Course - GOES-R

Total Precipitable Water (All-Sky) GOES-15 Sounder Data can also be used as proxy data for the LAP algorithm. Here is the All-Sky version, also compared to MIMIC TPW.   Total Precipitable Water (All-Sky) from LAP Algorithm (GOES-15 Sounder) 1300 UTC 11 February 2016 Satellite Foundational Course - GOES-R

DPI Precipitable Water Clear Regions only (GOES-15 Sounder) Transmitting Bad data Again, the baseline product is Clear-Sky only, similar to the GOES Sounder DPI Product.   DPI Precipitable Water Clear Regions only (GOES-15 Sounder) 1300 UTC 11 February 2016 Satellite Foundational Course - GOES-R

Supplemental Information Schmit, T. J., J. Li, J. J. Gurka, M. D. Goldberg, K. J. Schrab, J. Li, and W. F. Feltz, 2008: The GOES-R Advanced Baseline Imager and the continuation of current sounder products. J. Appl. Meteor. Climatol., 47, 2696–2711. Lee, Y.-K., Z. Li, J. Li, and T. J. Schmit, 2014: Evaluation of the GOES-R LAP Retrieval Algorithm using the GOES-13 Sounder. J. Atmos. Ocean. Technol., 31, 3-19. GOES-R Algorithm Theoretical Basis Document for LAP: http://www.star.nesdis.noaa.gov/goesr/docs/ATBD/LAP.pdf http://www.goes-r.gov Thanks to Mat Gunshor from CIMSS for Figures! Supplemental Information is listed here. Read all about it!  

Summary Legacy Atmospheric Profiles are created Hourly (Full Disk), half-hourly (CONUS) or every 5 minutes (Meso). Temperature and Moisture data are retrieved from the ABI radiances. First Guess from GFS especially important for temperature retrieval because GOES-R ABI channels have limited temperature information Total Precipitable Water and Atmospheric Stability Parameters (eg., CAPE, LI, Total Totals, K Index, Showalter Index) are available Baseline Products are Clear-Sky products All-Sky Products in development use GFS data as the first guess, and GFS values emerge as the solution if both Clear and Cloudy Retrievals Fail. The AWIPS display of Clear Sky products will show no data where clouds are present.