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NASA Langley Research Center / Atmospheric Sciences CERES Instantaneous Clear-sky and Monthly Averaged Radiance and Flux Product Overview David Young NASA.

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Presentation on theme: "NASA Langley Research Center / Atmospheric Sciences CERES Instantaneous Clear-sky and Monthly Averaged Radiance and Flux Product Overview David Young NASA."— Presentation transcript:

1 NASA Langley Research Center / Atmospheric Sciences CERES Instantaneous Clear-sky and Monthly Averaged Radiance and Flux Product Overview David Young NASA Langley Research Center GIST 21 Joint CERES-GERB Meeting Boulder, CO March 29 - April 2, 2004

2 NASA Langley Research Center / Atmospheric Sciences Outline Globally Gridded CERES Instantaneous and Time- Averaged Products –What CERES gridded products are available? –How do I know which one is best for my research? CERES Temporal Interpolation –How does it work? –How successfully do we remove temporal sampling errors? –What can we provide for comparison with GERB?

3 NASA Langley Research Center / Atmospheric Sciences CERES Temporal Interpolation and Spatial Averaging (TISA) Goals Produce climate quality monthly and daily means –Must maintain calibration Eliminate temporal sampling errors Retain consistency among TOA fluxes, cloud properties and surface fluxes Produce synoptic maps of TOA, surface, and atmospheric flux

4 NASA Langley Research Center / Atmospheric Sciences Where TISA Fits Into CERES Processing

5 NASA Langley Research Center / Atmospheric Sciences Start with Gridded CERES Observations One hour of CERES TOA SW Fluxes

6 NASA Langley Research Center / Atmospheric Sciences CERES Instantaneous Gridded Data Products CERES Data Product TRMM Terra Aqua ERBElikeProduct TOA andSurfaceProduct Atmosphere Product ES9 (ERBElike Monthly Regional Averages) Ed2 X SFC (Monthly Gridded TOA/Surface Fluxes and Clouds) Ed2BEd2ABeta2 X FSW (Monthly Gridded Radiative Fluxes and Clouds) Ed2CBeta3 2005 Beta1 X SYN (Synoptic Radiative Fluxes and Clouds) 2004 Beta 2004 Beta 2005 Beta1 X

7 NASA Langley Research Center / Atmospheric Sciences Organize Regional Data by Time One day of CERES TOA SW Fluxes at 10:30 LT

8 NASA Langley Research Center / Atmospheric Sciences Interpolate Fluxes and Clouds over Month Regional Time Series of Flux from Terra over ARM SGP TOA Albedo TOA LW

9 NASA Langley Research Center / Atmospheric Sciences Create Temporally Interpolated and Averaged Data Products TOA SW Flux Terra FM-1 July 2001

10 NASA Langley Research Center / Atmospheric Sciences CERES Monthly Gridded Average Data Products CERES Data Product TRMM Terra Aqua ERBElikeProduct TOA andSurfaceProduct Atmosphere Product ES9 (ERBElike Monthly Regional Averages) Ed2 X ES4 (ERBElike Monthly Geographical Averages) Ed2 X SRBAVG (Monthly TOA/Surface Averages) Ed2B Jul 2004 Ed2B 2005 Beta1 X AVG (Monthly Regional Radiative Fluxes and Clouds) 2004 Beta1 2004 Beta1 2005 Beta1 X ZAVG (Monthly Zonal and Global Radiative Fluxes and Clouds) 2004 Beta1 2004 Beta1 2005 Beta1 X

11 NASA Langley Research Center / Atmospheric Sciences Averaged Parameters TOA Total-sky Fluxes TOA Clear-sky Fluxes Surface Downwelling Fluxes Surface Net Fluxes 4 Layers of Cloud Properties Cloud Fraction Cloud Optical Depth Cloud Emissivity Cloud Height Aerosol Optical Depth Snow percentage Pristine Fluxes Tuned Atmospheric Fluxes Untuned Atmospheric Fluxes Clear and All-sky Albedos Precipitable Water Window Fluxes Cloud Particle Size Liquid Water Path

12 NASA Langley Research Center / Atmospheric Sciences ERBE-like Consistent with ERBE processing Useful for comparisons with ERBE climatology 2.5° grid TOA fluxes Limited cloud information SRBAVG Takes advantage of improved CERES fluxes Uses improved temporal interpolation to remove sampling effects 1.0° grid TOA and surface fluxes Detailed cloud properties Product contains GEO and nonGEO monthly means CERES Monthly Mean Products SYN/AVG Uses GEO-enhanced interpolation to produce global synoptic flux and cloud fields Atmospheric Fluxes Pristine/Clear Fluxes Complete RT results SYN/AVG

13 NASA Langley Research Center / Atmospheric Sciences Using Geostationary Data for Temporal Interpolation of TOA Fluxes 3-hourly imager data from geostationary satellites is used to define diurnal variations between CERES observations Calibration is critical –GEO imagers calibration tied to VIRS Cloud retrieval is a subset of CERES VIRS algorithm Narrowband GEO data converted to flux using NB-BB relationship & CERES TRMM ADMs Final fluxes are normalized to CERES observations –Normalization applied to total-sky flux and SW clear-sky

14 NASA Langley Research Center / Atmospheric Sciences GGEO Cloud Product Needed for SW interpolation & for monthly clouds –Necessary for ADM selection Uses IR/Vis retrievals (run as subset of CERES cloud algorithm) Uses CERES surface property maps and MOA soundings 3-hourly Cloud Properties –Cloud Amount –Cloud Temperature –Cloud Height (using standard 4 CERES layers) –Optical Depth/Emittance (Daytime Only) The GGEO Product is not publicly released –Only monthly mean properties available

15 NASA Langley Research Center / Atmospheric Sciences Adding GEO Data Decreases Temporal Sampling Errors 2:30 - 9:30 LT LW FLUX Terra FM-1 January 2001 PM Higher: Yellow-red AM Higher: Blue

16 NASA Langley Research Center / Atmospheric Sciences Adding GEO Data Decreases Temporal Sampling Errors 2:30 - 9:30 LT SW FLUX Terra FM-1 January 2001 PM Brighter: Yellow-red AM Brighter: Blue

17 NASA Langley Research Center / Atmospheric Sciences CERES Time Series Use GEO to simulate GERB-like sampling GEO inadequacies –Calibration –Conversion to broadband fluxes –Time sampling (3-hourly) Validation Compare with high temporal resolution data –GERB –Surface radiometry Compare CERES instruments –Instantaneous –Monthly means

18 NASA Langley Research Center / Atmospheric Sciences Temporal Interpolation of TOA LW Flux January 1998 E. Sahara 24.5N 20.5E

19 NASA Langley Research Center / Atmospheric Sciences

20 Comparison with Surface-Based Measurements ARM SGP CF February 1998 (W/m 2 )  Flux Bias  Flux RMS Instantaneous-0.0519 Interpolated-2.925

21 NASA Langley Research Center / Atmospheric Sciences SRBAVG DCSW vs. ARM SGP

22 NASA Langley Research Center / Atmospheric Sciences Comparing Interpolation from 2 CERES Satellites Adding GEO sampling should remove sampling differences Can assess instantaneous errors or monthly means March 2000 TRMM vs Terra Terra vs Aqua –December 2002 Terra Edition2A / Aqua Beta2

23 NASA Langley Research Center / Atmospheric Sciences Zonal Monthly Mean Aqua-Terra TOA Fluxes nonGEO December 2002 Aqua and Terra zonal monthly means can differ by 10 W/m2

24 NASA Langley Research Center / Atmospheric Sciences Zonal Monthly Mean Aqua-Terra TOA Fluxes GEO December 2002 The addition of GEO data reduces zonal flux differences to < 2 W/m2 Except….. SW flux near 30°S

25 NASA Langley Research Center / Atmospheric Sciences Aqua-Terra Monthly Mean LW Flux December 2002 nonGEO GEO

26 NASA Langley Research Center / Atmospheric Sciences Aqua-Terra Monthly Mean SW Flux December 2002 nonGEO GEO

27 NASA Langley Research Center / Atmospheric Sciences Aqua Data is Missing! Aqua sampling: LW data missing from SH deserts biases the Monthly mean flux GEO

28 NASA Langley Research Center / Atmospheric Sciences Summary There are 3 main data product groups –ERBElike –Surface + TOA products (SFC/SRBAVG) –Complete atmospheric radiative products (SYN/AVG/ZAVG) CERES attempts to model GERB-like sampling using narrowband GEO data –Large-scale diurnal sampling errors removed –Some sampling issues remain –Hourly interpolation provides a means to directly compare with GERB SRBAVG due out soon –SYN to follow later in year

29 NASA Langley Research Center / Atmospheric Sciences

30 Local time of last GGEO observation

31 NASA Langley Research Center / Atmospheric Sciences Number of Daytime GGEO Observations

32 NASA Langley Research Center / Atmospheric Sciences July 2001 Terra SRBAVG Monthly Means TOA SWTOA LW TOA Net TOA LW CF

33 NASA Langley Research Center / Atmospheric Sciences Aqua/Terra Interpolation Interpolation Errors (W/m 2 ) 30°S December 2002 Interpolation MethodMean SWBias Standard Deviation nonGEO Aqua to Terra251.4+5.9104.8 nonGEO Terra to Aqua243.2-5.5103.5 Aqua to Terra (all times)251.4-3.439.8 Terra to Aqua (all times)243.2-1.141.0 Aqua to Terra (GEO times)254.6-2.333.1 Terra to Aqua (GEO times)247.2+0.334.7

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