amsu/mhs climate data records for hydrological...

AMSU/MHS Climate Data Records for Hydrological Products

Ralph Ferraro1,2, Huan Meng1,2 Wenze Yang2, Isaac Moradi2

1NOAA/NESDIS, College Park, MD USA 2 Coopera9ve Ins9tute for Climate and Satellites, Univ. of Maryland,

College Park, MD

Outline

•  Why AMSU for hydrology and climate? •  AMSU/MHS CDR project objec9ves

•  AMSU‐A status

•  AMSU‐B/MHS status

•  Next steps

16‐20 September 2013 2013 EUMETSAT and AMS Satellite Conference ‐ Vienna, Austria 2

AMSU is Cri9cal for Global Hydrological & Climate Products!

•  AMSU‐A window channels (23, 31, 50 and 89 GHz) and AMSU‐B/MHS channels (89, 150/157 and three at 183 GHz) generate opera9onal hydrological products –  Cloud and Ice water, precipitable water, precipita9on rate, snow and ice cover, … –  Algorithms, although unique to MW sounders, have SSM/I heritage

–  Mul9ple opera9onal NOAA and MetOp satellites provide ~4 hour global coverage

•  Many “merged” products exploit AMSU’s temporal sampling to enhance products –  NOAA’s CMORPH rain product, NASA’s TMPA rain product, NOAA’s Blended TPW, etc.

•  For the same reasons, AMSU 9me series (~15 years) can be used for climate monitoring: –  The CDR’s are best suited when they are combined with similar CDR’s from other

sensors (e.g., SSM/I, AMSR‐E, TMI)


•  Atmospheric Rivers (AR) – poten9al to develop climatology from this data set and fuse together with SSM/I CDR

– AMSU‐A window channels are used to retrieve TPW (total precipitable water).

– AR’s connected to prolonged flooding events, e.g., “The Pineapple Connec9on” in the U.S. – AR’s have broad impact on agriculture, health, tourism, water resources, etc.

– Are the AR’s changing over 9me?

An Interes9ng Climate Applica9on…

Automated AR Detection from July 22, 2013 Blended TPW from July 22, 2013


AMSU CDR Project Objec9ves •  Project is funded by NOAA’s NCDC who manages program •  Develop AMSU‐A/‐B and MHS Fundamental (FCDR) for “window” and “water vapor” channels ‒  AMSU‐A: 23.8, 31.4, 50.3, 89.0 GHz ‒  AMSU‐B/MHS: 89, 150/157; 183±1, 183±3, 183±7/190 GHz

‒  Note – complimentary NOAA CDR projects include AMSU sounding channels, SSMI‐SSMIS (window channels) , and SSMT/2 (water vapor)

•  Develop Thema9c (TCDR) for hydrological products ‒  Precipita9on Rate (including snowfall), total precipitable water, liquid and ice

water path, sea ice concentra9on, snow cover, snow water equivalent, land surface temperature, land surface emissivity 23, 31 and 50 GHz.

•  Satellites: NOAA‐15,16,17,18,19 & MetOp‐A •  Time period: Years 2000‐2010 (depending on launch date)


For AMSU CDR, what are we concerned about and what have we found ?

•  AMSU‐A/AMSU‐B/MHS can have significant geoloca9on errors ‒  Problem can be more severe in a par9cular satellite or 9me period ‒  NOAA‐15 AMSU‐A2 was the most problema9c

•  AMSU‐A/AMSU‐B/MHS can have significant cross scan biases ‒  NOAA‐15 AMSU‐A and MetOp‐A MHS were the most severe

•  Several AMSU‐B sensors show degrada9on over 9me ‒  NOAA‐16 AMSU‐B channel 5 has the largest degrada9on

‒  Difficult to intercalibrate AMSU‐B and MHS because of subtle, but significant channel differences and primary polariza9ons ‒  150 vs. 157 GHz; 183+7 vs. 190 GHz, etc.

•  Mul9ple calibra9on methods are required to generate CDR’s for AMSU/all channels (e.g., SNO, vicarious calibra9on, etc.) ‒  Bias is oren scene temperature and/or polariza9on dependent ‒  Warm target contamina9on caused by orbital drir is one of the most important

error sources for inter‐satellite calibra9on


Geoloca9on


•  Geoloca9on error may lead to erroneous interpreta9on of observed TB, and the processes therearer, so it is very crucial to our project – Geoloca9on error may be derived from

pitch, roll and yaw error – Geoloca9on error can be quan9fied with the difference between ascending and

descending TB’s along coastlines

– NOAA‐15 AMSU‐A2 (channels 1 and 2)

has the largest geoloca9on error

– Arer correc9on, TB differences along coastlines disappears

See Moradi et al. (2013), TGRS

AMSU‐A Cross Scan Bias


•  AMSU‐A cross scan bias may be derived from polariza9on angle error or poin9ng angle error, and may cause asymmetry on products – Cross scan bias for AMSU‐A window channels are characterized by comparing observa9on

with radia9ve transfer model simula9on with different environmental condi9ons – The bias has been corrected using characteriza9on output – The improvements of the correc9ons have been verified with FCDR and TCDR products

– Details in Yang et al., TGRS, 2013

AMSU‐A Intercalibra9on


•  AMSU‐A intercalibra9on is mainly carried out using simultaneous nadir overpass (SNO) approach

– Though major SNO pairs appear at polar region, global SNO may occur in specific periods

– SNO dura9on and interval are different among pairs for different orbital configura9ons – Homogeneity is crucial for window channels, which is characterized as STD <= 10 * NEΔT

– C. Zou’s (NOAA) approach is used to correct warm target contamina9on

AMSU‐A Inter‐Calibra9on Warm Target Contamina9on Correc9on


ΔTb STD by Satellite Pair

23.8 GHz 31.4 GHz Before

Correction After

Correction Before

Correction After

Correction N16-N15 0.374 0.217 0.263 0.193 N17-N15 0.285 0.190 0.217 0.191 N18-N15 0.386 0.238 0.259 0.196 M02-N15 0.370 0.215 0.384 0.207 N19-N15 0.424 0.262 0.276 0.186

AMSU‐B/MHS Cross Scan Bias


•  Difference between left side of scan minus right side TB averaged over tropical region known as scan asymmetry. •  Varies over time and with particular satellite

NOAA‐15, CH 3 NOAA‐17, CH 3

AMSU‐B/MHS Intersatellite Calibra9on


Averages of TB over tropical region (warm end) and Antarctica (cold end) for NOAA-15 AMSU-B Channel 3 versus NOAA-17 AMSU-B Channel 3 for 2003 (left) and 2007 (right).

•  In general, AMSU-B/MHS has less issues than AMSU-A (aside from N15) •  MHS has less issues than AMSU-B •  Surface effects also less important than AMSU-A •  Following along concepts described by John et al. (2012, 2013a, 2013b)

N15 AMSU‐B CH3 vs. N17 ‐ 2003 N15 AMSU‐B CH3 vs. N17 ‐ 2007

Averages of brightness temperatures over tropical region (warm end) and Antarctica (cold end) for NOAA-19 and MetOp-A MHS Channel 3 versus NOAA-18 MHS Channel 3.


AMSU‐B/MHS Intersatellite Calibra9on

Intersatellite Differences – N19 and MOA vs. N18

N19 MHS CH3 vs. N18 MOA MHS CH3 vs. N18

PuRng it all together…CDR ProducTon Approach   AMSU‐A and AMSU‐B /

MHS CDRs take different approaches in scan bias correc9on and inter‐satellite calibra9on

  Processing requires:   C 9me and NetCDF toolkits

  FORTRAN CRTM libraries

  HDF4 libraries   HDF‐EOS2 libraries

  Online processing gets transi9oned to NCDC

  Extend 9me series

  Future reprocessing 16‐20 September 2013 2013 EUMETSAT and AMS Satellite Conference ‐ Vienna, Austria 14

Examina9on of β data sets – AMSU‐A Adjusted nadir FCDR between N15 and N18 are generally beXer than L1b; 23 GHz needs further work


Across scan bias greatly reduced in FCDR

Summary and Next Steps •  CDR’s for AMSU window channels and corresponding hydrological products are

vital for the climate community •  Our accomplishments to date include:

–  Completed AMSU and MHS geoloca9on •  See Moradi et al. 2013 – IEEE TGRS

–  Completed AMSU‐A scan bias correc9ons; intersatellite calibra9on ongoing •  See Yang et al. 2013 – IEEE TGRS

–  Inter‐calibrated AMSU‐B/MHS window and water vapor channels ongoing –  Developed β‐CDR for AMSU‐A window channels, which includes geoloca9on

correc9on, inter‐calibra9on, and scan bias correc9on –  Developed β‐CDR for MHS, which includes geoloca9on correc9on and inter‐calibra9on –  β‐CDR data sets are being analyzed for the effec9veness of the correc9on methods

•  Newer versions expected

•  Remaining steps to be completed in next 6 months: –  Complete AMSU‐A inter‐satellite calibra9on –  Complete AMSU‐B/MHS scan bias correc9on –  Release next beta version of AMSU‐A & AMSU‐B/MHS TCDR’s –  Deliver to NCDC/Ini9al Opera9onal Capability (IOC)


amsu/mhs climate data records for hydrological...

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