NCEP Assessment of ATMS Radiances Andrew Collard 1, John Derber 2 and Russ Treadon 2 1 IMSG at NOAA/NCEP/EMC 2 NOAA/NCEP/EMC 1NPP ATMS SDR Product Review13th January 2012

Content Introduction Spatial Averaging Comparison with Forecast Model Assimilation Configuration Final Remarks 2

Introduction Spatial Averaging Comparison with Forecast Model Assimilation Configuration Final Remarks 3

Introduction We are routinely receiving ATMS data as BUFR files from NDE We are using the antenna temperatures contain in these files (following our use of AMSU-A/MHS radiances) The comparisons shown are based on first-guess departure statistics (observed radiances minus those calculated from a 6- hour forecast) for the NCEP GSI assimilation system. As much as possible the performance is assessed relative to that of AMSU-A/MHS on NOAA-19. 4

Introduction Spatial Averaging Comparison with Forecast Model Assimilation Configuration Final Remarks 5

Spatial Averaging / Re-Mapping We use the AAPP FFT-based remapping code (described by Nigel Atkinson) to re-map (and in the process spatially average) the AMSU-A like ATMS channels to a common field of view (3.3°). This is to reduce the noise on the temperature sounding channels and also to allow the 5.2° FOV channels 1 and 2 to be consistent with the other AMSU-A like channels (as these are used for cloud-detection). Special attention has to be paid to missing and bad data as this will affect surrounding points in the re-mapped product. Similarly, we did not want to assimilate observations within 5 scan- positions/scan-lines of each other and they will be correlated. In this presentation we are showing both raw and re-mapped data. 6

Introduction Spatial Averaging Comparison with Forecast Model Assimilation Configuration Final Remarks 7

ATMS Scan Dependence 8 Uncorrected First Guess Departure; All Obs over Sea (K)

9 NOAA-19 AMSU-A Scan Dependence

AMSU-A vs ATMS Stats ATMS Ch.10 Uncorrected First Guess Departure; All Obs over Sea (K) Antenna Temperatures 10 AMSU-A Ch 9 Satellite Zenith Angle (degrees) Green points are after remapping ATMS has much better scan-dependent bias and (after re-mapping) noise levels are equivalent

Histogram ATMS Ch. 1 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 11

Histogram ATMS Ch. 2 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 12

Histogram ATMS Ch. 3 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. Polarization switch 13

Histogram ATMS Ch. 4 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 14

Histogram ATMS Ch. 5 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. Polarization switch 15

Histogram ATMS Ch. 6 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 16

Histogram ATMS Ch. 7 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 17

Histogram ATMS Ch. 8 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. Polarization switch 18

Histogram ATMS Ch. 9 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 19

Histogram ATMS Ch. 10 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 20

Histogram ATMS Ch. 11 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 21

Histogram ATMS Ch. 12 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 22

Histogram ATMS Ch. 13 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 23

Histogram ATMS Ch. 14 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 24

Histogram ATMS Ch. 15 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 25

Histogram ATMS Ch. 16 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 26

Histogram ATMS Ch. 17 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. Polarization Switch and channel not very close 27

Histogram ATMS Ch. 18 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 28

Histogram ATMS Ch. 19 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 29

Histogram ATMS Ch. 20 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 30

Histogram ATMS Ch. 21 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 31

Histogram ATMS Ch. 22 All Sea Land Ice Snow First Guess Departure (O-B) [K] Number Observations that pass quality control. Bias Corrected. 32

ATMS vs AMSU-A vs ATMS Std. Dev. of FG Departures Comparison ATMS NOAA-19 AMSU-A NOAA-19 MHS 33

ATMS is being monitored in EXP-hybens parallel Radiance monitoring stats: ATMS AMSU-A Temperature Sounding Channels 34

ATMS analysis and forecast impact Active assimilation of ATMS was turned on in our pre-implementation parallel experiment on Low resolution experiments have been run for a short time and show statistically neutral impact This is not unexpected as ATMS observations are very close to those from NOAA-19 and Aqua. There is some evidence that the humidity analysis fields are being improved, however. 35

Conclusions ATMS observations appear to be of good quality. In particular the bias characteristics seem much better than for AMSU-A Using the AAPP re-mapping tool, AMSU-A like noise performance can be obtained. We thank the ATMS team for all their hard work in getting to this point. 36