Error Correlation Study of IASI and CrIS Bias Using SNOs
Wed, Aug 9, 2017Scope and Purpose
This is a supplement in support of studies to evaluate and compare the channel to channel correlation of the bias between observation and calculations for the CrIS and IASI instruments.
The question relates to the application of the hyperspectral data from CrIS and IASI to numerical weather prediciton (NWP), in which one has to correctly allow for inter-channel observation errors that may be correlated.
An estimate of the observational error is available to us with the simulataneous nadir observations (SNOs) in which the analysis fields are co-located to the observations and the forward model (RTA) called SARTA - is used to estimate the top of atmosphere (TOA) radiance as measured by the sensor.
The best data to use for this study would be tropical clear sky ocean observations. Unforntunately CrIS and IASI have very different orbits so there are no close observation pairs in this region. A pseudo-SNO tropical pairing can be constructed with large separations, and it is possible that with a suitably large data set a meaningful comparison can be made.
For the main study true SNO pairs are obtained at the high latitudes from the clear subset RTP data for 2016, using ECMWF model fields and a common forward model (RTA).
The correlated observational error, (by error we mean the difference between the observed and calcuated radiance), will be influenced by the native noise of the measurements. The CrIS has lower noise than IASI, based on in-flight calibration data as shown in figure: (need a reference).
It is therefore of interest to know what the IASI error correlation looks like if the IASI data are deconvolved to the CrIS instrument line shape (ILS) and with the corresponding noise characteristic. Results are shown next section.
RTP Data - Overview
The source data that are utlized in this study are the clear subset RTP files provded by S. Sbuczkowski, and which have either the ERA or the ECMWF model fields and the SARTA TOA calculated radiance. Data from
Four studies are performed:
- pseudo-SNOs in the tropical oceans. May and June 2012, with ERA model fields.
- presudo-SNOs in the high-latitudes in the year 2012, with ERA model fields.
- True SNOs in the high latitudes in the year 2012, with ERA model fields and common SARTA.
- True SNOs in the high latitudes in the year 2016 with ECMWF model fields and common SARTA.
Original root directories of the RTP data are for CrIS and IASI respectively:
**/asl/rtp/rtp_cris_ccast_lowres/clear/ **
and
/asl/rtp/rtp_iasi1/clear/
The SNO data derived from the clear RTP subsets are located in:
/asl/s1/chepplew/data/sno/iasi_cris/LR/
and
/asl/s1/chepplew/data/sno/iasi2_cris/LR/
Data Production: Method and Code
The RTP generation and RTA calculated fields are described elsewhere (really - where??)
The IASI:CrIS Clear SNO from RTP subsets are formed using:
/home/chepplew/projects/sno/makeSNO/make_IASI_CRIS_SNO_frmRTP.m
and batch script:
batch_IASI_CRIS_SNO_frmRTP.m
The IASI CrIS tropical pseudo-SNO pairs are formed using:
/home/chepplew/projects/sno/makeSNO/make_IASI_lrCRIS_tsno_frm_rtp.m
and the batch scripts:
batch_IASI_lrCRIS_tsno_frm_rtp.m
batchJobs/batch_IASI_lrCRIS_tsno_frm_rtp.sh
and a list of dates for the batch processor:
batchJobs/jobDates.drv
All other IASI CrIS high-latitude sets are formed using:
/home/chepplew/projects/sno/makeSNO/make_IASI_lrCRIS_tsno_frm_rtp.m
and associated batch and driver files.
Data Analysis: Method and Code
The IASI:CrIS clear SNO correlation study uses matlab code:
/one/chepplew/gitLib/cris-corr/corr_clear_sno.m
The IASI:CrIS Tropical psuedo-SNO correlation study uses:
/home/chepplew/projects/corrcoef/ana_clear_tosno.m
which is based very closely on:
~strow/Work/Cris/Noaa/Ccorr/corr_processing.m
and associated scripts.
In all proceeding analysis and results a simple screening is applied for outliers based on the value of the bias error being greater than 6-sigma of the sample mean. This removes less than about 1% of samples. In addition, in each case the ILS radiances are hamming apodized.
The comparison of interest is how the CrIS correlation looks compared to that of IASI having been convolved to the CrIS ILS, but with CrIS having the equivalent of the IASI noise, which is larger than the CrIS noise. In other words we want the final CrIS noise to be the same as the IASI-to-CrIS noise. Therefore we want to modify the CrIS bias error, by an amount $ xn $
, given by:
$ (xn)^2 = (icn)^2 - (ncr)^2 $
where, $ icn $
is the IASI-to-CrIS noise, and $ ncr $
is the unmodified native CrIS noise.
The graphics shown here are also available in various formats (fig, pdf, png) on the maya computer at:
/home/chepplew/projects/corrcoef/figs
Results
IASI:CrIS clear RTP SNOs
IASI-1 and CrIS Overview plots:
SNO sets1 and 2: CrIS:IASI-1 and CrIS:IASI-2
It is important to remember that the actual observations determined to be cloud free from the two IASI instruments are different, and therefore the SNO sets are different. We refer to them as set 1 for CrIS:IAS-1 and set 2 for CrIS:IASI-2.
In this figure note that IASI-2 bias (Obs-calc) is slightly larger than that for IASI-1, and in the window region the Obs are colder than the calculations, perhaps due to effect of residual un-modelled clouds i nthe clear scenes. These observations have NOT had their noise adjusted (what I call native signals).