Line-by-line model development in support of the JCSDA PI – Eli Mlawer Co-PI – Jean-Luc Moncet...
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Line-by-line model development in support of the JCSDA PI – Eli Mlawer Co-PI – Jean-Luc Moncet Atmospheric and Environmental Research AER contributors:
Line-by-line model development in support of the JCSDA PI Eli
Mlawer Co-PI Jean-Luc Moncet Atmospheric and Environmental Research
AER contributors: Yingtao Ma, Gennady Uymin, Matt Alvarado, Karen
Cady- Pereira, Dan Gombos, Alan Lipton Other contributors to the
material presented: Vivienne Payne (JPL), David Turner (NOAA-NSSL),
Maria Cadeddu (DOE-ARL), Stefan Kneifel (U. of Cologne), Paul van
Delst (JCSDA), Quanhua Liu (JCSDA), Sid Boukabara (JCSDA) Joint
Center for Satellite Data Assimilation Workshop May 21, 2014
Copyright 2014, Supported by JCSDA external research program
through NOAA contract NA13NES4400002 Modernizing the Community
line-by-line radiative transfer models
Slide 2
Satellite data assimilation depends on accurate spectroscopy
Reducing uncertainties in spectroscopic line parameters and
continua is critical to improving the use of satellite data in
numerical weather prediction (NWP) and climate models. JCSDA
Community Radiative Transfer Model (CRTM) is trained using AER
line-by-line models Both OPTRAN-based CRTM and new version
developed with AERs OSS approach Two LBL models LBLRTM and MonoRTM
(Clough et al., 2005) _____________________________________________
Transition of our research focus in 2014 Formerly focused on
improving model quality accuracy, capabilities,... Current focus is
on modernizing the coding in the models Lesser focus on efforts
with respect to LBLRTM, MonoRTM, OSS enhancements JCSDA and
Line-by-Line Modeling at AER
Slide 3
Developing a Modern Community LBL Model Motivation Plan MonoRTM
Developments Release of MonoRTM_v5.0 Current LBLRTM Efforts H 2 O 2
band (1300-1900 cm -1 ) Planned Enhancement to MonoRTM Improved
Microwave Liquid Absorption Model Overview of Talk
Slide 4
AER LBL codes are highly respected in community Train fast
codes used operationally e.g. CRTM, RRTMG Reference LBL
calculations for RT code intercomparisons Code quality not up to
modern standards LBLRTM written in 1980s for that eras computing
environment Superb scientific achievement, as attested to by its
prevalence and importance today. However: Code assumes available
memory is small Extensive use of common blocks, equivalence
statements, etc. Difficult to enhance and maintain Goal: Keep the
physics, modernize the code. Motivation for Modernizing AERs LBL
Codes
Slide 5
Code example Equivalence between two very different vectors
Variable with dimension 2 equivalenced to multiple variables
Numerous instances of writing out and reading from disk Motivation
for Modernizing AERs LBL Codes
Slide 6
First step analysis of the existing code e.g. Construct calling
trees for each of the 19 modules in LBLRTM Developing a Community
Line-By-Line Model
Calling trees include the 301 subroutines in LBLRTM Analysis
also performed for common blocks in LBLRTM 214 distinct common
blocks 76 common blocks shared by more than one module 18 data
blocks used by LBLRTM Developing a Community Line-By-Line
Model
Slide 9
Goals of effort Develop a high-quality well-documented
supportable code Developmental approach modeled after inclusive
paradigm used for CRTM Maintain the codes current scientific
integrity Support future scientific advancement Extensive
collaboration with JCSDA Recommendations from JCSDA and wider
community (selected) Refactor LBLRTM in modern Fortran (e.g.
2003/2008) Input and output files in netcdf more appropriate names
for I/O files Allow use of any line parameter file in standard
format To the extent possible, eliminate max 2000 cm -1 restriction
Parallel computing capability Developing a Community Line-By-Line
Model
Slide 10
Design considerations Remove obsolete modules (e.g. Lowtran
aerosols, NCAR graphics plotting packages) Eliminate shared common
blocks replace with Fortran structures Minimize I/O May not be
possible to completely eliminate Dynamically allocate memory at run
time? Explore utility of keeping different spectral spacing for
each layer All program options need to be tested extensive test
suite Incremental approach to development one subroutine at a time,
ensuring that calculations dont change Developing a Community
Line-By-Line Model
Slide 11
MonoRTM upgrade Basic model features Monochromatic radiative
transfer model - Designed for use at a single frequency, same
physics as LBLRTM - Particularly appropriate for use in microwave
region Line shape: Voigt evaluated with Humlicek algorithm
(Van-Vleck Weiskopf) Line parameters in MW are from HITRAN 2012
with selected exceptions Continuum: MT_CKD_2.5 Liquid water
absorption model from Liebe et al. (1991)
Slide 12
MonoRTM upgrade MonoRTM_v5.0 released in December 2013
(rtweb.aer.com) -46 downloads (e.g. NOAA, NASA, numerous US
universities and foreign countries) More modular coding - supports
OSS-CRTM development -directly calls more LBLRTM subroutines
-utilizes same binary line parameter file as LBLRTM Upgraded
spectroscopy -HITRAN 2012 in MW with key exceptions (e.g. strengths
of 22/183 GHz H 2 O lines) -Changes in self widths of 22 GHz and
183 GHz H 2 O lines led to reanalysis of foreign widths as in Payne
et al. (2008) -Many lines added to default line list (accuracy 0.1
K for upwelling calculations) New capability to utilize line
broadening coefficients due to collisions from a specific molecule
(when available) -e.g. O 2 broadening due to H 2 O in microwave
(Drouin et al., 2014), CO 2 due to H 2 O Speed dependent line shape
option implemented (Boone et al., 2007, 2011) Output option for
spectral layer optical depths (netcdf) added
Slide 13
MonoRTM upgrade Differences between TOA brightness temperatures
calculated with MonoRTM_v5.0 and MonoRTM_v4.2 for a moist case (3.5
cm PWV) and SSMIS viewing geometry
Slide 14
Current version: LBLRTM_v12.2 Recent study - Alvarado et al.,
ACPD, 2013 Analysis of recent spectroscopic updates to LBLRTM with
respect to IASI measurements Ongoing studies Determination of
near-infrared water vapor self continuum coefficients from ground-
based measurements motivated by needs of Orbiting Carbon
Observatory II (OCO-II) Evaluation of HITRAN 2012 line parameters
in infrared using IASI and AERI measurements Evaluation of
sub-millimeter, far-infrared, and mid-infrared measurements from
the DOE-sponsored Radiative Heating in Underexplored Bands Campaign
II in Chile Planned upgrades to LBLRTM capabilities Line broadening
coefficients due to collisions from a specific molecule Allow
specification of vertical profiles of isotopologue abundances
Update on LBLRTM
Slide 15
Rigorous validation of recent spectroscopic updates to LBLRTM
against a global dataset of 120 near-nadir measurements from IASI.
The performance of LBLRTM v12.1 was compared to a previous version
(LBLRTM v9.4+) to test the impact of the latest updates to the line
parameters Conclusions: The improved CO 2 spectroscopy in LBLRTM
v12.1 can alter the retrieved temperature profiles by 0.5 K or
more. The LBLRTM v12.1 CO 2 spectroscopy is remarkably consistent
between the CO 2 2 and 3 bands. The H 2 O spectroscopy is improved
in both the P- and R-branches of the 2 band in LBLRTM v12.1, but
significant systematic residuals remain. Alvarado et al. validation
study of LBLRTM
Slide 16
Residuals in the H 2 O 2 band are improved Observation Mean
Residuals LBLRTM v12.1 Mean Residuals LBLRTM v9.4+
Slide 17
Residuals in the 616 JCSDA assimilated IASI channels are
substantially improved Mean Residuals LBLRTM v12.1 Mean Residuals
LBLRTM v9.4+ Observation
Slide 18
Evaluating HITRAN 2012 in H 2 O 2 band Mean Residuals aer_v3.3
line file Mean Residuals HITRAN 2012 Observation
Slide 19
Radiative Heating in Underexplored Bands Campaign (RHUBC)
Radiative heating/cooling in the mid-troposphere occurs primarily
in water vapor absorption bands that are opaque at the surface
Includes far-infrared, which contains ~40% of OLR - essentially
unvalidated Upper troposphere radiative processes are critical in
understanding the radiative balance of the tropical tropopause
layer and the transport of air into the stratosphere These
processes need to be parameterized accurately in climate
simulations (GCMs) RHUBC-II (PIs Mlawer and Turner) Cerro Toco
(~5400 m), Atacama, Chile August - October 2009 3 far-IR / IR
interferometers ~100 radiosondes, extremely low PWV (as low as 0.2
mm) 1 microwave radiometer for PWV
Slide 20
Transmission in the Infrared
Slide 21
Atmospheric Emitted Radiance Interferometer (AERI) ARM
Instrument developed at U. Wisconsin 550 - 3000 cm -1 (resolution
~0.5 cm -1 ) Far-infrared Spectroscopy of the Troposphere (FIRST)
PI - Marty Mlynczak, NASA-LaRC Michelson interferometer 100 - 1600
cm -1 (resolution ~0.64 cm -1 ) Radiation Explorer in the Far
Infrared (REFIR) Italian collaboration (RHUBC lead - Luca
Palchetti) Fourier Transform Spectrometer 100 - 1500 cm -1
(resolution ~0.50 cm -1 ) RHUBC-II Infrared Instruments
Slide 22
Spectral Observations 170 GHz (5.6 cm -1 ) to 3 m (3000 cm -1 )
SAO FTS (Smithsonian) FIRST (NASA/LaRC) REFIR (Italy) AERI (UW)
First ever measurement of the entire infrared spectrum from 3 to
1780 m!
Slide 23
Comparison between LBLRTM and RHUBC-II AERI 54 cases with PWV
< 0.3 mm AERI LBLRTM (aer_v3.3 line file) AERI-LBLRTM Stdev of
resids AERI uncertainty
Slide 24
IASI and RHUBC-II AERI present consistent pictures IASI-LBLRTM
(K) HITRAN 2012 aer_v3.3 Stdev (dotted) AERI-LBLRTM Stdev of resids
AERI uncertainty
Slide 25
IASI and RHUBC-II AERI present consistent pictures Very, very
preliminary conclusions -A number of apparent line width, strength,
position issues -No apparent issues with respect to water vapor
continuum in R- branch (1620-1900 cm -1 ) and in between P- and
R-branches (1595-1620 cm -1 ) of 2 band -Water vapor continuum may
be ~5% too strong in P-branch of 2 band (1300-1580 cm -1 ) Analysis
approach under consideration: use both IASI and AERI datasets in an
optimal estimation framework to retrieve key line parameters
(width, strength,...)
Slide 26
Future work upgrade MW liquid absorption model Research (e.g.
Cadeddu and Turner, 2011) have shown that existing liquid water
absorption models have issues, including the model (Liebe et al.,
1991) used by MonoRTM New study by Kneifel, Turner, Cadeddu, et al.
has derived a new absorption model Plan: introduce in MonoRTM later
this year Next few slides from material presented in Improving
Supercooled Liquid Water Absorption Models in the Microwave Using
Multi- Wavelength Ground-based Observations, by Turner et al. at
the 2014 Science Team Meeting of the DOE Atmospheric System
Research program
Slide 27
Motivation Accurate quantification of liquid water path (LWP)
in clouds critical for many atmospheric applications A large
fraction of liquid-bearing clouds are supercooled (T cloud < 0C)
There are very few laboratory observations of water vapor
absorption coefficient in microwave at supercooled temps Microwave
absorption models use semi-empirical models that are fit to warm
lab data and extrapolate to supercooled temps Translation: a lot of
uncertainty in LWP for T cloud < 0C !! MEI: Meissner and Wentz
(2004) RAY: Ray (1972) LIE: Liebe et al. (1991, 1993) STO: Stogryn
et al. (1995) ELL06: Ellison (2006) ELL07: Ellison (2007) Turner,
Kneifel, Cadeddu (2014)
Slide 28
Impact on retrieved LWP Turner, Kneifel, Cadeddu (2014)
Slide 29
Datasets used 31, 52, 90, and 150 GHz obs at three sites 225
GHz also available at Summit Summit station, Greenland,
3250mZugspitze, Germany, 2650m Black Forest, Germany, 511m Turner,
Kneifel, Cadeddu (2014)
Slide 30
Opacity ratios: Models vs. Obs A method from Mtzler et al.
(2010) is used to separate from liquid from other optical depths
using the temporal variability of the liquid. Turner, Kneifel,
Cadeddu (2014)
Slide 31
Absorption coefficient: Models vs. Obs Anchor these absorption
coefficients in the 90 GHz coefficients from the STO model, which
were validated in Cadeddu and Turner (2011) Turner, Kneifel,
Cadeddu (2014)
Slide 32
Building a new model Optimal estimation used to fit new
parameters for a double-Debye model (9 parameters), using Lab
observations, typically at temps between 0 and 30C (up to 100C),
most at frequencies below 60 GHz (up to 900 GHz) Derived opacity
ratios at supercooled temps Absorption coefficients from Stogryn
model at 90 GHz Results with respect to microwave radiometer
observations Turner, Kneifel, Cadeddu (2014)
Slide 33
Summary Transition of main focus from LBL model
quality/capabilities to code modernization Project underway to
create a modern Community LBL (CLBL) model Based on LBLRTM and
MonoRTM Design being done at AER, with key input from CRTM team
Requirements, project plan being finalized Implementation mainly to
be done in College Park by Yingtao Ma (AER) Major upgrade of
MonoRTM recently released Urge use of MonoRTM instead of models
without up-to-date spectroscopy Future upgrades of LBLRTM and
MonoRTM Challenging due to transition of focus our JCSDA external
research project Merging HITRAN 2012 and aer_v3.3 based on IASI and
RHUBC-II AERI data Liquid water absorption coefficient model
Upgrades of line broadening method and isotopologue handling
Slide 34
Acknowledgements S. A. Clough, Clough Radiation Associates
Marco Matricardi, ECMWF Joint Center for Satellite Data
Assimilation (JCSDA) NASA
Slide 35
IASI Closure Study Methodology Schematic of the retrieval
procedure. The dashed arrows show additional retrievals performed
to assess the consistency of CO 2 in the IASI spectral range. 120
clear-sky, nighttime, over ocean IASI profiles (a subset of
Matricardi, 2009) - minimize potential errors from clouds, surface
emissivity, and NLTE effects. Systematic spectral residuals after
retrievals indicate errors in the spectroscopy. A priori profiles:
Temperature: ECMWF adjusted between 10 mbar and 0.1 mbar (Masiello
et al., 2011). H 2 O: ECMWF model. O 3 : ECMWF model scaled by OMI.
CO 2, N 2 O, CH 4, and CO: Aura TES climatology
Slide 36
The addition of P- and R-branch line coupling improved
performance in the 2 band of CO 2 IASI Scan #754 Mean Residuals
LBLRTM v12.1 Mean Residuals LBLRTM v9.4+
Slide 37
The spectroscopy updates alter the temperature profiles
retrieved using the 2 band Right: Mean and std. dev. of the
differences between the temperature profiles retrieved with LBLRTM
v12.1 and v9.4+. Only the cases that converged for all four
model/band combinations are included.
Slide 38
Updates to the MT_CKD continuum have improved performance at
the 3 bandhead IASI Scan #754 Mean Residuals LBLRTM v12.1 Mean
Residuals LBLRTM v9.4+ Note that green 3 region was not used in
temperature retrievals here
Slide 39
The 2 and 3 temperature retrievals in LBLRTM v12.1 are
remarkably consistent. Mean and std. dev. of the differences
between the retrieved temperature profiles. Right panel: the 2
retrieval was smoothed with the 3 averaging kernel and
retrieval(Rodgers and Connor, 2003).