A study on harmonizing total ozone assimilation with multiple sensors
Authors: Rochon Yves J. , Sitwell Michael , Cho Young-Min 
Published: July 2019

Abstract. Bias estimations and corrections of total column
measurements are applied and evaluated with ozone data from satellite
instruments providing near-real-time products during summer 2014 and 2015
and winter 2015. The developed standalone bias-correction system can be
applied in near-real-time chemical data assimilation and long-term
reanalysis. The instruments to which these bias corrections were applied
include the Global Ozone Monitoring Experiment-2 instruments on the MetOp-A
and MetOp-B satellites (GOME-2A and GOME-2B), the total column ozone mapping
instrument of the Ozone Mapping Profiler Suite (OMPS-NM) on the Suomi
National Polar-orbiting Partnership (S-NPP) satellite, and the Ozone
Monitoring Instrument (OMI) instrument on the Aura research satellite. The
OMI data set based on the TOMS version 8.5 retrieval algorithm was chosen as
the reference used in the bias correction of the other satellite-based total
column ozone data sets. OMI data were chosen for this purpose instead of
ground-based observations due to OMI's significantly better spatial and
temporal coverage, as well as interest in near-real-time assimilation.
Ground-based Brewer and Dobson spectrophotometers, and filter ozonometers,
as well as the Solar Backscatter Ultraviolet satellite instrument (SBUV/2),
served as independent validation sources of total column ozone data.
Regional and global mean differences of the OMI-TOMS data with measurements
from the three ground-based instrument types for the three evaluated 2-month periods were found to be within 1 %, except for the polar regions,
where the largest differences from the comparatively small data set in
Antarctica exceeded 3 %. Values from SBUV/2 summed partial columns were
typically larger than OMI-TOMS on average by 0.6 % to 1.2 %, with smaller
differences than with ground-based observations over Antarctica. Bias
corrections as a function of latitude and solar zenith angle were performed
for GOME-2A/B and OMPS-NM using colocation with OMI-TOMS and three variants
of differences with short-term model forecasts. These approaches were shown
to yield residual biases of less than 1 %, with the rare exceptions
associated with bins with less data. These results were compared to a
time-independent bias-correction estimation that used colocations as a
function of ozone effective temperature and solar zenith angle which, for
the time period examined, resulted in larger residual biases for bins whose
bias varies more in time. The impact of assimilating total column ozone data from single and multiple
satellite data sources with and without bias correction was examined with a
version of the Environment and Climate Change Canada variational
assimilation and forecasting system. Assimilation experiments for
July–August 2014 show a reduction of global mean biases for short-term
forecasts relative to ground-based Brewer and Dobson observations from a
maximum of about 2.3 % in the absence of bias correction to less than 0.3 % in size when bias correction is included. Both temporally averaged and
time-varying mean differences of forecasts with OMI-TOMS were reduced to
within 1 % for nearly all cases when bias-corrected observations are
assimilated for the latitudes where satellite data are present.