OSSE TO INFER THE IMPACT OF ARCTIC AMVs EXTRACTED
FROM HIGHLY ELLIPTICAL ORBIT IMAGERY
1
2
1
1
Louis Garand , Yves Rochon , Sylvain Heilliette , Jian Feng , and Alexander P.
3
Trishchenko
1
2
Environment Canada, Dorval , Qc, or Downsview , On, Canada
3
Canada Center for Remote Sensing, Ottawa, On, Canada
Abstract
An Observing System Simulation Experiment (OSSE) is performed to evaluate the impact of
atmospheric motion vectors (AMVs) made available from the future polar Communications and
weather (PCW) mission. PCW is a 2-satellite constellation on a highly elliptical orbit (HEO) which
will fill the AMV observation gap in the Arctic. All currently assimilated data types at Environment
Canada are simulated. A nature run (NR) is used as truth. The HEO AMVs are extracted from NR
cloud tops every 6 hours. Simulated observations are perturbed appropriately. Assimilation cycles
are run in 3D-var. The control experiments include geostationary AMV, and it can exclude or include
currently available polar AMVs from MODIS or AVHRR. The test experiment includes HEO AMVs
o
in area 50-90 N. When comparing cycles with no AMV versus one with PCW AMVs, results
o
o
indicate a clear positive impact, not only in region 50-90 N, but also in region 20-50 N. The gain in
predictability at days 3-5 is of the order of 1-3 hours. Similar impacts are obtained when comparing
the current operational system with one that adds PCW AMVs.
INTRODUCTION
There is a well recognized spatio-temporal gap of Earth observation from space in polar
regions. Ideally, the imagery at high latitudes should have similar coverage characteristics to
those provided by geostationary (GEO) satellites. Trishchenko and Garand (2012) have shown
that as many as 23 Low Earth Orbiting (LEO) satellites would be needed to get 15 min imagery at
o
60 N. The Canadian Polar Communications and Weather (PCW) mission addresses that issue. It
consists of two satellites in a highly elliptical orbit (HEO) with orbital period in possible range 12h
to 24 h, and apogees slightly higher than GEO height. Such a constellation, planned by the end of
this decade, would provide 100% coverage over the entire Arctic (Trishchenko et al., 2011).
Coverage of southern hemisphere high latitudes would require two more satellites.
High temporal coverage is particularly important for a product such as atmospheric motion
vectors (AMV) requiring image triplets or at least pairs. Today, AMVs are produced from MODIS
o
and AVHRR in polar regions, but there is a sizeable gap in region 55-70 latitudes, as shown in
Fig. 1. TERRA and AQUA satellites providing MODIS imagery are aging, and will not be
replaced. Furthermore, AVHRR does not have water vapor channels which are a desirable asset
to complement visible and infrared window imagery for AMV production. The goal of this work is
to evaluate the added value of filling the AMV gap in the Arctic in terms of impact on numerical
weather prediction forecasts. An Observing Simulated System Experiment (OSSE) is used for
that purpose, as described below.
OSSE DEFINITION
The OSSE consists of simulating all observations currently used in the operational analysis
used by the currently operational Canadian Global Environmental Multiscale (GEM) model with
resolution of about 35 km and 80 levels (top 0.1 hPa). AMVs are those from GEO and MODIS
(Fig. 1). The ~4 million observations include surface data, buoys, ships, wind profilers, radiosondes, drop sondes, aircrafts, scatterometer winds, GPSRO, multiple AMSU-A, MHS and MSUB radiances as well as those from AIRS, IASI, and GEO satellites. The observations are
simulated from a “Nature Run” (NR) which was produced by ECMWF at similar resolution to that
of GEM (40 km, 90 levels, see http://www.emc.ncep.noaa.gov/research/JointOSSEs ).
The original NR was interpolated to the GEM grid, and that version defines the “truth” for
evaluation purposes. Assimilation cycles covered two months. These are done in 3D-var mode
for efficiency purposes. The NR is defined in 2005-2006. In order to include more recent data
types such as IASI and GPSRO, the positions of data available at the same dates as the NR, but
three years later, are used. In the case of infrared radiances however, all sky radiances were
produced from the NR, followed by application of the same quality control procedures as those of
the real system (Heilliette et al., 2012). Further details of the OSSE setup are provided by
Rochon et al. (2012). Simulated data were perturbed in such a way as to reproduce closely
observed minus 6-h predicted (O-P) and observed minus analysis (O-A) statistics of the real
system. Perturbation levels are a simple multiplier of the assigned observation error. The latter
is most often “inflated”, that is higher then the std of (O-P). For AMVs, the perturbation factor is
0.28 and the observation error varies with height only, between 3 m/s near surface to 6 m/s at
high levels, as seen in Table 1.
1.
Figure.1. Example of current 6-h AMV coverage used in assimilation, including MODIS Terra and Aqua at high
latitudes. Note gap at latitudes 50-70o.
Level
hPa
Raob
m/s
AMDAR
m/s
AMV
m/s
1000
1.6
2.6
3.0
(O-P) AMV MVD
60-90N 20-60N (std,
m/s)
------
925
1.7
2.6
3.0
----
1.8
850
1.7
2.6
3.0
----
1.8
700
1.8
2.6
3.5
2.7
3.2
500
2.0
2.6
4.5
2.7
3.2
400
2.2
3.1
5.0
3.2
3.2
300
2.6
3.1
5.5
3.2
3.6
250
2.6
3.1
6.0
3.2
3.6
200
2.3
3.1
6.0
3.2
3.6
150
2.1
3.1
6.0
3.2
3.6
100
1.9
3.1
6.0
3.2
3.6
Table 1. Wind observation errors used in assimilation as a function of level. For reference std of AMV mean
vector difference (MVD) are shown, evidencing AMV error inflation.
PCW AMV DEFINITION
o
o
PCW coverage is complete above 60 N and about 90 % at 50 N. Thus there is no need to
simulate the actual orbit to extract from it AMV data. PCW AMV can be extracted directly from
the NR at the level of the cloud top every 6-h. Actually, the NR is available every 3-h, but it was
judged that, in 3D-var mode, using the data exactly at the time of analysis is preferable. The
extraction process is illustrated in Fig. 2. From the NR, the all-sky infrared window (11 micron)
radiance is computed. Cloud top is defined at the level where the cloud transmittance tc from
model top drops to 0.9 (Garand et al., 2011). No AMV are available in clear areas (tc > 0.9).
a)
b)
c)
Figure. 2. Extraction of PCW AMV from NR: a) synthetic 11 µm brightness temperature; b) estimated cloud top; c)
corresponding NR wind vector.
ASSIMILATION CYCLES
Cycles were ran from 15 December 2005 to 28 February 2006. The initial analysis was a 5day forecast from the NR. The first 8 days were not used in validation, which then starts on Dec
23. Five day forecasts were ran every 12-h. Results provided here are based on the following
OSSE cycles:
PR10: All operational data assimilated
PCWS: PR10 + PCW AMV
EXP1: PR10, but no AMV at all, no IR radiances
o
EXP2: EXP1 + PCW AMV (50-90 N)
PR10 is compared to PCWS, and EXP1 to EXP2. Infrared radiances were inadvertently
absent from EXP1 and EXP2, so that these experiments cannot be compared to the other two. A
cycle was also ran with the real system and compared to the same one without AMV. These
results (not shown) confirm the positive impact of real AMVs in all regions. PCW AMV thinning is
75 km for PCWS and 180 km for EXP2, which is that used for MODIS AMVs operationally.
RESULTS
Fig. 3 presents the temperature anomaly correlation for EXP1 and EXP2 cycles scored
against the NR. It can be seen that the 2-3 hours predictability gain remains significant up to day
5. A remarkable result is that this impact characterizes not only the region of PCW observations
o
o
50-90 N, but also the lower latitudinal region 20-50 N. Fig. 4 presents the same comparison
between the cycle simulating all operational observations (PR10, including MODIS AMVs) and
that adding to it PCW AMVs (PCWS). In that case, the impact remains significantly positive up to
day 3 (about 1-2 h gain in predictability).
Figure. 3. 500 hPa temperature anomaly correlation or EXP1 (no AMV, red) and EXP2 (with AMV, blue) cycles as
a function of forecast lead time. Validation against nature run. Left: 50-90oN; right: 20-50oN. Difference below
zero (green) indicates positive impact with 95% confidence intervals shown.
Figure. 4. Same as Fig. 3, but comparing PR10 (operational system) and PCWS (PR10 + PCW AMV) cycles.
Fig.5 provides zonal and vertical std differences between EXP1 and EXP2 temperature
forecasts when each experience is evaluated either versus the nature run or versus its own
o
analysis. In the region 50-90 N, the positive impact is imposed initially by the PCW data, and as
o
shown earlier, that impact extends to latitudes 20-50 N at 72-h. In the region of PCW AMV, the
impact at 24-h appears slightly negative when forecast are evaluated against their own cycle
analysis. However, at 72-h (and beyond), results are remarkably similar between the two modes
of validation (lower panels of Fig. 5). This is also noted for the other main variables (geopotential,
wind, humidity). Validating short forecasts against own cycle analyses yields lower differences
than against an independent analysis such as the NR, as seen by the difference on the scales
between the top panels of Fig.5. Impact analysis is more trustworthy beyond day 2 in the OSSE
system. To further appreciate these aspects, Fig. 6 compares EXP1 and EXP2 time series of
500 hPa temperature standard deviations between forecasts (24-h, 72-h, and 120-h) and
o
corresponding NR (left) or own analysis (right) in region 50-90 N. The agreement between the
two evaluations is remarkable at 120-h and it can be seen that several bad forecasts are avoided
by adding AMV data.
Figure. 5. Difference in std of temperature between EXP1 and EXP2 for 24-h (top) and 72-h (bottom) forecasts
evaluated against the NR (right) and against its own analysis within each cycle. Red denotes superiority of EXP2
(adding PCW AMVs).
Figure. 6. Time series of std of temperature between EXP1 (red) and EXP2 (blue) 24-h, 72-h and 120-h forecasts
and corresponding nature run analysis (left) and own cycle analysis (right). Mean values on the right with
percentage of cases where EXP2 has higher values (negative impact).
CONCLUSION
OSSE experiments were conducted to evaluate the impact of filling the AMV observation gap
in forecasts. Results suggest a gain in predictability of the order of 1-3 hours at day 3, not only in
o
o
the region of HEO AMVs (50-90 N), but in the region 20-50 N as well. Results of that nature
support the justification for realizing the PCW mission. Validation statistics against the nature run
and against own analysis cycle are very similar beyond day 2, providing confidence on the
conclusions. Further analysis can be carried out on several aspects. This include, in priority, a
comparison of impact resulting from the assimilation of real and simulated AMVs. This will help
substantiating the realism of the simulated assimilation system. Various assimilation details can
be evaluated such as data thinning, observation error assignment, or the use or not of AMVs in
regions of high density of aircraft observations. Evaluation in 4D-var should also be carried out.
The authors hope to complete this study with an extended publication.
REFERENCES
Garand, L., O. Pancrati and S. Heilliette, 2011: Validation of forecast cloud parameters from multispectral
AIRS radiances. Atmosphere Ocean, 49, 121-137. doi:10.1080/07055900.2011.567379.
Heilliette, S, Y. Rochon, L. Garand, and J. Kaminsky, 2012: Infrared radiance assimilation in the context of
Observing Simulated System Experiments. Submitted to J. Appl. Meteor.
Rochon, Y., J. Kaminsky, S. Heilliette, and L. Garand, 2012: Observation system simulation experiments for
th
the PREMIER mission. Proc., 5 WMO workshop on the impact of various observing systems on NWP,
Sedona, AZ, 22-25 May 2012, available from www.wmo.int .
Trishchenko, A.P., L.Garand, L.D.Trichtchenko, 2011: Three apogee 16-h highly elliptical orbit as optimal
choice for continuous meteorological imaging of Polar Regions. Journal of Atmospheric and Oceanic
Technology. Vol. 28(11), pp. 1407-1422.
Trishchenko, A.P. and L.Garand, 2012: Observing Polar Regions from space: Advantages of a satellite
system on a highly elliptical orbit versus a constellation of low Earth polar orbiters. Canadian Journal of
Remote Sensing. Vol. 38, No. 2, 13pp, In press.