Assessment of MISR wind vector quality and impact using the
global NWP system at DWD
Alexander Cress
Deutscher Wetterdienst, P.O. Box 10465, 63004 Offenbach am Main, Germany
I Introduction
Global wind measurements are essential to improve our knowledge of atmospheric dynamics and to describe atmospheric transport processes of energy, water, air-borne
particles and trace elements. Atmospheric motion vector (AMV) wind fields - derived
from tracking cloud and water vapor image sequences - provide the only global tropospheric wind information for numerical weather forecast models and therefore make
an important contribution to the global observing system (GOS), particularly over the
oceans and polar regions were there are either no or only very few conventional wind
observations (WMO, 1998). However, substantial errors in derivating AMV wind vectors
can occur, due to erroneous pattern recognition, uncertainties of the height assignment
of the cloud-tracked winds or the dependency on a particular forecast as prior information.
Since Dec. 1999, a Multi-angle Imaging Spectral Radiometer (MISR) is flying on
board of the polar-orbiting satellite Terra, which is able to provide global tropospheric
cloud-tracked wind vectors and heights with high accuracy. It’s high spatial resolution
and multi-angle capability makes it feasible to simultaneously retrieve cloud height and
motion using a purely geometric stereoscopic technique (Horvach and Davies, 2001).
On behalf of the international wind working group (IWWG), MISR cloud tracked winds
were provided by NASA/JPL for a six week test period respectively, for summer 2010
and winter 2010/2011. In the following, first monitoring statistics and impact studies
concerning the quality of MISR wind vectors with respect to the data assimilation and
forecasting system of the Deutscher Wetterdienst (DWD) are presented.
II Verification results
The multi-angle imaging spectroradiometer on-board of Terra measures the sunlight reflected by earth with sensors oriented in nine different viewing angles along the satellite
track and allows the computation of the horizontal cloud motion vectors and there corresponding cloud heights with high accuracy using a purely geometric enhanced stereo
technique (Zong et al, 2002). Figure 1 shows the horizontal distribution of the MISR
wind measurements for one day in January 2011. Terra is the first EOS (Earth Observing System) platform and was launched on Dec. 18, 1999 into a sun-synchronous orbit
in 705 km height.
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Observation coverage MISR Winds
Date of Analyses: 20110101 - 20110102
Number of winds: 179814
-120
-80
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Figure 1: Horizontal coverage of MISR winds for Jan. 1, 2011.
The MISR instrument collects data only on the daylight side of the earth and observes points on the earth within a 360 km wide swath (Fig. 1) successively at all
nine angles within a seven minutes period viewing the earth in a period of nine days
(http://www-misr.jpl.nasa.gov/Mission/eosTerra/).
The vertical distribution of the MISR winds is depicted in Figure 2. Obviously, most
of the MISR winds are located in the lower levels of the troposphere between 500 and
5000 meters above ground. Most of the MISR winds are derived over the oceans. Over
land, very few winds can be found over high terrain covered by ice and snow (Himalaya
mountains, Rockies, Greenland, high areas of Antarctica) and over desert regions (Sahara) were high albedo values can disturb the measurements.
MISR Wind Distribution
height [m]
15000
10000
5000
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number
30000
Figure 2: Vertical distribution of MISR winds from the period Aug. 25 to Sept 15, 2010.
2
2.0•104
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All
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Number of Observations
Number of Observations
1.5•104
4000
1.0•104
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OBS-FG
Mean: -0.302115 RMS: 2.90976 Std: 2.89404 Min: -18.4766 Max: 34.7177
6•104
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Number of Obs.: 216500
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OBS-FG
Mean: -0.350129 RMS: 4.57713 Std: 4.56376 Min: -23.2360 Max: 47.3022
5000
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Number of Observations
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Number of Obs.: 53077
Active
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OBS-FG
Mean: 0.0338827 RMS: 2.84803 Std: 2.84783 Min: -24.0621 Max: 43.4167
0
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Number of Obs.: 597798
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OBS-FG
Mean: 2.14772 RMS: 5.41853 Std: 4.97474 Min: -22.8807 Max: 41.9252
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Number of Obs.: 87260
Figure 3: Frequency distribution of wind speed first guess departures (m/s) of MISR wind
observations with QI values larger than 80 for the winter period over the Northern Hemisphere
(upper panel) and the Southern Hemisphere (lower panel) separated over land (right) and sea
areas (left) for all data (green) and for data after a first guess quality control check (blue).
The quality of the MISR winds have been estimated against short range forecasts
(3 hourly) from the data assimilation and forecast system of the DWD for the periods
Aug. 15 to Sep. 30, 2010 and Dec. 1, 2010 to Jan. 15, 2011. The DWDs assimilation
and forecast system consists of a three-dimensional variational scheme in observation
space, using a variety of conventional (Synop, radiosonde, aircraft, buoy) and satellite
(AMSU-A from NOAA satellites, Aqua and Metop, various AMV winds, GPS radio occultation, etc.) observations and a global forecasting model on a triangular mesh with
a horizontal resolution of 30 km and 60 vertical levels. A detailed description can be
found in Majewski et al, 2002.
Similar to the AMV wind products, each MISR wind vector is assigned a quality
index (QI) indicating the usefulness of the derived wind. In contrast to the AMV QIIndex, the MISR obs - fg statistic shows very little dependency on the QI-Index. For
lower QI values there is a positive bias of approximately 1 m/s slowly decreasing with
increasing QI-Index. In a similar way the RMS values decreases slowly with increasing
QI, indicating growing quality of MISR winds with higher QI-Indices. There is very little
variation between the different hemispheres and seasons. Note that with increasing
QI the number of observations significantly decreases. In contrast to similar statistics
for AMV winds, no sharp drops of the mean RMS can be found in case of MISR wind
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Figure 4: Regional distribution of wind speed first guess departures (obs-fg m/s) of MISR wind
observations for the summer (upper panel) and winter period (lower panel) for winds with QI
larger then 80.
vectors, which makes it more difficult to set proper QI thresholds in order to filter out
low quality MISR winds. Following recommendations and practices of the IWWG only
MISR winds with QI values larger the 80 will be considered further in this study.
Over sea, the innovation statistic (obs-fg) for MISR winds follows a Gaussian distribution with very few outliers, indicating a high correspondence between MISR wind
observations and model first guess wind fields (Fig. 3). On the winter hemisphere,
there is a negative wind speed bias (model is faster than the observations) and on the
summer hemisphere the model is slower (positive bias). The wind speed RMS of the
innovations varies between 2.4 and 2.9 m/s and is very similar between summer and
winter but slightly larger on the Southern Hemisphere. Over land, the biases are much
larger and more outliers can be found, primarily on the Southern Hemisphere in winter,
where the bias is on average 2 m/s higher than in summer and the RMS exceeds 5
m/s with a lot of outliers which can be partly filtered out by the first guess check of the
assimilation system (Fig. 5, lower left). Over land the RMS is 1.5 to 2 times larger than
over sea, except for the Northern Hemisphere in summer. Here the bias and RMS
values are comparable to the values over sea. The higher bias and RMS values over
land can be attributed to a large extend to the high wind speed biases over regions
with high albedo values (Sahara desert) and elevated terrain with large reflectivity over
snow and ice (Greenland, higher regions of Antarctica). Here, the wind speed biases
exceed 5 m/s aligned with large RMS values (Fig. 4).
Over sea, the quality of MISR winds is comparable to the first guess wind field
(low bias and RMS values) and is also in good agreement with corresponding AMV
wind speed statistics. In Fig. 5 the mean MISR wind speed measurements and the
corresponding wind velocity observations from Meteosat 9 (visible channel) for summer
period shows a high level of compliance. After eliminating obvious erroneous MISR
winds over the Sahara, Greenland and Antarctica and after deploying a first guess
wind check, both independent measurement systems derive similar high wind velocities
over the baroclinic west wind zones over both hemispheres, stronger in winter than in
summer, lower wind speeds over the tropical oceans and the passat wind regions and
strong wind fields off the coasts of Namibia, Brazil and the Arabian peninsula during
the summer period.
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Figure 5: Regional distribution of time-averaged gridded wind speed observations from the
MISR instrument with QI values larger than 80 (upper panel) and the corresponding AMV wind
speed measurements from Meteosat 9 (visible channel) after first guess check for the summer
test period.
III Impact assessment
The global analyses and forecast system of the DWD was used to assess the impact
of MISR winds for the two periods, summer 2010 and winter 2010/2011. The control
experiment has the same configuration as the operational system and the MISR experiments includes the MISR wind dataset additionally to all the other routinely used
observations. The MISR winds are excluded over land and ice and only winds with a
quality index larger than 70 are used. Like other satellite wind observations, the MISR
winds are thinned to a resolution of 60 km. The observation fit statistics against radiosonde, aircraft and pilot wind observations show no significant differences between
the MISR experiment and the control run. For other satellite wind observations a reduction in bias can be found for winds derived from MTSAT-2 and Meteosat 7 over the
tropical areas of the west pacific and Indic oceans (not shown). A small increase in
mean wind speed analysis is found over the southern hemisphere using MISR winds
more pronounced for the u-wind component than for the v-wind component. In Fig.
6, a comparison of the 500 hPa geopotential height anomaly correlation coefficient
of the control and the experiment using MISR wind data separated for the northern
and the southern hemisphere, the Tropics and Europa is depicted for the winter period
2010/2011. A positive impact on the forecast quality over both hemispheres and Europa can be seen using the MISR wind observations, shlightly larger on the southern
hemisphere. For the summer experiment a positive impact can been deduced on the
northern hemisphere and Europa, whereas for the southern hemisphere a neutral to
slightly negative impact can be seen (not shown). For the tropics a small significant
positive impact can be found for both seasons using the MISR wind data additionally
to all other operational used observations. The impact is more pronounced over the
Pacific and Indic ocean than over the Atlantic ocean.
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GEOPOTENTIAL 500 ANOC 12h
NH
9635-09635
TR
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46 forecasts
2010120100 to 2011011512
9636-09635
46 forecasts
2010120100 to 2011011512
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Figure 6: Anomaly correlations for 500 hPa geopotential height in the northern (upper left),
southern (lower left) hemisphere, the tropics (upper right) and Europe (lower right) for the control (blue) and the experiment using MISR winds /red) verified against their own analyses for
winter 2010/2011
IV Conclusions
The data assimilation and forecast system of the DWD was used to estimate the quality
of MISR wind vectors, provided by NASA/JPL from two six weeks periods in summer
2010 and winter 2010/2011. Most of the MISR winds are derived in the lower levels of
the troposphere over ocean regions and much less winds are estimated over land, especially over regions with high terrain and high reflectivity (Greenland, Antarctica, Sahara). No strong dependency could be found between innovation statistics and MISR
QI-Index, which makes it difficult to filter out erroneous wind observations. The quality
of MISR winds is higher over sea than over land. Very large biases are found over
high terrain with high reflectivity (Greenland, Antarctica) and regions with high albedo
(Sahara desert). The correspondence between MISR winds and first guess wind fields
is large over sea with very few outliers. Over land the correspondence is weaker with
larger outliers which can be partly filter out by the first guess check. A strong regional
correlation between derived MISR wind velocities and corresponding AMV wind vectors could be assessed after eliminating strong biased MISR winds and a subsequent
used first guess wind check. Using the global assimilation and forecasting system of
the DWD a positive impact could been found for both hemispheres, the tropics and Europa using the MISR wind data set in addition to all other routinely used observation,
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more pronounced in winter than in summer. Given the availability of the MISR winds for
public use within three hours after observation, they represent a promising new wind
data source for operational usage in our global data assimilation system.
References
Horvath, A., Davies, R., 2001: Feasibility and error analysis of cloud motion wind
extraction from near-simultaneous multiangle MISR measurements. J. Atmos.
Oceanic. Technol., 18, 591-608.
Majewski, D., Liermann, D., Prohl, P., Ritter, B., Buchhold, M., Hanisch, T., Paul,
G., Wergen, W., Baumgardner, J. (2002): The operational global icosahedralhexagonal grid point model GME: Description and high resolution tests. Mon.
Wea. Rev., 130, 319-338.
Mueller, K, Garay, M., Moroney, C, Jovanovic, V. (2002): Misr 17.6 km gridded cloud
motion vectors: Overview and Assessment
Zong, J., Davies, R., Muller, J.P., Diner, D.J., (2002:): Photogeometric retrieval of
cloud advection and top height from the multi-angle imaging spectroradiometer
(MISR). Journal of the American Soc. for Photogrammetric Engineering and Remote Sensing 68 (8), 821-830.
World Meteorological Organization (WMO), (1998): Preliminary statement of guidance regarding how well satellite capabilities meet WMO user requirements in
several application areas.-WMO Satellite Reports SAT-21. WMOTD No. 913
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