Transcript Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss Global Criteria for Tracing the Improvements of Radiosondes over the Last.

Federal Department of Home Affairs FDHA
Federal Office of Meteorology and Climatology MeteoSwiss
Global Criteria for Tracing the
Improvements of Radiosondes
over the Last Decades
P. Jeannet1), C. A. Bower2), B. Calpini1)
1) MeteoSwiss, Payerne
2) US NWS, Silver Spring
TECO-2006, WMO, Geneva, 05.12.2006
Task, action, deliverables
2004: WMO-CIMO ET on UASI-1
• Task: develop performance measures to
demonstrate the continuous improvement in the
quality of upper-air observations.
• Action: elaborate global criteria for tracing the
improvements, based on previous intercomparisons
and recent radiosonde development, and including
remote sensing
• Deliverables: IOM report on global criteria for tracing
the improvements of radiosondes
Tracing the Improvements of Radiosondes
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Preliminary analysis
• Following methods were considered:
• (1) using the previous IOM reports on the
WMO international radiosonde comparisons,
• (2) comparing radiosonde measurements with
ECMWF model values,
• (3) elaborating first a general CIMO
questionnaire to the NMHSs, or
• (4) extracting numbers from the scientific
literature.
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First WMO radiosonde comparisons:
WMO World Comparison of Radiosondes at
Payerne, Switzerland: 1950 and 1956
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WMO Radiosonde Comparison (Phase I) at
Beaufort Park, U.K., 1984.
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WMO Radiosonde Comparison (Phase VI) at
Vacaos, Mauritius, 2005
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using the previous IOM reports
Candidate criteria: priority to a short list
• Temperature:
• Mean difference @10hPa or 30 hPa DAY/NIGHT time
+ standard deviation
• Geopotential height
• Mean difference @10hPa or 30 hPa DAY/NIGHT time
+ standard deviation
• Mean difference @100hPa DAY/NIGHT time
+ standard deviation
• Humidity
• Mean difference in the temperature range -35 to -45C,…
(tropospheric values only) + standard deviation
• (Wind)
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Criteria (temperature and geopotential)
Criteria
Remarks
Temperature difference around*) 10 or The 10 hPa level is the highest standard level in the
30hPa, @ night/day time
TEMP messages. Reaching a high quality standard
around this level is a demanding task. Temperature
Standard deviation of the temperature errors are different during night and daytime (noon). A
differences around*) 10 or 30 hPa, @ higher data sample is found around 30 hPa than
around10 hPa, particularly in the first Phases.
night/day time
Geopotential difference around*) 10 or 30 Geopotential measurements from a radiosonde
hPa, @ night/day time
accumulate errors from other parameters (temperature,
pressure, etc.) between surface and this level. Recent
Standard deviation of the geopotential advances in GPS positioning have brought major
differences around*) 10 or 30 hPa, @ upgrade on this criteria.
night/day time
Geopotential difference around*) 100 hPa, The 100 hPa level is the primary level used in the
@ night/day time
quality control of upper air data based on comparison
with numerical model outputs.
Standard deviation of the geopotential
differences around*) 100 hPa, @ night/day
time
Tracing the Improvements of Radiosondes
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Pressure difference
around*) 100 hPa, @ Pressure criteria are very sensitive to the pressure range. 8
using the previous IOM reports
• Candidate criteria are based on differences
between simultaneous measurements
obtained with different types of radiosondes
launched under the same balloon (50-100
launches during an intercomparison)
•
The first WMO radiosonde comparisons defined 15 pressure categories in
the comparison of simultaneous measurements. The 10 hPa category
considered all measurements between 8.4 and 11.9 hPa, as defined by
the link sondes. The 30 hPa category was more exactly centred at 32 hPa
(24.5 – 41.5). The 100 hPa category range was 84 – 119 hPa. This
ensured that the statistics were relying on a sufficient number of timepaired measurements. In the more recent radiosonde comparisons, 2 km
wide altitude categories were introduced instead of the previous ones.
• This method represents a valuable tool for
comparison over the last two decades.
• Examples (Excel file and graph): systematic
temperature differences @10 hPa, @ day time
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using the previous IOM reports
Phase Systematic temperature
difference at 10 hPa, day time
in Degree Celsius
UK 1984
Phase I
USA 1985
Phase II
1984
1985
URSS 1989
Phase III
Japan 1993
Phase IV
Brazil 2001
Phase V
Mauritius 2005
Phase VI
1989
1993
2001
2005
Radiosonde
OCAN 1524-511
RS 3 (UK)
RS4 MK3(Aus)
MK-III (India)
Graw 78 C (D)
Graw DFM97 (D)
SMA-TC-1 (SMT) China
SMA-GZZ (SMG) China
MARS-2 (MRS) URSS
MRZ-3A (MRZ) URSS
Meisei RS2-80 (JP1)
-3.5
4d
-0.1
4d
0.4
-0.3
5.5
1.3
5.5
4d
-0.65
-2.76
5.10
-1.49
5.10
-2.8
5.10
Meisei RS2-91 (JP2)
-1.8
2.2a
0.1
2.2a
ppt
0.1
4d
-1.4
5.5
-1.01
5.10
-0.8
Vaisala RS80-15N (FN3)
9.13
2.2a
0.8
9.13
-0.2
9.13
0.25
9.13
0.3
9.13
-0.4
9.13
2.2.c
Vaisala RS80-15LH (FN2)
Vaisala RS90-…
Vaisala RS92-…
AIR IS-4A- (AR1)
1.26
5.10
0.7
-0.4
2.2a
AIR IS-4A- (AR3)
-0.3
2.2.c
VIZ 1392 (VIZ0)
0.6
Value
Statistics
Minimum
Maximum
Span
Mean
Mean Abs. Dev.
Tracing the Improvements
Sigma
Mean - 1*sigmaP. Jeannet et al.
Mean + 1 sigma
RMSD
4d
0
5.5
1.01
Fig. Number of
IOM report
-1
ppt
-0.2
ppt
2.2a
AIR IS-4A- (AR2)
VIZ Mark II (VIZ)
VIZ Mark II (VZ2)
VIZ Mark II (VZ3)
Sippican Chip (prototype)
Sippican LMS-5
GL-98 (MODEM)
SRS-C34
0.45
All individual values
extracted from the IOM
reports without any
modification
Meisei RS2-01G
Vaisala RS80-15N (FN1)
Systematic temperature
differences at 10 hPa, day
time, in degree Celsius.
5.10
1
2.2a
-0.1
2.2.c
-0.2
2.2.c
0.8
ppt
0.5
ppt
-0.9
ppt
-3.5
-1.4
-2.8
-1.8
-1.0
-0.4
0.6
1.3
1.3
1.0
0.8
0.8
4.1
2.7
4.1
2.8
1.8
1.2
-0.5
-0.1
-1.0
-0.2
-0.2
0.2
1.2
0.8
1.4
0.6
0.6
0.3
of Radiosondes
1.5
1.0TECO-2006 1.6
0.8
0.7
0.4
-2.0
-1.1
-2.6
-1.0
-0.9
-0.2
1.0
0.9
0.7
0.6
0.4
0.6
1.6
1.0
1.9
0.8
0.7
0.4
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using the previous IOM reports
Temperature bias at 10 hPa, day
Temperature difference (Degree C)
4
3
All individual values of the
previous slide, without any
additional information
2
Graph is „anonymous“
1
0
1980
-1
1985
1990
1995
2000
2005
-2
-3
-4
UK 1984 Phase I
Japan 1993 Phase IV
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USA 1985 Phase II
Brazil 2001 Phase V
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URSS 1989 Phase III
Mauritius 2005 Phase VI
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using the previous IOM reports
• Results presented in somewhat different forms
• final reports Brazil and Mauritius !
• Some intercomparisons addressing a “given” class of
parameters and thus…not presenting all the necessary
results.
• Brazil 2001: relative humidity measurements in the tropics and
performance of the GPS sondes.
• No true reference sonde, but “link radiosondes”: thus only
relative numbers can be extracted, but they are still
somewhat related to absolute accuracy
• Different sondes’ types…and additionally different data post
processing (correction of the radiation error on temperature,
etc.)
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Results
for geopotential altitude
Geopotential height bias at 10 hPa (night and day for all Phases)
2000
Bias of the geopotential
altitude around 10 hPa
(simultaneous
measurements)
Geopotential height difference (m)
1500
1000
500
0
1980
1985
1990
1995
2000
2005
-500
-1000
-1500
-2000
UK 1984 Phase I
Japan 1993 Phase IV
Std. Dev.
Tracing the Improvements of Radiosondes
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USA 1985 Phase II (versus radar)
Brazil 2001 Phase V (versus GPS)
Envelope
TECO-2006
URSS 1989 Phase III
Mauritius 2005 Phase VI (only GPS)
Span
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Standard deviations
of geopotential height differences
at 10 hPa
Results
for geopotential
altitude
(night and day time results for all Phases)
1800
Estimated random errors of
the geopotential altitude
around 10 hPa (simultaneous
measurements)
Std. dev. of differences (m)
1600
1400
1200
1000
800
600
400
200
0
1980
1985
1990
UK 1984 Phase I
URSS 1989 Phase III
Brazil 2001 Phase V (versus GPS)
Mean
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1995
2000
2005
USA 1985 Phase II (versus radar)
Japan 1993 Phase IV
Mauritius 2005 Phase VI (only GPS)
Envelope
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Results for temperature
Biastimes
of
Temperature bias at 10 hPa, day and night
the
temperature around
10 hPa (simultaneous
measurements )
night/day time
5
Temperature difference (Degree C)
4
3
2
1
0
1980
-1
1985
1990
1995
2000
2005
-2
-3
-4
UK 1984 Phase I
USA 1985 Phase II
URSS 1989 Phase III
Japan 1993 Phase IV
Brazil 2001 Phase V
Mauritius 2005 Phase VI
Std. Dev.
Envelope
Span
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Results for temperature
Reproducibility of temperature measurements at 10 hPa
Std. dev. of differences (Degree C)
3
Standard deviation of the
temperature around 10 hPa
(simultaneous measurements)
2.5
2
1.5
1
0.5
0
1980
1985
1990
UK 1984 Phase I
Japan 1993 Phase IV
Mean
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1995
USA 1985 Phase II
Brazil 2001 Phase V
Envelope
TECO-2006
2000
2005
URSS 1989 Phase III
Mauritius 2005 Phase VI
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Results for temperature
Results from WMO Radiosonde Comparison
demonstrating the range of systematic errors
in RS80 temperature sensor from 1984 to 2003
NIGHT
Temperature differences of Vaisala RS80 [link radiosonde]
at night from the working reference ,
WMO Radiosonde Comparisons + PREFRS
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Geopotential height [km]
Increase in error with
height
result of wrong
software correction at
low pressures
used extensively 1985-???
RS80(I and 2)night
RS80(PREF)night
RS80(3) night
RS80(4)night
RS80 (RH95) night
RS80 (BRAZ)
30
25
20
15
Around 1989-91, one of the two
calibration facilities was faulty
in the factory giving an additional
positive offset at low temperatures
for some batches of radiosondes
Software correction at low
pressures much
smaller in recent software,
1995- 2003
[ Met Office systems ,
1990 -2003]
10
5
• Results of process
analyses would
bring explanations
related to these
improvements
(Fig. from J. Nash)
0
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
Temperature difference [K]
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Results for pressure
Pressure bias at 100 hPa, dayBias
and night
oftimes
the
pressure
around 100 hPa
(simultaneous
measurements)
4
Pressure difference (hPa)
3
2
1
0
1980
-1
1985
1990
1995
2000
2005
-2
-3
-4
UK 1984 Phase I
Japan 1993 Phase IV
Std. Dev.
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USA 1985 Phase II
Brazil 2001 Phase V
Envelope
TECO-2006
URSS 1989 Phase III
Mauritius 2005 Phase VI (only GPS)
Span
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Results for pressure
Reproducibility of pressure measurements at 100 hPa
Std. dev. of differences (hPa)
3
Estimated random errors of the
pressure measurements
around 100 hPa (simultaneous
measurements)
2.5
2
1.5
1
0.5
0
1980
1985
1990
UK 1984 Phase I
URSS 1989 Phase III
Brazil 2001 Phase V
Mean
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1995
2000
2005
USA 1985 Phase II
Japan 1993 Phase IV
Mauritius 2005 Phase VI (only GPS)
Envelope
TECO-2006
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1995
V, 2001
None of the sensors reported identical humidity profiles. A final, and very important
conclusion is that it is doubtful that the sensor measurements can be accepted at
temperatures lower then -40 oC.
Results for humidity
In the troposphere up to around 8000 m, where the mixing ratio is large, the radiosonde
(see Mauritius
measurements
presented a low report)
dispersion. At higher altitudes the measurements were
highly dispersed.
VI, 2005
Estimating a suitable working reference is most difficult for relative humidity.
At night the two most reliable relative humidity sensors agreed on average within ±2
percent relative humidity from the surface to 14 km (-70 oC) over the full range of
relative humidity encountered in the intercomparison. This performance represents a
large improvement over any relative humidity sensing system in previous WMO
Radiosonde intercomparisons.
Large systematic biases in relative humidity measurements occurred in nighttime
measurements as well as in daytime measurements. At temperatures higher than -40°C,
maximum bias from the chosen reference at night was + 10 %. In the daytime, many
radiosonde types had systematic biases in the range -10 to -20 % relative humidity for
temperatures lower than -40 °C. Standard deviations of the differences between
different relative humidity sensors were usually relatively small (less than 5 per cent) at
temperatures higher than -40°C, so the random errors in relative humidity were usually
much smaller than the large systematic biases. This suggests that many of the large
systematic biases could be resolved by improved sensor mounting and exposure, plus
improved estimation/measurement of the relative humidity sensor temperature.
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Conclusions: radiosonde
improvements over the last 20 years
• Geopotential height around 31 km (10 hPa): the largest
improvements (one order of magnitude) due to GPS
• Temperature: an improvement by a factor of ~3 around
31 km.
• Pressure: large improvements, GPS technology is a
way of improving the pressure measurement accuracy
in the stratosphere
• Humidity: most challenging parameter, strong
deficiencies in the past, the Mauritius intercomparison
documents a large improvement over any hygristor in
the past.
• Wind: not studied, but large improvement due to GPS.
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Final remarks
• The proposed criteria can be extracted from the IOM
reports, as well as from other/further radiosondes
intercomparisons.
• They rely on comparisons of simultaneous (timepaired) measurements.
• This method provides valuable results, but also suffers
from some limitations despite the fact that the WMO
intercomparisons are very carefully organized.
• Remote sensing was not introduced in this study.
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