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A Method for D aily T emperature D ata I nterpolation and Q uality C ontrol B ased on the S elected P ast E vents Presentation for the 6 th Seminar for Homogenization and Quality Control in Climatological Databases Gregor Vertačnik Budapest, May 2008. Overview. Purpose - PowerPoint PPT Presentation
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ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
A A MethodMethod forfor D Dailyaily T Temperatureemperature D Dataata I Interpolationnterpolation andand Q Qualityuality CControlontrol B Basedased onon thethe S Selectedelected P Pastast E Eventsvents
Presentation for the 6th Seminar for Homogenization and Quality Control in Climatological Databases
Gregor Vertačnik
Budapest, May 2008
-12-10-8
-6-4-20
2468
10121416
1820
1.1.07 1.2.07 1.3.07 1.4.07 1.5.07 1.6.07 1.7.07 1.8.07 1.9.07 1.10.07 1.11.07 1.12.07
date
tem
per
atu
re [
°C]
20 similar days
measured
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
Overview
• Purpose• Description• The selection of similar days• Interpolation• Examples• Issues and disadvantages• Conclusion
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
Purpose
• Missing data interpolation and quality control of daily air temperature series at climatological stations (T7, T14, T21, Tmin, Tmax)
• In simple methods (e.g. with monthly correction factors) the same climate statistics regardless the weather type at given day is used
• Typical temperature diurnal ranges and spatial patterns in complex terrain (Slovenia):– Northeasterly föhn wind, Bora (warm and windy littoral, cold
interior)– Temperature inversion in valleys and basins (colder nights, fog,
larger/smaller diurnal range)• Aim of a new method: the use of climate statistics for the
corresponding weather type• Interpolation improvement:
– Reduction of interpolation error (standard deviation)– Better mean values for longer periods (month)
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
Climatological stations in the complex terrain of northwestern Slovenia, 1980: mountain-, plateau-, slope-, valley/basin-stations
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
An example of strong horizontal temperature (Tmax, yellow) gradient due to daily precipitation gradient (blue), August 29, 2003 (Val Canale flood). Stations below 1000 m are marked by a red circle.
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
Description
• Temperature interpolation at the target station on the chosen (target) day
• Two-step method:– Selection of the most similar days to the interpolated one
– Interpolation
• Use of temperature ranges and the spatial pattern:– Measurements before/after and at the interpolation time
(e.g. for Tmin, T21 the day before, Tmin, T7, T14)
– User-defined or the best-correlated nearby stations
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
The selection of similar days
• Minimum weighted Euclidean distance
• Input: temperature data at reference stations at the target and a similar day
• Weights based on Pearson correlation coefficient
• Two types of similarity:– Range and spatial pattern
(weather phenomena)– Absolute values (air mass)
6
8
10
12
14
16
18
20
22
24
26
28
18:00 21:00 0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
time (CET)
air
tem
per
atu
re [
°C]
T0 T1 T2
Temperature time series on Rudno polje (Pokljuka) 18-19 July, 2007 (T0) and
arbitrary similar series (T1, T2)
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
sv
psv
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• Basic weights:
• Normalized (standardized) average temperature deviation of a similar day from the target day:
• Normalized (standardized) weighted Euclidean distance between a similar and the target day:
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
Interpolation
• Basis: mean differences between the values of the reference variable at a reference station and the interpolated variable at the target station in the set of similar days
• Temperature estimation for each reference station
• Weighted mean of estimations
• Corrected for the number of days with the data
dayssimilar
s,d,S,D,s,sim
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An example of temp. estimatations at the reference stations, the final result and the measured value (in brackets)
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
• Minimum temperature in Portorož 2006-2007:– Reference stations:
1) Bilje2) Bilje, Postojna
– Reference variable: Tmin– Var. for the selection of simil. days:
a) Tminb) Tmin, T21_y, T14c) T14_y, T21_y, T7, Tmin, T14, Tmax
– 30 similar days– Reference period: 1991-2005– p1=1, p2=1, p3=2,kdev=0.5
Topography in western Slovenia with marked station locations
Stat \ Var a) b) c)
1) 1.69 1.65 1.63
2) 1.57 1.52 1.50
Standard deviation of the error in °C (Bilje + monthly correct. 1.80, Postojna + monthly correct. 2.35)
Examples
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
2.2
2.4
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
month
stan
dar
d d
evia
tio
n [
°C]
20 similar days 200 similar days Ljubljana only, all days
-16
-14
-12
-10
-8
-6
-4
-2
0
2
4
6
8
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31
day
tem
per
atu
re [
°C]
measured 20 similar days
200 similar days Ljubljana only, all days
• Minimum temperature at Ljubljana Airport, 2003-2007:– 5 reference stations (highest correlation)– Reference variable: minimum temperature– Reference period: 1995-2002– Var. for the selection of similar days:
T21 (the day before), T7, Tmin, T14, Tmax
– p1=1, p2=1, p3=2,kdev=0.97
Standard deviation of the error series
Standard deviation depending on the value of kdev
Result comparison, March 2004
1.09
1.1
1.11
1.12
1.13
1.14
1.15
1.16
1.17
0 0.2 0.4 0.6 0.8 1
k dev
stan
dar
d d
evia
tio
n [
°C]
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
Issues and disadvantages
• The choice of the weighting factors (depend on variables, stations)• How many days to select and variables to include?• Homogenous series strongly prefered! (possible solution iterative
process?)• Time consuming• Sometimes impossible to infer on local phenomena (lack of stations):
– wind (e.g. Karavanke föhn)– valley/basin fog– showers and thunderstorms
the reason for a large part of the variance remained unexplained (other meteorological variables and data at the target station should be included)
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
Conclusion
• Lower interpolation error compared to the most simple method (monthly correction factors)
• More stations and variables for the selection of similar days usually improve interpolation results
• The method is unable to recognize some local weather phenomena → other meteorological variables should be included
• Optimal parameter values vary from case to case• Homogenous series strongly prefered!
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIAENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA
www.arso.gov.si
Many thanks for your attention!