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1 Joint report Overview of data homogenization procedures Zita Bihari, Tamás Kovács Hungarian Meteorological Service January 2011
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Joint report
Overview of data homogenization procedures
Zita Bihari, Tamás Kovács
Hungarian Meteorological Service
January 2011
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DELIVERABLE SUMMARY
PROJECT INFORMATION
Project acronym: DMCSEE
Project title: Drought Management Centre for South East Europe
Contract number: SEE/A/091/2.2/X
Starting date: 1. 4. 2009
Ending date: 31. 3. 2012
Project WEB site address: http://www.dmcsee.eu
Lead partner organisation: Environmental Agency of the Republic of Slovenia
Name of representative: dr. Silvo Žlebir, director
Project manager: dr. Gregor Gregorič
E-mail: [email protected]
Telephone number: +386 (0)1 478 40 65
DELIVERABLE INFORMATION
Title of the deliverable: Overview of data homogenization procedures
WP/activity related to the deliverable:
WP3, Activity 3.1.2
Type (internal or restricted or public):
Internal
Location (if relevant): N/A
WP leader: OMSZ
Activity leader: OMSZ
Participating partner(s): OMSZ, NIMH, AUA, GEORAMA, DHMZ, RHMSS, HI-M, HMS, INEUM
Author: Zita Bihari, Tamás Kovács
E-mail: bihari.z @met.hu
Telephone number: +36 13464727
DELIVERY DEADLINES
Contractual date of delivery to the JTS:
31. 5. 2010
Actual date of delivery to the JTS:
28.02.2011.
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TABLE OF CONTENTS
1. INTRODUCTION ............................................................................................................................................. 5
2. CURRENT STATUS OF HOMOGENIZATION PROCEDURES .............................................................. 7
2.1 HOMOGENIZATION METHODS ........................................................................................................................ 7
2.2 THE PROCESS OF HOMOGENIZATION .............................................................................................................. 7
2.3 HOMOGENIZED DATA SERIES ......................................................................................................................... 8
2.4 METADATA .................................................................................................................................................... 8
2.5 TREATMENT OF HOMOGENIZED DATA SERIES................................................................................................. 9
3. R&D STATUS – EFFORTS UNDERTAKEN IN ORDER TO IMPLEMENT CERTAIN
HOMOGENIZATION METHOD ..................................................................................................................... 10
3.1. PLAN TO HOMOGENIZE DATA SERIES ........................................................................................................... 10
3.2. REQUEST FOR PERSONAL TRAINING ............................................................................................................ 11
4. CONCLUSIONS ............................................................................................................................................. 12
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ABSTRACT
In Work Package 3 of DMCSEE project a mapping system as a precondition for the establishment of a
common methodology for drought assessment has to be developed. The aim of the Act 3.1 is the
preparation of climate data and maps. Outcomes of this Act 3.1 are three overviews about
climatological databases (Act 3.1.1), procedures used for data quality and homogenisation (Act 3.1.2)
and mapping procedures (Act 3.1.3).
In recent overview status of data homogenization procedures in partner institutes is described. We
present the applied homogenization methods, the homogenized data series and the plans for future
developments.
Contact address in Hungary: [email protected], [email protected]
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1. INTRODUCTION
One of the most important aims of DMCSEE project is mapping of drought. When somebody wants to
interpolate drought indices he need:
- good quality time series of various climate parameters
- reliable interpolation methods
In this overview homogenization methods applied by DMCSEE project partners are presented.
To facilitate the work of partners a questionnaire was prepared. It was fulfilled by those partners
who are climate data holders, namely the national meteorological services. This overview is based on
their work. These partners are the following:
Environmental Agency of Slovenia, Slovenia (EARS)
Hungarian Meteorological Service, Hungary (OMSZ)
National Institute of Meteorology and Hydrology, Bulgaria (NIMH)
Agricultural University of Athens and Hellenic National Meteorological Service, Greece (AUA-HNMS)
Meteorological and Hydrological Service, Croatia (DHMZ)
Republic Hydrometeorological Service of Serbia, Serbia (RHMSS)
Hydrometeorological Institute of Montenegro, Montenegro (HI-M)
Hydrometeorological Service, Republic of Macedonia (HMS)
Institute for Energy, Water and Environment, Albania (INEUM)
In the overview we tried to give a detailed description about the status of mapping procedures in
partner institutes. However if anyone has questions about different parts of the overview, the
following contact persons can answer them:
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Contact persons:
Institute Country Name(s) E-mail(s)
EARS Slovenia Gregor Gregorič
Mojca Dolinar
Gregor Vertačnik
OMSZ Hungary Zita Bihari
Monika Lakatos
NIMH Bulgaria Vesselin Alexandrov [email protected]
AUA
HNMS
Greece Christos Karavitis
Stavros Alexandris
Dimitris Stamatakos
Dimitris Tsesmelis
Vassilia Fassouli
Artemis Papapetrou
DHMZ Croatia
RHMSS Serbia Tatjana Savid
Predrag Petrovid
HI-M Montenegro Mirjana Ivanov
Gordana Markovic
Vera Andrijasevic
HMS Republic of
Macedonia
Nina Aleksovska [email protected]
INEUM Albania Liri Muçaj [email protected]
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2. CURRENT STATUS OF HOMOGENIZATION PROCEDURES
Availability of homogenized data series:
Homogenized data series are available: EARS, OMSZ, NIHM, DHMZ, INEUM.
2.1 Homogenization methods
Used methods:
EARS: The Craddock method was used to homogenize some temperature and precipitation series
(relative method).
OMSZ: Mash method (relative method).
NIMH: The Meteo-France, The HU weather service, The Canadian RHtestv2 (relative methods).
INEUM: Man test, Double mass curve.
Suitability of the methods:
For quality control of original data For completion of missing values
EARS Generally suitable Generally suitable
OMSZ Suitable Suitable
NIMH Partly suitable (e.g. The Meteo-France method)
Partly suitable (e.g. The Meteo-France method)
INEUM Not suitable Not suitable
2.2 The process of homogenization
Practice with homogenization:
EARS: Not performed regularly, it is based on request.
OMSZ: Once in a year, in the beginning of each year
NIMH: Up to now once.
INEUM: Once.
Location of the process:
EARS: Outside the data base. Homogenized data series are kept separately.
OMSZ: Outside the database.
NIMH: Outside the database.
INEUM: Inside the database.
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2.3 Homogenized data series
2.4 Metadata
EARS, OMSZ, DHMZ, INEUM: The homogenization method uses metadata as input.
NIMH: Metadata not used.
Institute Type of the
element
Temporal
resolution of
data series
Approximate rate of
missing data in original
series
Length of data
series
Number
of
stations
EARS Temperature Monthly/daily 8 % 100 - 151 Few
EARS Max. snow
cover depth
Annual 0 50 1
EARS Precipitation Monthly 4 % 100 -151 Few
OMSZ Temperature Daily 110 years 15
OMSZ Precipitation Daily 110 years 58
OMSZ Temperature Monthly 40 years 57
OMSZ Precipitation Monthly 60 years 177
OMSZ Rel. humidity Monthly 30 yeras
OMSZ Wind speed Monthly 30 years
OMSZ Cloudiness Monthly 30 years
NIMH Temperature Monthly <30% 50-100 years 40
NIMH Precipitation Monthly <30% 50-100 years 60
NIMH Sunshine
duration
Monthly <30% 50 years 10
DHMZ Temperature Annual 1% 50 years 20
DHMZ Precipitation Annual 1% 50 years 30
INEUM Temperature Monthly 3% 40 years 62
INEUM Precipitation Monthly 4% 40 years 62
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2.5 Treatment of homogenized data series
Storage of data series:
EARS: Homogenized data series are stored outside the “normal” climatological data base. Both the
original and homogenized series are stored.
OMSZ: Homogenized data series are stored outside the data base. Both the original and
homogenized series are stored.
NIMH: Homogenized data series are stored both inside and outside the data base. Both the original
and homogenized series are stored.
DHMZ: Both the original and homogenized series are stored.
INEUM: Both the original and homogenized series are stored.
Purpose of homogenized data series:
EARS: Climate studies. Main purpose is to prepare a homogenized data set for trend calculations
since it is frequently required to prepare homogenized data series
OMSZ: Climate studies.
NIMH: So far – research including climate studies
DHMZ: Research and climate applications
INEUM: Climate studies.
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3. R&D STATUS – EFFORTS UNDERTAKEN IN ORDER TO IMPLEMENT
CERTAIN HOMOGENIZATION METHOD
3.1. Plan to homogenize data series
EARS: The feasibility of the Craddock method is being studied for operational temperature series
homogenization and (in test mode) also precipitation data series.
OMSZ: No.
NIMH: Yes.
AUA-HNMS: Yes,
DHMZ:
RHMSS: Yes.
HI-M: Yes.
HMS: We are working on the program MASH from March 2010.
INEUM: No.
Details of demands:
Institute Type of the
element
Temporal
resolution of data
series
Approx. rate of
missing data in
original series
Length of data
series
Nr. of
stations
EARS Temperature Monthly ? 20 a–50 a+ > 100
EARS Precipitation Monthly ? 20 a–50 a+ > 300
EARS Sunshine duration Monthly ? 25 a + > 50
EARS Solar irradiance Hourly Few percent 5-17 years > 20
EARS Snow depth Monthly Few percent 20 a-50 a+ > 300
NIMH Temperature Monthly <30% 50-100 years 40
NIMH Precipitation Monthly <30% 50-100 years 60
NIMH Sunshine duration Monthly <30% 50 years 10
AUA-HNMS Temperature Daily 20% in monthly
series
45 years 45 - 50
AUA-HNMS Precipitation Monthly 20% 45 years 45 - 50
AUA-HNMS Relative humidity Monthly 20% 45 years 45 - 50
AUA-HNMS Wind Monthly 20% 45 years 45 - 50
RHMSS Temperature Annual/monthly 5% 1965 - present 55
RHMSS Precipitation Annual/monthly 5% 1965 - present 55
HI-M Temperature Monthly 60 years 10
HI-M Precipitation Monthly 60 years 10-up
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3.2. Request for personal training
EARS: Not at the moment.
OMSZ: No.
NIMH: Although NIMH can do data homogenization by itself, any help in the field would be useful.
AUA-HNMS: Mash is already used, they are in process of homogenizing monthly temperature series
from 5 stations in Eastern Aegean area. Help is definitely needed with Mash in order to homogenize
precipitaion and wind.
RHMSS: Yes.
HI-M: Yes.
HMS: Yes.
INEUM: No.
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4. CONCLUSIONS
The final aim of application adequate homogenized data series in the DMCSEE project is to make
regional maps of drought indices. While the drought index calculations are based on long time data
series, use of homogenized data is very important. However the half of partners don’t have
homogenized data series unfortunately.
While the SPI index is based only on monthly precipitation sum, homogenization of the necessary
input precipitation data can be solved in a simple way.
In the frame of the project OMSZ can give personal training to the partners who need help in
homogenization. The experts of OMSZ can travel to the parner’s institute and help in the
homogenization of their own data. The organization of travel began with HI-M but OMSZ is waiting
for the request of other partners.
