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2nd Baltic Earth Conference
The Baltic Sea Region in Transition
Helsingor, Denmark
11 - 15 June 2018

BACC II


 

PIDCAP - Pilot Study for Intensive Data Collection and Analysis of Precipitation

Project description compiled by Hans-Jörg Isemer, International BALTEX Secretariat, 10 September 1995


The initial implementation plan for BALTEX foresees intensive observational periods in order to provide basic data sets for the analysis and diagnosis of synoptic-scale systems and extreme events in the BALTEX region. The first of such an intensive observation period was PIDCAP, the BALTEX Pilot Study for Intensive Data Collection and Analysis of Precipitation.

The objectives of PIDCAP included

  • the validation of the output of different models against such precipitation data sets,
  • the development, testing and establishment of necessary data management and analysis procedures (especially the co-operation between different research groups and the BALTEX Meteorological Data Center) for future comprehensive studies in the framework of BALTEX,
  • and the collection, analysis and intercomparison of measured and estimated precipitation from different data sources in order to identify and establish reliable standards for model validation.

The observational period of PIDCAP was scheduled for August to October 1995, the area of interest being primarily the BALTEX region south of about 60 N, with the possibility of further extension, if nessecary. Precipitation data sets to be compared included standard data (gauge land stations) and non-standard data (research vessel, specially equipped ships of opportunity, from satellite radiometer SSM/I and from radar stations). Modeling groups at e.g. MPIfM, GKSS, DMI, and SMHI were to perform model runs with different regional models for the same period. 15 different research projects from five countries were included in PIDCAP.


Summary

The Initial Implementation Plan for BALTEX, the Baltic Sea Experiment, foresees Intensive Observation Periods in order to provide basic data sets for the analysis and diagnosis of synoptic-scale systems and extreme events in the BALTEX region. The first of such an Intensive Observation Period is PIDCAP, the BALTEX Pilot Study for Intensive Data Collection and Analysis of Precipitation. The objectives of PIDCAP include 1)the collection, analysis and intercomparison of measured and estimated precipitation from different data sources in order to identify and establish reliable standards for model validation, and 2) the validation of the output of different regional models against such precipitation data sets. The observational period of PIDCAP is scheduled for August to October 1995, the area of interest is primarily the BALTEX region south of about 60 N, with the possibility of further extension, if necessary. Precipitation data sets to be compared will include standard data (gauge land stations) and non-standard data (research vessel, specially equipped ships of opportunity, from SSM/I and radar stations). Modelling groups at MPIfM, GKSS, DMI and SMHI will perform model runs with different regional models for the same period. At present, 15 different research projects from five countries are included in PIDCAP.

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Introduction

A number of challenging tasks for BALTEX, as outlined in the Scientific Plan for BALTEX, can adequately be solved only in close co-operation between scientists and groups from different research directions or disciplines. Measurement and modelling of precipitation will be a key issue in order to meet the objectives of BALTEX. For validation of model results reliable ground truth data must be established. This includes estimates of their uncertainties. Ground truth data will have to be compared against each other in order to identify their specific potential with respect to model validation. At a national BALTEX workshop in Germany the need for intense co-operation between different national groups within the German BALTEX contribution and with BALTEX groups in other countries has been recognized. As a consequence plans for co-operation and interaction between groups have been outlined during this workshop. An ad-hoc working group on problems of precipitation measurements pointed out the urgent need for an organized initiative to collect rain data from different sources for comparison and validation purposes. The implementation of this initiative was planned in form of an Intensive Observation Period. The workshop suggested to organize a BALTEX Pilot Study for Intensive Data Collection and Analysis of Precipitation (PIDCAP).

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Objectives of PIDCAP

The objectives of this pilot study are to collect and analyse measured and estimated precipitation from different data sources, to compare different precipitation data sets against each other in order to identify and establish reliable standards for model validation, to validate the output of BALTEX Regional Models against such precipitation data sets, to develop, test and establish necessary data management and analysis procedures (especially the co-operation between different research groups and the BALTEX Meteorological Data Center) for future comprehensive studies in the framework of BALTEX. As a first step only rain events will be studied. The key data collection and modelling period of PIDCAP will be August to October 1995. The area of interest for PIDCAP has been defined as the southern BALTEX region south of about 60N. It will include both land surfaces and the Baltic Sea area.

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Implementation of PIDCAP

The BALTEX Science Steering Group, on its second meeting in Helsinki, January 25-27, 1995, considered PIDCAP as an important contribution to BALTEX and recommended international participation. The Initial Implementation Plan for BALTEX identifies two types of field experiments in order to investigate physical processes related to the energy- and water cycle of the BALTEX region:

  • field experimental campaigns studying small- and meso-scale processes, and
  • Intensive Observational Periods, the principle objectives of which are to provide basic data sets for the analysis and diagnosis of synoptic scale systems and extreme events in the BALTEX region.

PIDCAP will be mainly an Intensive Observation Period, scheduled for August to October 1995. Additionally, a field campaign is scheduled for September 1 - 9, 1995, when the research vessel ALKOR of IfM Kiel will operate in the Baltic proper east of the island of Gotland. Part of the contributions to PIDCAP described in section 4 are closely related to this ALKOR cruise. For estimating rainfall and in order to validate rainfall predictions from models BALTEX will rely on a combination of different techniques with different characteristics concerning e.g. estimation technique, and resolution in time and space. The major objective of PIDCAP is to compare such rainfall estimates from different sources for at least part of the BALTEX area, and to identify their particular strengths and weaknesses. In a second step measured and estimated amounts of rainfall will be compared to model outputs. Time resolution of rain estimates will be at least one day. If possible, time resolution should be increased to 12 or 6 hours. PIDCAP is meant to be a pilot experiment for later comprehensive BALTEX research phases. In this sense PIDCAP will serve as a test for procedures to combine data sets from different measurement and modelling sources. These procedures need to be developed towards a near-operational state. Hence, participation of the BALTEX Meteorological Data Center is an important step in order to test and, if necessary, to improve or develop data exchange strategies for BALTEX. PIDCAP will rely on methods already available at different BALTEX participants or other groups. It will be run in addition of expertise" mode: Each group is expected to determine rain in the BALTEX area by its own techniques for a given area and a given period of time. During the experiment there will be no central experiment co-ordination and no central logistics. Necessary contacts between individual groups have to be organized primarily by the participating groups. In order to prepare feasible data exchange during or after the study another co-ordinating meeting with participation of all groups will be performed before the start of PIDCAP, preferably in June 1995. This meeting will be organized by the International BALTEX Secretariat in co-operation with the Institute of Marine Sciences in Kiel (IfM). However, in general, it is recommended that participating groups develop their own co-ordination of activities and procedures in PIDCAP. Both, IfM Kiel (L. Hasse) and the International BALTEX Secretariat will prepare and survey PIDCAP in a more loose manner, but activities have primarily to originate from the participating groups. There will be no extra or central funding for PIDCAP. Participants will need to rely on their own sources and funding to support their participation in PIDCAP.

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Contributions to PIDCAP

A first coordinating meeting for PIDCAP took place on October 10, 1994 at IfM Kiel. The participating groups defined their research interest for PIDCAP. An announcement for PIDCAP was formulated and distributed asking for further participation of other groups. To date, research groups in Sweden, Finland, Denmark, Austria, Great Britain and Germany have indicated their interest to participate in PIDCAP. Two projects from SMHI dealing with HIRLAM precipitation forecasts and meso-scale precipitation analysis including radar data from the NORDRAD network, a modelling project at DMI and a precipitation analysis project at Vienna University confirmed contribution to PIDCAP. A BALTEX workshop was held in Minsk, Belarus, at the beginning of November 1994. During that workshop representatives of six countries which already co-operate within BALTEX (Belarus, Estonia, Latvia, Lithuania, Poland and Russia) indicated their intention to participate in PIDCAP. The intention is to provide a comprehensive data set of daily rainfall amounts measured at all existing conventional rain stations in those regions of the above-mentioned countries which are part of the BALTEX area. This will include, in particular, those stations which do not transmit their data into international accessible data centers, and hence, will not be available on a routine basis. It is anticipated that further intentions of participation should be indicated until early spring 1995 to either IfM Kiel (L.Hasse) or the BALTEX Secretariat (for addresses see section 5). In the following the participating research groups of PIDCAP and their research interests are shortly described. At present 15 projects are included in PIDCAP:

They are described with more detail at the following pages.

I Rain estimates from ship gauges - Ferry-boats

1. Principal Investigators: L. Hasse
2. Institute:Institut fuer Meereskunde, Kiel
3. Participants: K. Niekamp and M. Grossklaus
4. Scientific Objective: Determine rain at the Baltic Sea
5. Methodology and Approach: We have deployed recording rain gages at ferries of the route Luebeck / Helsinki. This provides rain amounts for the main body of the Baltic Sea. The data can be used to establish a rain climatology of the Baltic Sea and to calibrate other techniques of rain estimation.
6. Measurement or Data Collection Plan: Data are collected at ships that run continuously between Luebeck and Helsinki and are about 40 hours out of 48 hours at sea. Special ship rain gages are used that are suitable to measure rain at moving ship. Rain amounts are determined every 8 minutes and are recorded together with the position for later analysis. We intend to equip two additional ships with ship rain gages in 1995. The data are collected along the mayor shipping route in the long direction of the Baltic Sea.
7. Analysis Technique: The data collection at running ship can be seen as a sampling for a given location along the ship route. For the determination of rain climatology, the rain amounts are corrected according to the time fraction of ship in area to total time. This provides a rain climatology along the back bone of the Baltic Sea. The simplest analysis techniques is to compare data at sea with data from shore stations, and draw isolines according to distance from shore (traditional analysis techniques). A better extrapolation from the line to the area is via numerical weather forecast models (NWF model). Such model provide fields of rain forecast for the area. Calibration against ship rain measurement of forecasted rain would lead to an improved determination of rain for the Baltic Sea.
8. Data Requirements, Co-operation: Rain measurements from shore stations and rain estimates from NWF models.
9. Time Plan: Two ships at present take observations continuously.
10. Additional Remarks: We would try to help to equip additional ships with ship rain gages, preferably such that do meteorological routine observations already. We intend to co-operate with other groups who need verification data from the sea.

II Rain estimates from ship gauges - Research vessel

1. Principal Investigators L. Hasse
2. Institute: Institut fuer Meereskunde, Kiel
3. Participants: K. Niekamp
4. Scientific Objective: Shipborne rain measurements for validation of rain estimates at sea from remote sensing methods and numerical weather forecast models.
5. Methodology and Approach: Rain will be measured at R.V. ALKOR by a mechanical ship rain gage and an optical disdrometer. The instrumentation is designed to allow measurements at a moving ship. Measurements are to be taken at a position where radar measurements are available and conditions are favourable for microwave satellite remote sensing of rain.
6. Measurement or Data Collection Plan: R.V. ALKOR will operate east of Gotland the first 10 days of September 1995 and collect rain data. Standard sampling interval is 8 minutes for rain amount and drop spectra. Data can be combined to hourly averages.
7. Analysis Technique: Data are available as short term (8 minute) and hourly rain amounts for a given position or cruise leg. The ship rain gage collects rain at a horizontal and a vertical rain collecting surface. Total rain amount is calculated as a function of local relative wind speed from the two items of information. The ship rain gage has been calibrated with reference to disdrometer measurements.
8. Data Requirements, Co-operation: Fields of frontal and convective rain for the position / cruise leg of R.V. ALKOR from any kind of rain estimation.
9. Time Plan: R.V. ALKOR will be available at the site east of Gotland from about 1 through 9 September 1995. Measurements will be made on route from Kiel to Gotland and return starting 25 August, ending 11 September 1995.
10. Additional Remarks: We will also try to measure air sea momentum transfer by the so-called eddy dissipation technique.

III Application of Microwave Radiometry to Estimate Rainfall

1. Principal Investigators E. Ruprecht
2. Institute: Institut fuer Meereskunde, Kiel
3. Participants: C. Fueg, H. Gaeng, C. Simmer
4. Scientific Objective: Developing and application of algorithms to estimate rainfall over the BALTEX area, in particular over the sea.
5. Methodology and Approach:

  • a) Application of single parameter algorithms (published in the literature) to SSM/I data.
  • b) Use of the numerical results of a BALTEX mesoscale model e.g. REMO as input for a microwave radiative transfer model and simulation of brightness temperatures, TB, comparison between simulated and observed TB, "correction" of the geophysical parameters including precipitation rate to obtain an agreement between simulation and observation.

6. Measurement or Data Collection Plan: There are no observations planned by our own group.
7. Analysis Technique:
8. Data Requirements, Co-operation:

  • a) SSM/I data 8 tapes per month per satellite (at present 2 satellites)
  • b) Numerical results of REMO (or similar mesoscale BALTEX model)
  • c) Rain gauges data from the ferry boats (see L. Hasse)
  • d) Rain gauges data from land stations
  • e) RADAR data: DWD, NORDRAD

9. Time Plan:

  • a) SSM/I data are in general available 2 - 3 months after observation period.
  • b) The working group of REMO at GKSS estimates 3 - 4 months for the completion of the numerical results

10. Additional Remarks:

  • a) Additional financial support is needed for the purchase of the SSM/I data: US$ 125,00 per tape plus handling, postage. That is 24 tapes for 3 months and 1 satellite: US$ 3.000.00, for all 2 satellites: US$ 6.000,00. That is about DM 9.600,00.
  • b) Additional data from other satellite (METEOSAT, NOAA) in the VIS and IR spectral range should be available from other groups of the German BALTEX community.

IV Airborne validation of cloud and precipitation parameters

1. Principal Investigator: D. Offiler
2. Institute: United Kingdom Meteorological Office
3. Participants: D. Jones, S. English
4. Scientific Objective: Validation of RT models decribing (precipitating) clouds for developement of passive microwave precipitation and liquid water path (LWP) algorithms (e.g. for AMSU, SSM/I, SSM/T1+2, MIMR)
5. Methodology and Approach:

  • To use C-130 thermodynamic and microphysical data and NORDRAD data to populate an RT model for comparison with SSM/I and airborne microwave radiometer radiances at 23.8, 50.3, 89 and 157 GHz.
  • To use C-130 in situ data to validate SSM/I LWP algorithms and to test performance of these algorithms in precipitating systems. These algorithms will also be validated against LWP derived from C-130 microwave radiometers.

6. Measurement or Data Collection Plan:C-130 flights will be coordinated with RV Alkor, DMSP overpasses and NORDRAD radar network. The C-130 has a long endurance and may operate at all heights up to approximately 10 km. Comprehensive measurements of standard thermodynamic parameters, cloud microphysics and narrow- and broad-band-infra-red radiation are made as well as passivemicrowave pbservations at a range of frequencies.
7. Analysis Technique:LWP retrieval algorithms have already been developed by UKMO and expertise exists in combining radar and aircraft data for radiative transfer modelling at microwave frequencies.
8. Data Requirements, Co-operation:

  • All DMSP passive microwave radiances
  • Ship/ferry raingauges
  • NORDRAD rainfall fields
  • 3D reflectivity fields from Rostock radar
  • "Alkor" radiometer TBs and derived water vapor burdens/LWPs

9. Time Plan:These may a few months delay in producing "definitive" calibrated microwave TBs from the aircraft radiometers. In situ thermodynamic and microphysical values could be made available on a shorter time scale.

V Case Study of Precipitation Systems over the Baltic Sea

1. Principal Investigators: E. Ruprecht and C. Simmer
2. Institute: Institut fuer Meereskunde, Kiel
3. Participants: C. Fueg, H. Gaeng, D. Ramm
4. Scientific Objective: Investigation of the microwave radiation of rain clouds for validation of microwave radiative transfer models and algorithms to estimate rainfall over the sea.
5. Methodology and Approach:During a 2 week period August/September 1995 an experiment on the research vessel "Alkor" is planned in the center of the Baltic Proper. Measurements are planned on board with the following instrumentation:

  • radiosondes launched from the ship to describe the thermodynamic state of the atmospheric column above
  • microwave radiometer, to measure the downwelling microwave radiances
  • ceilometer, to determine the height of the cloud base
  • instrumentation to measure sea surface temperature and meteorological data at ship level: temperature, humidity, wind, radiation. The data are used a input for:
  • the radiation model to simulate the upwards and downwards directed microwave radiances
  • the mesoscale cloud model GESIMA to simulate the (vertical) distribution of cloud water and ice content and of precipitation water.

6. Measurement or Data Collection Plan:

  • a) radiosonde observations (T,RH,v) several times per day: at the times of satellite overpasses (SSM/I) and depending on certain weather situations (precipitation systems).
  • b) microwave data from the ship-borne radiometer: continuously
  • c) synoptical observations: every hour (including SST)
  • d) cloud base height: continuously.

7. Analysis Technique:
8. Data Requirements, Co-operation: In addition to the observations carried out on board the following data are required for the period of the experiment:

  • a) SSM/I data of all overpasses
  • b) Satellite data in the VIS and IR spectral range from NOAA-satellite (AVHRR), METEOSAT
  • c) Precipitation data from gauge on "Alkor"
  • d) RADAR data (NORDRAD, DWD) 3-dimensional for the experimental site horizontal distribution of derived precipitation over the Baltic Sea
  • e) numerical results of REMO.

9. Time Plan:

  • a) The experiment is planned for the time period of August 23 to September 6, 1995. The data will be processed in the following two months.
  • b) Satellite data
    • VIS, IR data are normally available within one month after observation
    • SSM/I data are available 2 - 3 month after observation

  • VI Derivation of rain rates from satellite data using a combination of visible, infrared, and microwave data

    1. Principal Investigators. J. Fischer
    2. Institute: Freie Universitaet Berlin
    3. Participants: R. Bennartz, A. Thoss
    4. Scientific Objective: Although several global retrieval algorithms for cloud and rain parameters based on microwave data over ocean exist, the application of these algorithms to the BALTEX region is rather problematic. Two major reasons for that are: First, global algorithms may not represent special climatic regions very well. Second, the Baltic Sea is mainly comprised of coastal waters. Taking into account the low resolution of spaceborne passive microwave radiometers, algorithms developed for open ocean conditions will fail. In order to tackle these problems we will derive synergic algorithms using a combination of infrared and visible data, which has a high resolution, and microwave data. Employing these algorithms, datasets of cloud liquid water content, instantaneous rain rates, and other parameters will be made available.
    5. Methodology and Approach: In the microwave region a broad range of physically realistic atmospheric conditions will be simulated using an existing matrix operator model. Additionally, statistical information derived from NOAA/AVHRR and METEOSAT data will be included in the retrieval algorithms.
    6. Measurement or Data Collection Plan: Data from NOAA/AVHRR, METEOSAT and DMSP/SSM/I is needed. Further, radio-soundings for the BALTEX region are needed as input for radiative transfer simulations.
    7. Analysis Technique: The simulated and statistical datasets will be inverted using gradient methods.
    8. Data Requirements, Co-operation: NOAA/AVHRR and METEOSAT data are operationally archived at the FU Berlin. Microwave datasets (SSM/I) for the PIDCAP study period from August to October 1995 have to be purchased from Remote Sensing Systems, Santa Rosa, California. The total expenses for that will be about 800 US$/month = 2400 $ total. In order to validate the retrieval algorithms, especially for rain rates, it will be necessary to get rain radar measurements.
    9. Time Plan: Preliminary studies will be done until May 1995. First results of the retrieval algorithms will be available at October 1995.
    10. Additional Remarks: Additional financial support is needed, to purchase the SSM/I data for the PIDCAP study period (see. 8.).

    VII Weather Radar Data for PIDCAP

    1. Principal Investigators: J. Riedl (DWD, MOHp)
    2. Institute: German Weather Service (DWD), Meteorological Observatory Hohenpeissenberg (MOHp)
    3. Participants: I. Doelling
    4. Scientific Objective: Provision of radar reflectivity data and area precipitation data.
    5. Methodology and Approach:

    • a) Filter technique investigations (Doppler, statistical) and optimization of the signal processor parameters
    • b) Topical Z/R-relation derived from Distrometer data
    • c) Calculation of area precipitation (100 km range) and adjustment by surface rain gauge data (see additional remarks)
    • d) Extraction of three-dimensional radar reflectivity data from the Rostock radar (see additional remarks)
    • e) Estimation of the precipitation coverage of the southern Baltic Sea by compositing NORDRAD, Danish and German radar data.

    6. Measurement or Data Collection Plan:

  • 1. November 94 - July 95

    • a) Preparation radar Rostock (performance, clutter effects, storage capacity)
    • b) Preliminary evaluation Distrometer/Ombrometer data Rostock (and Fehmarn)
    • c) Preparation of access to NORDRAD and Danish radar data and to wind data.

    2. August 95 - December 95

    • a) Operational radar data collection including Distrometer/Ombrometer data (DWD)
    • b) Data collection NORDRAD and wind data for selected periods
    • c) Calculation of adjusted area precipitation data.

    7. Analysis Technique: 8. Data Requirements, Co-operation

    • a) NORDRAD data
    • b) Ship rain gauge data (L. Hasse, Kiel)
    • c) Surface rain gauge data (DWD)
    • d) Wind data (DWD-network, masts and buoys in the Baltic Sea).

    9. Time Plan: November 94 - July 95 (6.1) and August 95 - December 95 (6.2).
    10. Additional Remarks:

    • a) To 5c): Adjusted data of daily accumulated area precipitation will be calculated for up to 10 selected days of the period.
    • b) To 5d): The extraction will be performed for the predetermined satellite passages.

    VIII Swedish Weather Radar Data for PIDCAP

    1. Principal Investigators: T. Andersson
    2. Institute: Swedish Meteorological & Hydrological Institute Research & Development
    3. Participants: T. Andersson, D. Michelson
    4. Scientific Objective:

    • a) To improve our ability to use radar for analysing precipitation.
      - To improve our knowledge of the characteristics and behaviour of precipitation.
      - To improve our knowledge of the characteristics and behaviour of clutter types.
      - To improve current methodology for identification and removal of artifacts in radar data caused by clutter.

    • b) To improve our ability to use radar for analysing winds.
      - To develop a methodology for utilizing clear air echoes when analysing winds (during warm seasons).

    5. Methodology and Approach:

    • - Image analysis methods on 2-D PseudoCAPPI imagery.
    • - Improved methods for analysis and processing of 3-D polar data.
    • - Improved analysis of vertical reflectivity profiles.

    6. Measurement or Data Collection Plan:

    • a) NORDRAD composite imagery:

      • - archive all individual reflectivity and wind images

      • - generate and archive all composite images

      • - generate and archive corrected composite images (see point 7).

    • b) Precipitation from satellites

      • - archive ZNP volume scans from Gotland, coincident with DMSP SSM/I image acquisitions.

    • c) UKMO C-130 campaign: week 36 (see project IV in this report)

      • - archive reflectivity and wind colume scans from the Gotland, Karlskrona and Norrkorping radars.

    7. Analysis Technique:
    8. Data Requirements, Co-operation: Knowledge of DMSP SSM/I data asquisition times. (C. Simmer, Kiel, see project V)
    9. Time Plan Data collection: August - October 1995. Data analysis: Autumn - Winter 1995-96.
    10. Additional Remarks:

    IX Rain measurements at land stations, daily values

    1. Principal Investigators: A. Lehmann
    2. Institute: Deutscher Wetterdienst (DWD) Offenbach Meteorological Data Centre for BALTEX at DWD
    3. Participants: R. Luckner
    4. Scientific Objective: The Meteorological Data Centre for BALTEX will be the service centre for all national and international participants in BALTEX research activities as regards meta-information on data, data collection and data exchange. PIDCAP should be the first testing phase to develop, test and establish necessary management and analysis procedures.
    5. Methodology and Approach: MDC obtained information about precipitation data in the BALTEX countries by an questionnaire, which was distributed to all meteorological and hydrological services, participating in BALTEX. The information about delayed data is expected to be not yet complete for some countries. The MDC will contact international participants in order to supply the information.
    6. Measurement or Data Collection Plan: The BALTEX MDC partly works as a METADATA Centre. The following types of data are planned to be stored physically at DWD (relating to PIDCAP):

    • - all data of the German meteorological network
    • - all data of the PIDCAP area (type SYNOP and TEMP), transmitted in real time via GTS.

    The MDC will endeavor to obtain additional delayed precipitation data, measured and stored in the countries participating in PIDCAP.
    7. Analysis Technique:
    8. Data Requirements, Co-operation: The success of taking available additional non-real-time data from abroad will depend on the co-operation of PIDCAP nations.
    9. Time Plan: Real-time data will be available as quick-look data with only a very short delay. Non-real-time data of German precipitation network will be available about 2 month's after the end of a measuring period.
    10. Additional Remarks:

    X a Validation of model results of precipitation

    1. Principal Investigators: B. Rockel
    2. Institute: GKSS Forschungszentrum Geesthacht
    3. Participants: U. Karstens, R. Nolte-Holube
    4. Scientific Objective: Validation of the BALTEX Version of the Regional Model (REMO), in particular the validation of the parameterization for rain fall. Computations will be carried out using the physical parameterization routines developed by the German Weather Service (DWD). The results will be compared to measured precipitation rates and the results of the study proposed by the Max-Planck-Institute for Meteorology in Hamburg (MPI), (see proposal IXb) .
    5. Methodology and Approach:REMO is based on the "Europa-/Deutschland- Modell (EM/DM)" weather forecast models of the DWD. The user can choose between two implemented physics: the original EM/DM and the ECHAM4 physics.
    6. Measurement or Data Collection Plan: Spatial resolution of precipitation data calculated by REMO is 18 x 18 km2. Temporal resolution is approximately 5 min; however, a minimum of 1 h for model output is preferred. The output format is either HDF or WMO GRIB1. 30h forecasts will be performed using the hours 6 to 30 for precipitation interpretation.
    7. Analysis Technique:
    8. Data Requirements, Co-operation: Analysis data (six hourly EM initial analysis) of the DWD are required for the selected period. These data are used to run the REMO in low resolution (55 x 55 km2, l-REMO) that calculated the boundary values for REMO in high resolution (18 x 18 km2, h-REMO). We are interested in all data relevant for the atmospheric energy budget and water cycle, especially rainfall data.
    9. Time Plan: Per workday normally we can run one l-REMO/h-REMO combined 30h forecast on the Cray C916 at the German Climate Computing Centre in Hamburg. Therefore, we will need about three months to get all results for the selected period (Aug. - Oct. 1995). If we could get the analysis data by day from the German Weather Service during that period, the results can be obtained latest end of November 95.
    10. Additional Remarks:

    X b Validation of model results of precipitation

    1. Principal Investigators: M. Claussen
    2. Institute: Max-Planck-Institut fuer Meteorologie, Hamburg
    3. Participants: D. Jacob
    4. Scientific Objective: Validation of the Regional Model (REMO) with respect to parameterization of processes relevant for rain fall. The parameterization routines implicit in the Hamburg climate model ECHAM4 will be tested and compared with the performance of the routines implicit in the Europa-/Deutschland-Modell (EM/DM) weather forecast models of the German weather service (DWD) (see proposal IXa).
    5. Methodology and Approach: REMO is based on the EM/DM weather forecast models of the DWD. REMO includes prognostic equations of temperature, humidity, and liquid water instead of total heat and total water content as used in EM/DM. Two packages of parameterization routines can be chosen: from EM/DM and from ECHAM4.
    6. Measurement or Data Collection Plan: Spatial resolution of precipitation data calculated by REMO is 18 x 18 km2 . Temporal resolution is approximately 2 - 3 min; however, only 1h-mean values are stored as model output. The output is GRIB 1.
    7. Analysis Technique:
    8. Data Requirements, Co-operation: Analysis data (six hourly EM initial analysis) of the DWD are required for the selected period. These data are used as boundary values for REMO. We are interested in all meteorological data (mean sea level pressure, wind, temperature, cloudiness, and, particularly, precipitation) that can be used for comparison with REMO results. Co-operation is planned with DWD and GKSS (see proposal IXa).
    9. Time Plan: Under favorable circumstances, it takes approximately one month to simulate one month. Depending on the availability of the EM initial data, the simulations can be finished by December.
    10. Additional Remarks:

    XI Validation of model results of precipitation - HIRLAM at DMI

    1. Principal Investigators: B. Sass
    2. Institute: Danish Meteorological Institute (DMI), Copenhagen
    3. Participants: DMI staff
    4. Scientific Objective: Validation of the atmospheric water cycle in the HIRLAM forecasting system during the PIDCAP period.
    5. Methodology and Approach:The most recent version of the HIRLAM analysis and forecast model will be used. The model domain is chosen to agree with that used at SMHI. In addition, this applies to the horizontal and vertical model resolution. The data assimilation and forecasts with the HIRLAM forecasting system will be carried out in delayed mode at DMI in contrast to the procedure applied at SMHI. This method has the advantage that conventional meteorological data that may not be available due to real time cut-off limitations can be utilized in the analyses.
    6. Measurement or Data Collection Plan: The atmospheric analysis frequency is 6 hours. For validation of the parameterized precipitation it is relevant to consider forecasted precipitation up to a forecast range of at least 24 hours. Such forecasts will be done daily, with precipitation data stored every 3 hours for the BALTEX region. For selected periods the frequency may be increased to one hour.
    7. Analysis Technique:
    8. Data Requirements, Co-operation: The experience gained from the real time data assimilation and analysis with the HIRLAM system at SMHI will be utilized at DMI. The processing in delayed mode (see the time plan) also enables the utilization of various precipitation data made available to the modelling groups for validation.
    9. Time Plan: The data assimilation system including extensive diagnostics related to the water cycle is set up during spring 1996. The results of the precipitation validation utilizing other data obtained during PIDCAP should become available one year later.
    10. Additional Remarks:

    XII HIRLAM precipitation forecasts for PIDCAP

    1. Principal Investigators: K.-G. Karlsson 2. Institute: Swedish Meteorological and Hydrological Institute (SMHI), Norrkoeping, Sweden
    3. Participants: K.-I. Ivarsson, K.-G. Karlsson, N. Gustafsson
    4. cientific Objective: Validation of precipitation forecasts from the mesoscale version of the HIRLAM model.
    5. Methodology and Approach: HIRLAM is the basic regional weather prediction model used at all the Nordic meteorological institutes. A special version is used at SMHI which includes a prognostic scheme for cloud water (the Sundqvist scheme), an improved radiation scheme and a new physiographic database with a better description of roughness and surface characteristics (topography, forest and vegetation types, land and sea fractions in each gridpoint etc.). In this study, a fine-resolution version of HIRLAM will be used having a horizontal resolution of 20 km and including 24 vertical layers.
    6. Measurement or Data Collection Plan: The mesoscale HIRLAM version will be run operationally in parallel with the standard version of HIRLAM at the time for the PIDCAP experiment. Precipitation forecasts will be stored and collected for the area of interest. At least two forecast runs will be performed each day (00ÊUTC and 12 UTC) producing accumulated precipitation in three hour intervals. A higher time resolution (one hour) may alternatively be used.
    7. Analysis Technique:Not applicable.
    8. Data Requirements, Co-operation: No special requirements.
    9. Time Plan: The mesoscale HIRLAM is introduced operationally 15 February 1995. Preparations for the collection of HIRLAM forecasts for the area of interest will be done before August 1995. Results will be compiled in its final form by the end of 1995.
    10. Additional Remarks: Special case studies could be introduced for studying particularly interesting weather situations to test parametrization and model formulations.

    XIII Gridded mesoscale precipitation data for six hour periods during PIDCAP

    1. Principal Investigators: L. Haggmark
    2. Institute: Swedish Meteorological and Hydrological Institute (SMHI), Norrkoeping, Sweden
    3. Participants: D. Michelson
    4. cientific Objective: Our objective is to create a database containing gridded analyzed precipitation information for every six hour period, during the BALTEX PIDCAP. The used grid resolution will be 0.1 degree.
    5. Methodology and Approach: The analysis is based on optimal interpolation, where consideration is taken to the various data sources specific qualities, such as accuracy and sensor internal pixel correlation. Analysis will be accomplished by integrating data from NORDRAD, observations from the synoptical and climate station networks, and forecasts from HIRLAM.
    6. Measurement or Data Collection Plan: All NORDRAD, synoptical and HIRLAM data generated during the PIDCAP will be saved and used in the analysis.
    7. Analysis Technique Preprocessing of weather radar data before creating NORDRAD composites includes applying automated routines for removal of clutter and anomalous propagation echoes. See point 5 for analysis method
    8. Data Requirements, Co-operation
    9. Time Plan: Analysis during the first half of 1996.
    10. Additional Remarks:

    XIV Monthly gridded precipitation data

    1. Principal Investigators: B. Rudolf
    2. Institute: Global Precipitation Climatology Centre DWD Offenbach/Main.
    3. Participants: B. Rudolf
    4. cientific Objective: Monthly gridded area-mean precipitation from different sources, separately, intercompared as well as merged:

    • - rain-gauge measurements
    • - IR geosynchr. satellite observations
    • - DMSP-SSM/I polarorb. satellite observations
    • - NWP model results
    • - climatic long-term means.

    5. Methodology and Approach: Objective analysis of rain-gauge data by spatial distance/directional interpolation (method SPHEREMAP after Willmott et al.). Satellite based estimates provided by the GPCP Satellite Centres operated by NOAA and NASA (methods: GPI for IR, emission after Wilheit et al. and scattering after Ferraro et al. for SSM/I). Model based accumulated from daily ECMWF results. Grid size 0.5 degree latitude by longitude.
    6. Measurement or Data Collection Plan: GTS data (SYNOP and CLIMAT reports) will be prepared to be used in the analysis with delay of about one month after observation. Additional raingauge data from national sources will be prepared with delay of about one month after delivery. The delay of delivery is unknown. Satellite based estimates will be available with a delay of about six months after observation. Model results will be prepared with delay of about one month after forecast.
    7. Analysis Technique: See under 5.
    8. Data Requirements, Co-operation: Monthly precipitation data from co-operating countries have to be acquired and (partly) digitized by the help of BALTEX secretariat.
    9. Time Plan: Gridded single-source estimates will be available one month after data delivery (see 6.). Results of intercomparison studies are expected to be obtained by mid of 1996.
    10. Additional Remarks:

    XV Objective analysis of surface precipitation

    1. Principal Investigators: M. Hantel, F. Rubel
    2. Institute: Institute for Meteorology and Geophysics, Univ. of Vienna - Institute for Medical Physics, VU-Vienna
    3. Participants: M. Hantel, F. Rubel
    4. cientific Objective: Grid point representation of the precipitation field over BALTEX based on rain gauge and radar data.
    5. Methodology and Approach The surface precipitation data routinely available in the SYNOP network will be analysed with the method of optimal averaging (Gandin, 1993). Routinely observed radar data will be used as background field (first guess). This method guarantees optimum use of the radar information (high space/time coverage) and the surface information (high local accuracy).
    6. Measurement or Data Collection Plan: Three sources of routinely observed data will be combined for the present project:

    • (1) Regular SYNOP data;
    • (2) Radar data (European sources); and
    • (3) Additional data from the BALTEX Data Centre.

    7. Analysis Technique:The technique described in 5. can be run in a coarse mode and in a fine mode. The present coarse mode over Europe has a space/time resolution of 100 km/12 hours, dictated by the SYNOP network. Preliminary runs over Austria in the fine mode (Rubel, 1994) resolve down to 12.5 km and 1 hour in time. The fine mode requires additional climate data; during PIDCAP it shall be further elaborated.
    8. Data Requirements, Cooperation: The technique described will be applied for selected cases. To the extent that BALTEX data become accessible the evaluation will be applied to the inner BALTEX area. This requires cooperation with the other PIDCAP groups.
    9. Time Plan: - Until end of 1995: Test runs; coarse mode completed. - 1996: Runs of selected cases in fine mode.
    10. Additional Remarks

    List of Acronyms and Abbreviations

    AMSU Advanced Microwave Sounding Unit
    AVHRR Advanced Very High Resolution Radiometer
    BALTEX Baltic Sea Experiment
    DMI Danish Meteorological Institute, Copenhagen / Denmark
    DMSP Defense Meteorological Satellite Programme
    DWD Deutscher Wetterdienst, Offenbach / Germany
    ECHAM European Climate Model - Hamburg Version
    ECMWF European Center for Medium Range Weather Forecast, Reading / UK
    EGS European Geophysical Society
    EM / DM Europa Modell / Deutschland Modell
    GESIMA Geesthachter Simulations Modell der Atmosphaere
    GKSS GKSS Research Centre, Geesthacht / Germany
    GIS Geographical Information System
    GPI GOES Precipitation Index
    GOES Geostationary Operational Environmental Satellite
    GRIB Grid in Binary Format
    GTS Global Telecommunication System
    HDF Hierarchical Data Format
    HIRLAM High Resolution Limited Area Model
    IfM Institut für Meereskunde, Kiel / Germany
    IR Infrared
    LWP Liquid Water Path
    MDC Meteorological Data Centre
    METEOSAT European Meteorological Satellite Series of EUMETSAT
    MIMR Multi-frequency Imaging Microwave Radiometer
    MOHp Meteorological Observatory Hohenpreissenberg
    MPIfM Max Planck Institut für Meteorologie, Hamburg / Germany
    NASA National Aeronautics and Space Administration
    NOAA National Oceanic and Atmospheric Administration
    NORDRAD Nordic Weather Radar Network
    NWF Numerical Weather Forecast Model
    NWP Numerical Weather Predciction
    PIDCAP Pilot Study for Intensive Data Collection and Analysis of Precipitation
    REMO Regional Mode
    RT Radiative Transfer
    SMHI Swedish Meteorological and Hydrological Institute, Norrkoeping/Sweden
    SPHEREMAP Interpolation Method
    SSM/I Special Sensor Microwave/Imager
    SST Sea Surface Temperature
    TB Brightness Temperature
    UKMO United Kingdom Meteorological Office
    VIS Visible
    WMO World Meteorological Organization

    Addresses

    • Dr. Tage Andersson
      Swedish Meteorological and Hydrological Institute
      S-60176 Norrkoeping
      Sweden
      +46-11-158467
      +46-11-170207
      tandersson@smhi.se

    • Prof. Dr. Martin Claussen
      Potsdam Institut fuer Klimafolgenforschung
      Postfach 601203
      D-14412 Potsdam
      Germany
      +49-331-288-2522
      +49-331-288-2600
      claussen@pik-potsdam.de

    • Prof. Dr. Juergen Fischer
      Freie Universitaet Berlin
      Institut fuer Weltraumwissenschaften
      Fabeckstrasse 69
      D-14195 Berlin
      Germany
      +49-30-838 66 66
      +49-30-832 86 48
      fischer@zedat.fu-berlin.de

    • Lars Haggmark
      Swedish Meteorological and Hydrological Institute
      S-60176 Norrkoeping
      Sweden
      +46-11158407
      +46-11170207
      lhaggmar@ux.005.smhi.se

    • Prof. Dr. Michael Hantel
      Universitaet Wien
      Institut fuer Meteorologie und Geophysik
      Hohe Warte 38
      A-1190 Wien
      Austria
      +43-1360263001
      +43-1365612
      michael.hantel@univie.ac.at

    • Prof. Dr. Lutz Hasse
      Institut fuer Meereskunde
      Universitaet Kiel
      Duesternbrooker Weg 20
      D-24105 Kiel
      Germany
      +49-431-5973875
      +49-431-565876
      lhasse@ifm.uni-kiel.d400.de

    • Dr. Hans-Joerg Isemer
      GKSS Forschungszentrum
      International BALTEX-Secretariat
      Postfach 1160
      D-21494 Geesthacht
      Germany
      +49-4152-87-1536
      +49-4152-87-2020
      isemer@gkss.de

    • Dr. Karl-Goran Karlsson
      Swedish Meteorological and Hydrological Institute
      S-60176 Norrkoeping
      Sweden
      +46-11-158407
      +46-11-17020
      kgkarlsson@smhi.se

    • Dr. Angela Lehmann
      Deutscher Wetterdienst
      BALTEX-Datenzentrum Postfach 10 04 65
      D-63004 Offenbach/Main
      Germany
      +49-69-8062-2762
      +49-69-8062-2012
      lehmann@f3.za-offenbach.dwd.d400.de

    • Dr. Daniel Michelson
      Swedish Meteorological and Hydrological Institute
      S-60176 Norrkoeping
      Sweden
      +46-11158494
      +46-11170207
      daniel.michelson@smhi.se

    • Dr. Dave Offiler
      U.K. Meteorological Office
      Meteorological Research Flight
      Building Y46, DRA Farnborough
      Hants. GU14 6TD
      U.K.

    • Johann Riedl
      Deutscher Wetterdienst
      Meteorologisches Observatorium
      Albin-Schwaiger-Weg 10
      D-82383 Hohenpeissenberg
      +49-880-5920039
      +49-880-5920046

    • Dr. Burkhardt Rockel
      GKSS Forschungszentrum
      Institut fuer Atmosphaerenphysik
      Postfach 1160
      D-21494 Geesthacht
      Germany
      +49-4152-87-2802
      +49-4152-87-2020
      rockel@gkss.de

    • Dr. Bruno Rudolf
      Deutscher Wetterdienst
      Global Precipitation Climatology Centre
      Postfach100 465 / Frankfurter Str. 135
      D-63004 Offenbach/Main
      Germany
      +49-69-8062-2981
      +49-69-8062-2993
      rudolf@k7-wzn.za-offenbach.dwd.d400.de

    • Prof. Dr. Eberhard Ruprecht
      nstitut fuer Meereskunde an der Universitaet Kiel
      Duesternbrooker Weg 20
      D-24105 Kiel
      Germany
      +49-431-5973872
      +49-431-565876
      eruprecht@ifm.uni-kiel.d400.de

    • Dr. Bent Hansen Sass
      Danish Meteorological Institute
      Research and Development Department
      Lyngbyvej 100
      DK-2100 Copenhagen
      Denmark
      +45-39157500
      +45-39157460
      bhs@dmi.min.dk

    • Priv. Doz. Dr. Clemens Simmer
      Institut fuer Meereskunde
      Universitaet Kiel
      Duesternbrooker Weg 20
      D-24105 Kiel
      Germany
      +49-431-597-3875
      +49-431-565-876
      csimmer@ifm.uni-kiel.d400.de

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    Summary
    Introduction
    Objectives
    Implementation
    Contributions


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    Last update of this page: 14 March 2007