The Baltic Sea Experiment BALTEX: a Brief Overview and Some Selected Results

GKSS

The Baltic Sea Experiment BALTEX: A brief overview and some selected results

PR 0 S 833 OSH

Autoren: E. Raschke U. Karstens R. Nolte-Holube R. Brandt H.-J. fsemer D. Lohmann M. Lobmeyr B. Rockel R. Stuhlmann

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The Baltic Sea Experiment BALTEX: A brief overview and some selected results

Autoren: E. Raschke U. Karstens R. Nolte-Holube R. Brandt H.-J. Isemer D. Lohmann M. Lobmeyr B. Rockel R, Stuhlmann (Institut fur Atmospharenphysik) Die extemen Berichte der GKSS warden kostenlos abgegeben. The delivery of the external GKSS reports is free of charge.

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The Baltic Sea Experiment BALTEX: A brief overview and some selected results

E. Raschke, U. Karstens, R. Nolte-Holube, R. Brandt, H.-J. Isemer, D. Lohmann, M. Lobmeyr, B. Rockel, R. Stuhlmann

28 pages with 8 figures and 2 tables

Abstract

The mechanisms responsible for the transfer of energy and water within the climate system are under worldwide investigation within the framework of the Global Energy and Water Cycle Experiment (GEWEX) to improve the predictability of natural and man-made climate changes at short and long ranges and their impact on water resources. Five continental-scale experiments have been established within GEWEX to enable a more complete coupling between atmospheric and hydrological models. One of them is the Baltic Sea Experiment (BALTEX). In this paper, the goals and structure of BALTEX are outlined. A short overview of measuring and modelling strategies is given. Atmospheric and hydrological model results of the authors are presented. This includes validation of precipitation using station measurements as well as validation of modelled cloud cover with cloud estimates from satellite data. Furthermore, results of a large-scale grid based hydrological model to be coupled to atmospheric models are presented. Z^....,'j ,

Das Regional-Experiment BALTEX: Ein kurzer Uberblick und einige ausgewahlte Ergebnisse

Zusammenfassung j Im Rahmen des Programmes GEWEX (Globales Energie- und Wasserkreislauf-Experiment) werden weltweite Untersuchungen derjenigen Mechanismen untemommen, die die Ubertragung von Energie und Wasser innerhalb des Klimasystems bestimmen. Dadurch soil die Vorhersagbarkeit von naturlichen und anthropogenen Klimaanderungen in kurzen und langeren Zeitraumen und deren Wirkung auf die ver- fugbaren Wasservorrate verbessert werden. Insgesamt funf kontinentweite Experimente wurden innerhalb von GEWEX fur diese Zwecke begonnen. In ihnen soil vordringlich eine Kopplung von Hydrologiemodellen an Atmospharenmodelle erfolgen. Bines dieser Experimente ist das BALTEX (Baltic Sea Experiment). In dieser Arbeit werden die Ziele und die Struktur von BALTEX vorgestellt. Es wird auch ein kurzer Uberblick iiber die Mefl- und Modellierstrategie vermittelt. Femer werden erste Ergebnisse der Autoren vorgestellt. Diese schliefien auch einen Vergleich zwischen gemessenen und modellierten Verteilungen des Niederschlages und der Bewdlkung im BALTEX-Gebiet. Weiterhin werden erste Ergebnisse des in einem gitterorientierten AbfluGmodell berechneten Abflusses vorgestellt. Dieses Model! soil spater an das Regionalmodell fur das BALTEX-Gebiet angekoppelt werden. \ \

Manuscript received /Manuskripteingang in der Redaktion: 11. April 1997 CONTENTS

1 INTRODUCTION 7

2 BALTEX GOALS AND STRUCTURE 8 2.1 Goals and structure 8 2.2 Structure and organization of BALTEX 12

3 OBSERVATIONS 13 3.1 In-situ measurements and data centers 13 3.2 Remote sensing data from satellites, radar and other profilers 15

4 MODELLING 16 4.1 Atmospherical modelling: Precipitation 17 4.2 Atmospheric Modelling: Cloud cover 19 4.3 Hydrological modelling 20

5 CONCLUSIONS 22

6 ACKNOWLEDGEMENT 23

7 REFERENCES 23

1 INTRODUCTION

The transport of water and energy within the climate system, which consists of the atmosphere, oceans, cryosphere and land surfaces, must be known very accurately in various spatial and tem poral domains to describe present and future climate states and the impact of their variations on related processes and on the water resources on the earth ’s surface.

Several studies investigated the mean monthly atmospheric water budget over the Baltic Sea using observations from aerological stations in combination with precipitation measurements. The budget calculations are based on the "aerological method" in which the divergence of the water transport and the change of water content are determined from direct atmospheric soundings, and the difference between evaporation and precipitation is computed as the residuum of the budget (for a review: see Holopainen, 1996). Palmen and Soderman (1966) computed the evaporation from the central part of the Baltic Sea for the time period October 1961 - September 1962 using the aerological method. Alestalo (1983) presented the seasonal variation of the water budget over Europe based on radiosonde data for July 1969 - June 1977 in comparison to long-term averages of precipitation and evaporation.

The most comprehensive study of the water budget of the Baltic Sea has been initiated by the Baltic Marine Environment Protection Commission - Helsinki Commission - (HELCOM, 1986). Here, long-term averages (1951-1970) of precipitation and evaporation as well as river inflow and sea volume changes are presented. In another study, results from numerical simulations over a period of 3 years with the Europa-Modell (EM) of the German Weather Service (DWD) have been analysed by Heise (1995). He calculated the components of energy and water cycles over the Baltic Sea catchment area from consecutive daily operational forecasts and obtained close agree ment with climatology.

Numerical modelling with high spatial and temporal resolution often provides the only means to estimate the available water resources in future scenarios of climate states and land uses. However, even the most advanced climate models show at present quite large differences between observa tions and modelled quantities (Gates, 1992; Lau et al., 1996). With controlled forcings at their lower boundary the decadal simulations of the AMIP (Atmospheric Model Intercomparison Project) show large differences in computed cloud and precipitation fields of up to 50 % from the average of all model results. But even in daily weather forecasts of the precipitation monthly aver ages can differ from measurements by the order of 50 %. Recently it has been demonstrated in more detail by Cubasch et al. (1995), that the precipitation values which were modelled for the present climate over Central Europe are more than 50 % smaller than observations, and over some areas the seasonal variations deviate by up to 6 months in phase.

Such systematic deficiencies, which were evident since the beginning of the World Climate Research Programme (WCRP) must considerably be reduced to justify the confidence into the results of such models and their projections into the far future. An accurate validation of model results had been established already in 1987 within the WCRP-programme GEWEX (Global Energy and Water Cycle Experiment; see e.g.: WCRP, 1990, Chahine 1992) with the major objectives - to determine the hydrological cycle and energy fluxes by means of global measurements of observable atmospheric and surface properties; - to model the global hydrological cycle and its impact on the atmosphere, the ocean, and on the land surface; 8

- to develop the ability to predict variations of global and regional hydrological processes and water resources, and their response to environmental change; - to foster the development of observational techniques, data management and assimilation systems suitable for operational application to long-range weather forecasts, hydrological and climate predictions.

The outcomings of GEWEX contribute to improvements of weather and climate analyses and forecasts. They are of benefit to the climate and climate impact research in general, but also to the research of various aspects within the International Geosphere and Biosphere Programme (IGBP) and the monitoring of pollutant transports within the atmosphere. Most of the involved opera tional agencies and organizations advice their national governments and economical sectors on climate issues.

In this paper an introduction is provided into the present objectives and structure of BALTEX and its major subprojects. Some first results of the authors are shown on the modelling of energy and water transports within the BALTEX region and their validation.

2 BALTEX GOALS AND STRUCTURE

Within GEWEX, which at present provides an umbrella for all climate related precipitation, atmos pheric water vapour, cloud and radiation projects and also for related numerical experimentations, five continental scale experiments (CSEs) have been established. Their geographical areas and major specific tasks are outlined in Table 2.1. Besides of several specific applications, these regional CSEs serve the major common goal to improve the modelling of hydrometeorological processes in numerical forecast schemes for weather and climate.

Table 2.1: Characteristics of the five GEWEX Continental-Scale Experiments (CSEs).

-W^CSE Area / Catchment Si/i (H) km2i/ ' /' Specific regional Runoff (km3/a) - V ' research issues _ „ i (not common to others)

flood forecasts, GCIP Mississippi 3.2 / 500 water management

permafrost hydrology, MAGS Mackenzie-River 1.8 / 300 forestry

oceanographic component: salt BALTEX Baltic Sea 2.1 / 470 water inflow

vegetation LBA Amazone River 6.2 / 6300 IGBP - reasearch

South-East Asia, Monsoon effects on GAME Tibet, >5/? water resources and Lena River water supply to the Arctics 9

One of these regional projects is the Baltic Sea Experiment (BALTEX), whose area, the drainage basin of the Baltic Sea, covers entirely or in smaller fractions the territories of fourteen countries (see Table 2.2). It has a size of about 2.1 Mill. km2. The Baltic Sea annually drains an amount of about 470 km3 of water into the North Sea. More than 80 Mill, inhabitants live in this area and use it intensively.

Table 2.2: Countries whose territory belongs entirely or in part to the drainage basin of the Baltic Sea. Data ^ from Brockhaus Enzyklopadie, 1991. Baltic Sea catchment boundary from Sweitzer et al, 1996.

Country Total area Areal fraction within Areal fraction of Annual precipitation (km2)11 Baltic Sea catchment Baltic Sea catchment (mm/a)a) (%) (%)

Denm irk 43.069 54.4 1.3 1250 Sweden 449.964 100 25.2 400-2000 Finland 338.145 100 18.9 400-700 Russia ■ ,| 17.075.4 2 19.1 700 Estonia*.' 45.100 100 2.5 554 ", - L a\ 11 64.400 100 3.6 550-800 Lithuania | 65.200 100 3.6 600-850 Belarus 207.600 42.8 5.0 600 ' Poland 1 312.683 100 17.5 600 ■ Gernianyzfl 471.100 2.7 0.7 600 1 ■ 'Ukraine' | 608.700 2.3 0.8 700 Slovakia 49.035 5.1 0.1 500 Ouxh Rep 78.864 10.3 0.5 400-700

N.hw iv 323.895 6.1 1.1 300-2000

The BALTEX region covers several climate zones from the more temperate midlatitudinal continental climate in Northern Germany and Poland to the subpolar permafrost climate (Defant, 1972). The Baltic Sea creates its own maritime climate. A sketch of this area and the areal extent of the Regional Model for BALTEX (REMO) are shown in Figure 2.1.

The major objectives of BALTEX are the development and validation of coupled regional models for the atmosphere with explicit consideration of hydrological processes at the lower boundary and also of the interaction with the sea surface. Research groups and operational meteorological, hydrological and oceanographic institutions from more than the 10 nations, whose territories drain water into the Baltic Sea, participate in BALTEX by collecting data, modelling transfer processes, performing experimental process studies or analysing satellite data with respect to their information contents on the radiation budget, clouds and precipitation. 10

10°W 0° 10°E 20°E 30°E 40°E 50°E 60°E

10°E 20°E 30°E

<0 0 0-100 100-200 200-500 500-1000 1000-15001500-3000 >3000 m

Fig. 2.1: Modelling area of the BALTEX REMO for the Baltic Sea water catchment.Orographic contours are shown with same resolution (18 km ) as for the model. This model area is imbedded within the Europa-Modell of the Deutscher Wetterdienst, as indicated in the upper right corner (see also Section 4). 11

The scientific objectives of BALTEX (see also IBS, 1995) are defined accordingly to explore and model the various mechanisms determining the space and time variability of energy and water budgets of the BALTEX region and their interaction with surrounding regions; - to relate these mechanisms to the larger-scale circulation systems in the atmosphere and oceans over the globe, and - to develop transferable methodologies in order to contribute to the basic needs for climate, climate impact and environmental research.

They stress the need for interdisciplinary cooperations between meteorology, hydrology and oceanography. Their fulfilment requires a strategy making simultaneous use of process-studies, routine as well as non-operational observations, and modelling in different spatial scales for the final purposes to obtain - improved weather, climate and climate impact models; - data sets and an advanced understanding for climate variations and their impact with particular consideration of the many mesoscale phenomena occurring in the higher latitudes of that area; - improved models for water management, which are coupled to the atmospheric models; - improved forecasts of various marine phenomena, such as inflow of saltwater, algae blooming, rapid ice developments (as during the winter 1995/96) and the exchange between the Baltic basins.

The research in BALTEX concentrates on coupled systems, consisting of the atmosphere, land surface (with explicit hydrology) and the Baltic Sea. The coupling mechanisms between these components are schematically outlined in Figure 2.2. As a basic hypothesis for modelling it is as sumed that all subgrid-scale phenomena can be parameterized in terms of the model predictables (e.g.: pressure, temperature, moisture and wind fields, etc) in each grid element. Thus the research strategy will require simultaneous work in both numerical modelling and observation in various spatial domains.

ATMOSPHERE

i i . i i , { w E,P H E,P H ' i—; l---- i______: f l f: SEA ICE R LAND 4—*- BALTIC SEA SURFACE

Fig. 2.2: Schematics of the coupling between the three components of BALTEX: atmosphere, continental surfaces and Baltic Sea (from IBS, 1995). E evaporation, P precipitation, F inflow and outflow through the Danish Straits, H heat and energy flux at the air-sea and air-land interaction interfaces, including radiation, L lateral heat exchange with the atmosphere outside the BALTEX region, R river runoff, W wind stress at the sea surface. 12

During the preparation for BALTEX the following projects have been identified to be carried out during the next years: a. ) Water and energy budgets over the BALTEX region from atmospheric models; b. ) Baltic Sea response to atmospheric and hydrological forcing; c. ) Development of a sea ice model for the Baltic Sea model; d. ) Thermohaline circulation and long-term variability of the Baltic Sea; e. ) Intercomparison of the various atmospheric models; f. ) Development and comparison of hydrological models for selected river basins; g. ) Complete hydrological model for the BALTEX region; h. ) Use of hydrological models and observations to validate the hydrological components of the meterological models; k.) Coupled atmosphere/ocean/land surface models.

BALTEX results will support many research tasks envisaged within the various subprogrammes of the IGBP. They will also improve the various attempts to quantify in space and time the transport of pollutants into this sensitive area, as to be determined within the RELCOM agreements (RELCOM, 1986). This integrated research will also be of benefit for work within the other four regional hydrometeorological experiments (CSEs) and for a new global programme on the climate variability (CLTVAR, 1995). Close cooperations has been established in particular with the IGBP-project BAHC (Biospheric Aspects of the Hydrological Cycle) with the possibility of joint field campaigns.

An important goal of BALTEX - and of the other CSEs - is the development of models in which submodels for the atmosphere, land surface with river basins and the oceans are coupled. To obtain the full benefit of such coupling, a two-way coupling between the different models will be necessary. While the above-mentioned atmospheric models already contain an explicit inclu sion of land surfaces, they do not describe the formation and transport of water in rivers. So far only a few attempts were made to couple the above-described hydrological models with an atmospheric model, where, however, the success depends strongly on the accuracy of the precipitation forecast (see e.g.: Lohmann, 1996, Lohmann et al., 1996).

The final definition of BALTEX goals and structure began already in 1991 during several inter national workshops and later by the BALTEX Science Steering Group (Figure 2.3). They are formulated in the Science Plan (Raschke, 1993) and in the Initial Implementation Plan (IBS, 1995). These publications were worldwide distributed within the scientific community and they are available from the International BALTEX-Secretariat at the GKSS Research Center in Geesthacht.

Recent details are reported in the internet ( http://w3.gkss.de/baltex/baltex_hdme.html).

2.2 Structure and organization of BALTEX

The BALTEX organizational structure (Figure 2.3) takes into account the need to organize and maintain this international project efficiently and in accordance with the general structure of GEWEX and other projects of the WCRP. 13

Accordingly, BALTEX is steadily reviewed by the BALTEX Science Steering Group with membership representing all 10 participating countries (Denmark, Sweden, Finland, Russia, Estonia, Latvia, Lithuania, Belarus, Poland and Germany) and the three scientific disciplines (hydrology, meteorology and oceanography) involved in this research. These countries contribute to the BALTEX research through their national resources, but also some external funding could be obtained from the European Union.

Figure 2.3: BALTEX organizational structure, as of July 1996 (from IBS, 1995).

At present there are three working groups on Process Studies, on Numerical Experimentation, and on the Radar Network with the common objectives to steadily review their respective fields and initiate and coordinate relevant research within BALTEX. A fourth working group has been established to prepare for the large experimental phase lasting over about 2 years in the time period April 1999 to March 2001. A special project has been defined to develop runoff models for all river basins, which later will be coupled to the atmospheric models.

An International BALTEX Secretariat has been established at the GKSS Research Center in Geesthacht, Germany, as a focal point for all scientific activities and their logistic requirements within BALTEX. Although primarily funded by German sources, international cooperations are sought to assure its international connections to all members of the BALTEX community and outside.

During the built-up phase of BALTEX, which may last until about the year 1999, several intensive data collection studies will be made. One of them, the PIDCAP (Pilot Study for Intensive Data Collection and Analysis of Precipitation; IBS, 1996a), concentrated primarily during the period from August 1995 to November 1995 on collection of all available precipitation measurements.

3 OBSERVATIONS

3.1 In-situ measurements and data centers

The basis for the BALTEX research and data collection is provided by operational in-situ measurements of meteorological, hydrological and oceanographic data. However, some of the data sets are distributed over many individual organizations of the BALTEX-countries, hence the 14 installation of operational data centers has been a prerequisite for BALTEX. This function to collect data or catalogue their availability has been taken over by the DWD in Offenbach for all meteorological data, by the Finnish Institute for Marine Research (FIMR) in Helsinki for all oceanographic data, and the Swedish Meteorological and Hydrological Institute (SMHI) in Norkopping for all hydrological data. Additional hydrological data are also available through the Global Runoff Data Center (GRDC) in Koblenz, Germany.

The BALTEX area is well covered with stations for meteorological observations, even on many of the islands in the Baltic Sea. However, the network of upper air soundings (about 40 stations) requires some improvements. Only very few operational radiation stations exist in this area. The network of precipitation stations is in some of the countries more than 15 times denser than seen in the official GTS data. The same ratio holds for river gauge data. Figure3.1 shows the spatial distribution of most radiation, synoptic and radar stations in the water catchment area of the Baltic Sea.

Legend: ■ synujilival sLilions + rmlialiuu Slaiiuus ® radar sliiliims

Baltic S«ii catchment air.i

■: .*■»

« . +

Figure 3.1: Synoptic, radiation and radar stations of the BALTEX area.

Hydrological data include observations of stream flow, lake storage, snow, ground water, soil moisture and in some cases also evapotranspiration. They are, however, obtained from different networks and often stored at different archives by meteorological and hydrological services or only regional authorities. In some areas extensive snow-core programmes arc carried out and long records of snow water exist. 15

A homogeneous hydrological data set is required at least for the enhanced observational and modelling periods. A data base for the total runoff into the Baltic sea, based upon monthly data from some 200 stations has been established at the Swedish Meteorological and Hydrological Institute (SMHI) in Norrkoping. It covers at present the time span from 1950 to 1990. The GKSS Research Center collects all available runoff and precipitation data together with meteorological information from all stations in Poland, Belarus, the 3 Baltic states, Germany and Russia. Also all precipitation data is obtained from Denmark, Finland and Sweden. The effect of hydropower on runoff is evident and has changed it for many rivers drasticallly with all consequences for the ecology in the neighborhood of the river mouth.

Of particular interest is the development of automatic optical and mechanical precipitation shipbome gauges (Basse et al., 1994), of which already 5 are installed on operational ferry boats crossing the Baltic Sea. Such measurements should be made from other ships of opportunity over all oceans to provide some index of the intensity and occurance in time and space for the ground-truth of precipitation values, which are now operationally been derived from satellite measurements. Recent developments make also use of sound and microwaves.

Oceanographic data from the Baltic Sea have been collected over a long time by ships and land stations. From these extensive measurements of the water temperature, salinity and chemical parameters a reasonable understanding of the thermohaline circulation could be derived. Real time delivery of oceanographic data and products consists of basic parameters, such as sea level, sea surface temperatures (also from satellite data) and ice conditions.

The network of direct observations of water characteristics within the Baltic Sea is quite sparse but important for calibration of satellite derived information. The Finnish Institute of Marine Research (FIMR) operates real-time collection of temperature and salinity on three ferries boats running regularity between Helsinki and Travemunde, Helsinki and St Petersburg and between Vaasa and Umea, respectively. There are also several national ice services.

A number of long historical records exists. Information on the ice coverage dates back to the year 1721, although some proxy-information can be derived from the descriptions of the many historical events in this interesting area (e.g.: Neumann, 1978, Neumann and Lindgren, 1979, Neumann and Kington, 1992).

Accurate measurements of the net water exchange between the Baltic and the North Sea are a prerequisite to close the water budget. Some of them are done steadily, others are available from engineering activities in this area.

3.2 Remote sensing data from satellites, radar and otho* profilers

There is now a large set of passive visible, infrared and microwave data from operational and experimental satellites available, which are received by many services and at the EUMETSAT center in Darmstadt. Further missions are planned by the space agencies in Europe, in the US, in China, Japan and Russia.

The field of view of the geostationary satellite Meteosat covers only the southern and middle portion of the BALTEX area, while the northernmost area is only seen with low resolution and slant paths. 16

This large data set expects further exploration for the purposes of BALTEX. It enters already the quasi-operational analyses within the ISCCP (Rossow et ah, 1996). Other preliminary analyses of such data are available on the cloud occurance, surface temperature, vegetation index and also the planetary radiation budget.

Rain-Radar is expected to provide additional information on the precipitation in particular over otherwise data sparse regions, despite of its well documented uncertainty (e.g, Joss and Waldvogel, 1990; Sauvageot, 1994). The Nordic countries began to establish an operational radar network (NORDRAD). During a first workshop in June 1996 basic recommendations were elaborated to combine the NORDRAD data with German and Polish radar (IBS, 1996b). Along the further eastern shorelines of the Baltic Sea no other rain radar is yet available. This data should be merged with simultaneous satellite measurements to extend this network over the data sparse regions by even only crude but still valuable estimates. Similarly merged data are now available over the British Isles and over France (Browning and Collier, 1989).

Wind profilers and other remote sounding instrumentation are operated at present only at very few research stations (e.g. at the observatory of the German Weather Service near Lindenberg), where they will extensively be used for process studies, as also the NOPEX field site near Uppsala.

4 MODELLING

The modelling efforts within BALTEX are directed towards the development and verification of models which describe all relevant components of the energy and water cycles in the BALTEX region. These models must allow to study the response of the system to natural and anthropogenic changes of the global climate. They also will form the basis for environmental models in the region.

Specifically the models must be capable of adressing the following scientific issues:

- Water and energy budget of the BALTEX region; - Interaction of mesoscale with synoptic scale processes; - Land-surface variability; - Snow in the hydrological cycle; - The role of sea ice in the Baltic Sea.

Different spatial scales will be considered within BALTEX studies to account for their impact on the transports investigated here.

The large scale area covers the entire drainage basin. One basic model for this scale, REMO (see Section 4.1), covers a much larger region to avoid boundary effects within the BALTEX region (Figures 2.1 and 4.2). Small scale areas, which are required for intensive process studies, extend over about 10 km and less. The latter ones are of the size of the NOPEX field sites (Northern Hemisphere Pilot Experiment; Halldin et al., 1995) near Upsalla, Sweden, or of the LITE ASS (Lindenberg Inhomogeneous Terrain - Fluxes between Atmosphere and Surface: a Long-term Study) of the German Weather Service near Lindenberg, Germany (Muller et al., 1995). Both sites are well equipped for process studies. 17

4.1 Atmospherical modelling: Precipitation

Atmospheric models must meet the fine spatial scales of precipitation patterns which occur even over very homogeneous terrain. They further must take into acccount the details of orography and surface properties, which in turn effect the exchanges of energy, water, and momentum. Orographic effects on the precipitation pattern and amount are of major concern in all five CSEs. Specific examples of modelling questions which need to be addressed are the parameterization of organized convection, organized boundary layer-driven circulation, and of the cloud^adiation- precipitation interactions.

For research within BALTEX a REgional scale MOdel REMO has been implemented in a joint effort of the DWD, the GKSS Research Center Geesthacht, the Max-Planck-Institute for Meteorology (MPI) in Hamburg, and the Deutsches Klimarechenzentrum (DKRZ) in Hamburg, to cover a region including the Baltic Sea catchment area. At GKSS results of consecutive short range weather forecasts (30 hours) are used to analyse a time span of the order of months. Initial and boundary conditions are derived from analyses, and the model is restarted with new initial conditions every day. Thus, the model is forced to stay close to the real weather situation (Karstens et al. 1996).

The regional model REMO is based on the regional weather forecast model "Europa-Modell" (EM, version 2.11) of the German Weather Service (Majewski, 1991, Jacob et al., 1995). The model uses the hydrostatic approximation with 20 vertical levels in a hybrid coordinate system. The horizontal resolution is approximately 18 km, while the "Europa-Modell" uses a horizontal resolution of about 54 km (see Figure 2.1). All components of the atmospheric water cycle (precipitation, evapotranspiration, horizontal transport, and change of water content in the atmosphere) are computed explicitely and time integrated during the model ran.

The components have been calculated for every day of June 1993 (for further details: Karstens et al. 1996). Daily mean values over the catchment area of the Baltic Sea are shown in Figure 4.1. It can be seen that the first 10 days of June 1993 were comparatively dry over the BALTEX region. Major precipitation events of about 4 kg m2d ‘ occur later on June 12, 17, 20 and 25. Daily mean evapotranspiration remains nearly constant near its mean value of 1.5 kg m V during the month. From day 3 to 8 the change in water content is mainly determined by horizontal transport. Precipitation and evapotranspiration approximately balance each other. In contrast to this, water storage and horizontal transport follow the strong precipitation in the period from day 17 to 20. Regarding the whole month of June 1993, the excess of precipitiation over evapotranspiration is balanced by a transport of water into the region and a decrease of water content.

The validation of the individual components of the water cycle is necessary to assure reliable estimates of the balance. It will also indicate possible deficiencies in the physical parameterizations and their feedbacks in the model. The main objective here is the validation of the precipitation field because this is a critical input parameter for hydrological models.

The precipitation, computed by the REMO, is compared with measurements from the operational rain gauge network of several meteorological services within the Baltic Sea region, as far as they were available to the authors (data collection of the International BALTEX Secretariat). Observa tions from 7775 stations were used. The measurements are converted to the model grid by taking the average of the values of all stations situated in a grid box. Figure 4.2 shows accumulated measured and calculated precipitation for June 1993 at those grid boxes where measurements 18

------Precipitation P ------Evaporation E ■ — Storage Change A W ...... Convergence C ------Residuum R

a> -2 ' / \

11 13 June 1993

Fig. 4.1: Atmospheric components of the water cycle over the catchment area of the Baltic Sea for June 1993 (Karstens et ah, 1996). The daily values refer to the time span from 06 UTC to 06 UTC on the following day, corresponding to hours 6 to 30 after model start at 00 UTC. All components are calculated explicitely, the residuum has only numerical character. Note: negative values mean a loss of the atmosphere.

Fig. 4.2: Measured a) and calculated b) precipitation in June 1993. Only grid boxes where measurements were available are coloured, all others are shown in grey. The Baltic Sea catchment area is marked by the pink line. 19

were available. Both fields show similarities in their structure, but in some regions the model underestimates the amount of precipitation by more than 50 %. The differences are mainly due to a mismatch in location of the precipitation regions, and only to a lesser extent to a general underestimation. These uncertainties are subject of further investigations.

Error estimates for both, measured and calculated precipitation values are not available so far. This will hopefully be one of the future results of BALTEX. We must also keep in mind that most rain gauges underestimate the precipitation amounts by up to 15 % (Sevruk, 1982, Joss and Waldvogel, 1990, Legates, 1995).

4.2 Atmospheric Modelling: Cloud cover

To validate the model, satellite data are particularly well suited because they can cover the whole model area. In the following, first results of a comparison between REMO model output and satellite observations of cloud cover are presented (Nolte-Holube et al., 1996).

The aim of the International Satellite Cloud Climatology Project (ISCCP) is a global cloud climatology with a time resolution of one month and 250 km horizontal resolution (Rossow et al., 1996). Data from both geostationary and polar orbiting satellites form the basis of several stages of processing. The intermediate ISCCP-product ISCCP-DX can be used for a comparison with REMO calculations. In the framework of WCRP (World Climate Research Programme) it was agreed to provide this product for use in the various GEWEX regional projects.

At GKSS the first months of ISCCP-DX data are available. Among the variables is a cloud flag which assumes the values 0 for clear sky or 1 for a cloudy pixel. Time resolution and horizontal resolution are 3 h and 30 km, respectively. For comparison, the data were transformed to the REMO grid, but no interpolation between the 30 km sampling was done. The results shown in this paper refer only to those grid points where measurements are available. Consequently the area mean values are not representative for the whole model area, but only for the strongly varying set of grid points covered at each date.

The ISCCP-parameter CLOUD can only assume the values 0 or 1 for clear or cloudy sky. In contrast, the regional model REMO includes cloud cover as a continuous variable. Thus the mean value of CLOUD over a given set of grid points can not be compared directly with the corresponding model output. As a simple approach to overcome this discrepancy, the continuous cloud cover variable is set to 1, if it is above a certain threshold value, and to zero if it is below. After this transformation the area mean is calculated.

Figure 4.3 shows area means of the cloud cover at all available grid points at all dates in June 1993. Model results come closer to the satellite data if the threshold transformation is applied. The mean value decreases with increasing threshold. In fact, all values between 0 and 1 can be obtained as mean value if the threshold is varied. Model and satellite data result in the same monthly mean for the threshold 0.3126. The corresponding time series and the difference between area means of model and satellite data are also shown in the figure. While the area means are relatively close to each other (deviations around 10 %), the spatial correlation (not shown) is only between 0.2 and 0.6. This reflects deviations in the location of clouds. More detailed investigations considering Meteosat and AVHRR data separately are underway. 20

CLOUD flag ISCCP DX BALTEX REMO, threshold 0.3126 Difference (REMO03126 - CLOUD) REMO, no threshold

-0.10

,q 20 —■—■—'—i—1—'—i—i—i i i i i i i i i i i i i i i i i i i i -0.20 0 5 10 15 20 25 30 Day in June 1993

Figure 4.3: Area mean values of cloud coverover all REMO grid points where measurements are available. Before calculating the mean value, the continuous cloud cover variable of the model is set to 1 if it is higher than the threshold value, and to 0 if it is smaller. Note that the strong diurnal variation is mainly caused by the sampling.

4.3 Hydrological modelling

There are at present hydrological models available considering two different scales:

Large-scale conceptual hydrological models have been designed for operational flood forecasting, some of them also for water resources and hydropower management. Examples are the models by Bergstrom and Forsman (1973), Nielsen and Hansen (1973) and others (see Maidment, 1993 and Schulz et al., 1995). They all include some empiricism about the processes involved with evapotranspiration, runoff and moisture storage. Typical timesteps range between one day and one month. What is common to most of them is that they are not resolving the diurnal cycle of evapotranspiration and that they are solving the water balance equation or the Penman-Monteith combination equation. 21

In the BALTEX region the model of the SHMI is currently used in large catchments ranging up to 100.000 km2. For each catchment the model has to be calibrated with measured streamflow data (Bergstrom and Carlsson, 1993, Bergstrom and Carlsson, 1994). It computes only the runoff amount at the river mouth.

Small-scale physically based models are also categorized as distributed differential models (Schulz et al., 1995). These models use time steps similar to those used in atmospheric models. Examples are the models by Abbott et al. (1986 a,b) or Wigmosta et al. (1994). These models are currently applied in catchments up to 5000 km2. It is assumed that this model type is at the limit of its physical basis with effective parameters using approximately 2x2 km2 grid squares (Schulz et al., 1995). Despite the physical basis of these models they also have to be calibrated with measured streamflow data. A complete scale and scaling theory in hydrology (Beven, 1995) is absent.

A survey of land surface parameterizations used in climate and weather forecast models can be found in Garratt (1993), Geyer and Jarvis (1991) or Schulz et al. (1995). Many of these models are now subject to a detailed investigation in the GEWEX project PILES (Project for Intercomparison of Land Surface Parameterization Schemes; Henderson-Sellers et al., 1995). They cover a broad range of complexity from the simple Bucket model (Manabe, 1969) to process-oriented SVATS (Soil Vegetation Atmosphere Transfer Schemes; Dickinson et al., 1986; Sellers et al., 1986). The main task of these models is to partition the incoming solar and longwave radiation in energy and water fluxes at the surface. Most of them are designed to resolve the daily cycle of the energy and water fluxes at the land surface - atmosphere interface, resulting in model structures with a high vertical resolution. These models are seldomly subject to a detailed calibration, they normally assume global parameters (Beljaars and Viterbo, 1995) or use roughly estimated land surface and vegetation parameters.

In general it can be stated that today ’s hydrological models focus on the water budget, while they ignore aspects of the energy budget (Schaake et al., 1996). On the other hand the water balance part in todays LSPs is treated in a rather simple way (Avissar and Verstraete, 1990). Many of these LSPs assume horizontal homogenity while keeping their local point process oriented model structure (Henderson-Sellers et al., 1995). It must be stated that most of these LSPs are used for space scales far beyond the applicability of their govering equations. As energy and water budget are linked via the latent heat flux or evapotranspiration, a poor treatment in the water balance automatically leads to errors in the energy balance part. Scale issues must be considered (e.g.: Beven, 1995).

The horizontal grid of atmospheric models used for climate and weather prediction is today in a range of 10 km to 600 km, so LSPs can learn from the conceptual hydrological water balance models how to improve their water balance part. Recent developments to include large scale concepts into LSPs are made by Wood et al. (1992), Liang et al. (1994), Dumenil and Todini (1992) and references therein. Schaake et al. (1996) and Lohmann (1996) followed this earlier work consequently looking for the necessary complexity needed in the water balance part of LSPs (see also Lohmann et al., 1996). Figure 4.4 shows daily averages of measured and modeled streamflow data of the Weser river in Germany. The calculations were done on the 18x18 km2 grid of the REMO. This model will now be applied to the Odra and Daugava basins. 22

2400

2000 - measured • calculated ■ difference

1200

1982 1983 1984 1985 1986 1987 time Fig. 4.4: Measured and calculated daily streamflow of the Weser river (Germany) at gauge station Intschede. (see Lohmann, 1996.) The area of the Weser catchment upstream of this gauge station is 37500 km2. The model calculation was done on the the 18x18 km2 grid of the atmospheric model REMO.

5 CONCLUSIONS

As climate research results gain increasing importance for providing solutions for many of the world's economy problems, as more accurately energy and water cycles must be known and modelled numerically in the global but even more the regional domains. Continental scale experiments, such as the BALTEX and others which cover the discharge areas of major river basins are possibly the right means to solve these problems. Their results will enter the global models; newly developed methods will be available for use over other possibly data sparse regions, like the important basins of Siberian streams or the Zaire-River in the tropical Africa.

The preliminary results and experiences obtained so far can be summarized in the following way:

- Great care is required to collect and quality proof ground-based measurements from many different countries. Indeed in this case also several radiation stations and in particular 1 or 2 rain radar should be added. - There are careful intercomparisons required of all components of models used in such an experiment. Since precipitation errors of ±50 % are found on a monthly basis, all possible reasons have to be investigated, ranging from the treatment of soil moisture to that of atmospheric dynamics. 23

- There are process-oriented experimental and numerical studies required over vegetated terrain to improve our understanding of energy, momentum and water exchanges at ground, and also of the temporary water storage in the uppermost soil layers. They are planned for the areas near Lindenberg and Uppsala; another will be made over the Baltic Sea. - The full potential of information contained in remote sensing data has not yet been fully explored for the purpose of such Continental Scale Experiments, as it could be shown with the comparison of model cloud data with the ISCCP cloud products. - Since basins of all major rivers have different properties and undergo also different atmospheric forcings, a hydrological modelling scheme must carefully be calibrated with measured data. The presented scheme is not yet able to respond to major changes in the land use.

6 ACKNOWLEDGEMENT

The authors appreciate the always encouraging cooperation of many scientists and of related administrators from all "ten BALTEX countries", who helped with great enthusiasm to develop BALTEX. Additional financial support has been received from the GKSS Research Center, from the German climate research programme (Grant 07 VWK 01/06., and also from the 4. Programme on Environment and Climate of the European Union. D.L. is now with the Princeton University; his model development has been also supported by Prof. D. Lettenmaier, Seattle.

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Wigmosta, M.W., L.W. Vail and DP. Lettenmaier, 1994: A distributed hydrology-vegetation model for complex terrain. Water Resour. Res., 30, 1665-1679.

Wood, E.F., DP. Lettenmaier and V.G. Zartarian, 1992: A land-surface hydrology parameterization with subgrid variability for general circulation models. J. Geophys. Res., 91. 2717-2728. Fur die Zukunftssicherung des Wirtschaftsstandortes Research and development is of fundamental sig Deutschland ist Forschung und Entwicklung von grund- nificance to the future of Germany's advanced, legender Bedeutung. Neben anderen Forschungs- industrialized economy and is in the responsibility of organisationen leisten sechzehn nationale Einrichtungen 16 German National Research Centres, organized in der Hermann von Helmholz-Gemeinschaft Deutscher the Hermann von Helmholz-Gemeinschaft Deutscher Forschungszentren (HGF) hierfur einen wichtigen Forschungszentren (including GKSS with its 800 Beitrag. Zu ihnen zahlt mit ca. 800 Mitarbeitern und employees and an annual budget of 120 million DM) einem Budget von 120 Mio. DM das GKSS-Forschungs- and numerous other research organisations. The zentrum. Aufgabe dieser Zentren, die vom Bundes- National Research Centres, which are funded jointly by ministerium fur Bildung, Wissenschaft, Forschung the Federal Ministry for Education, Science, Research und Technologic (90%) und den Landern (10%) and Technology (90%) and the Federal States (10%), getragen werden, ist es, fur unsere Volkswirtschaft have the task of opening up and shaping new stra strategische Zukunftsfelder zu eroffnen und zu gestalten. tegic technological fields of benefit to the economy. In wissenschaftlicher Autonomic werden von ihnen langfristige Forschungsziele des Staates verfolgt. The GKSS research and development mission is to establish the basis for tomorrow's key technologies. Durch Forschung und Entwicklung Grundlagen fur This involves the fusion of research, development Technologien von morgen zu schaffen, ist Ziel der GKSS. and industrial utilization. The GKSS research program Dabei bilden Forschung, Entwicklung und Anwendung is therefore characterized by close ties between science eine Einheit. Die Vernetzung mit Wissenschaft, Industrie and industry, in particular in the northern German und offentlichen Anwendem sowie eine Internationale region, and international cooperation within the Zusammenarbeit in den Forschungsschwerpunkten und framework of the main research activities and project den Projektfeldern, verbunden mit einer industriellen areas, thus ensuring industrial applications and Umsetzung und Nutzung der Ergebnisse, markieren utilization. das GKSS-Forschungsprogramm auf den Gebieten: The main research activities are: - Materialforschung, - material research, - Trenn- und Umwelttechnik, - separation- and environmental technology, - Umweltforschung. - environmental research.

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