Baltic Sea Experiment Research Articles

The BALTEX/Baltic Earth program: Excursions and returns

The Baltic Sea Experiment (BALTEX) started in 1993 as part of the Global Energy and Water Cycle Experiment (GEWEX). It was later organized into three programs: BALTEX I, BALTEX II, and Baltic Earth. Here, we examine in a brief overview the overall BALTEX achievements, including program goals, risks encountered during the research journey, and knowledge development when finalizing the programs.During three decades of climate and environmental studies of the Baltic Basin within the BALTEX/Baltic Earth programs, significant steps have been taken towards improved scientifically constructed knowledge and efforts to disseminate this knowledge to neighboring sciences and the public. These programs have illustrated the need to actively navigate the European research arena while remaining an independent science network. The well-organized International Baltic Earth Secretariat and many dedicated scientists made the research excursions safe and successful. The learning process relates to improved knowledge of the dynamics of the atmosphere–ocean–land climate system in the Baltic Sea region, the cycling of carbon and other substances, the region's anthropogenic climate and environmental changes, and how global warming and regional human activities can be detected outside natural variability.

Baltic Sea Operational Oceanography—A Stimulant for Regional Earth System Research

Two important communities related to oceanography in the Baltic Sea are those working on operational oceanography and Earth system science, with focusing on the same water body but different temporal scales. They have been coordinated through two organizations/programs: the Baltic Sea Operational Oceanographic System (BOOS) and the Baltic Sea Experiment (BALTEX) and its successor, the Baltic Earth Program (Earth system science for the Baltic Sea region), respectively. Although the two communities have archived significant progresses in their own fields since early 1990s, there were few interactions between the communities. Rapid advancements of operational oceanography on ocean monitoring, data sharing, modelling and historical ocean state reconstruction in the last decade have provided a wide range of data, products and modelling tools which may be used in Earth system and climate change research. This is especially true when operational oceanography in the Baltic Sea is in a transition to a seamless service, i.e., from basin to local scales, from synoptic to climate scales and from physical to biogeochemical and biological systems. On the other hand, the Baltic Sea Earth system research can help to improve operational oceanography by contributing research observations and transferring their research achievements to the operational system. Based on a review of state-of-the-art of BOOS monitoring and modelling capabilities and on-going BOOS research, this paper will highlight topics and areas which are related to the Baltic Earth Grand Challenges, i.e., salinity dynamics, land-sea biogeochemical linkages, natural hazards and extreme events, sea level dynamics, coastal morphology and erosion, regional variability of water and energy exchanges, and multi-drivers of regional Earth system changes. Potential win-win cooperation and interaction between the BOOS and the Baltic Earth communities are also proposed and discussed.

Robust adaptive filter for shipborne kinematic positioning and velocity determination during the Baltic Sea experiment

Information on trajectory and attitude is essential for analyzing gravimetric data collected on kinematic platforms. Usually, a Kalman filter is used to obtain high-accuracy positional and velocity information. However, this can be affected by measurement outliers and by state disturbances that occur frequently under a fast-changing environment. To overcome these problems, a robust adaptive Kalman filtering algorithm is applied for state estimates, which introduces an equivalent weight to resist measurement outliers and an optimal adaptive factor to balance the contributions of the kinematic model information and the measurements. In addition to the conventional robust estimator, an improved Current Statistical (CS) model is proposed. The improved CS model adopts a variance adaptive learning algorithm, and it can perform self-adaptation of acceleration variance with the innovation information; thus, it can overcome the shortcoming of lower tracking accuracy and avoid setting the maximum acceleration. Following a gravimetry campaign on the Baltic Sea, it is shown in theory and in practice that the robust adaptive Kalman filter is not only simple in its calculation but also more reliable in controlling the colored observation noise and kinematic state disturbance compared with the classical Kalman filter. The improved CS model performs best, especially when analyzing the positioning errors at the turns due to the target maneuvering. Compared to the CS model, the RMS values of the positional estimates derived from the improved CS model decrease by almost 30% in the horizontal direction, and no significant improvement in the vertical direction is found.

Dynamics of halocarbons in coastal surface waters during short term mesocosm experiments

Environmental context Halocarbons are trace gases important in atmospheric ozone chemistry whose biogenic production – among other factors – depends on light-induced stress of marine algae. Several studies have confirmed this effect in laboratory experiments but knowledge in natural systems remains sparse. In mesocosm experiments, which are a link between field and laboratory studies, we observed that the influence of natural levels of ultraviolet radiation on halocarbon dynamics in the marine surface waters was either insignificant or concealed by the complex interactions in the natural systems. Abstract The aim of the present study was to evaluate the influence of different light quality, especially ultraviolet radiation (UVR), on the dynamics of volatile halogenated organic compounds (VHOCs) at the sea surface. Short term experiments were conducted with floating gas-tight mesocosms of different optical qualities. Six halocarbons (CH3I, CHCl3, CH2Br2, CH2ClI, CHBr3 and CH2I2), known to be produced by phytoplankton, together with a variety of biological and environmental variables were measured in the coastal southern Baltic Sea and in the Raunefjord (North Sea). These experiments showed that ambient levels of UVR have no significant influence on VHOC dynamics in the natural systems. We attribute it to the low radiation doses that phytoplankton cells receive in a normal turbulent surface mixed layer. The VHOC concentrations were influenced by their production and removal processes, but they were not correlated with biological or environmental parameters investigated. Diatoms were most likely the dominant biogenic source of VHOCs in the Baltic Sea experiment, whereas in the Raunefjord experiment macroalgae probably contributed strongly to the production of VHOCs. The variable stable carbon isotope signatures (δ13C values) of bromoform (CHBr3) also indicate that different autotrophic organisms were responsible for CHBr3 production in the two coastal environments. In the Raunefjord, despite strong daily variations in CHBr3 concentration, the carbon isotopic ratio was fairly stable with a mean value of –26‰. During the declining spring phytoplankton bloom in the Baltic Sea, the δ13C values of CHBr3 were enriched in 13C and showed noticeable diurnal changes (–12‰ ±4). These results show that isotope signature analysis is a useful tool to study both the origin and dynamics of VHOCs in natural systems.

Aerosol indirect effects on continental low-level clouds over Sweden and Finland

Abstract. Aerosol effects on low-level clouds over the Nordic Countries are investigated by combining in situ ground-based aerosol measurements with remote sensing data of clouds and precipitation. Ten years of number size distribution data from two aerosol measurement stations (Vavihill, Sweden and Hyytiälä, Finland) provide aerosol number concentrations in the atmospheric boundary layer. This is combined with cloud satellite data from the Moderate Resolution Imaging Spectroradiometer and weather radar data from the Baltic Sea Experiment. Also, how the meteorological conditions affect the clouds is investigated using reanalysis data from the European Centre for Medium-Range Weather Forecasts. The cloud droplet effective radius is found to decrease when the aerosol number concentration increases, while the cloud optical thickness does not vary with boundary layer aerosol number concentrations. Furthermore, the aerosol–cloud interaction parameter (ACI), a measure of how the effective radius is influenced by the number concentration of cloud active particles, is found to be somewhere between 0.10 and 0.18 and the magnitude of the ACI is greatest when the number concentration of particles with a diameter larger than 130 nm is used. Lower precipitation intensity in the weather radar images is associated with higher aerosol number concentrations. In addition, at Hyytiälä the particle number concentrations is generally higher for non-precipitating cases than for precipitating cases. The apparent absence of the first indirect effect of aerosols on low-level clouds over land raises questions regarding the magnitude of the indirect aerosol radiative forcing.

BALTIMOS—a coupled modelling system for the Baltic Sea and its drainage basin

The major tasks of the Baltic Sea Experiment (BALTEX) are to simulate the water and energy cycles of the Baltic Sea catchment and to identify important processes, which are relevant to the climate in the Baltic region. A fully coupled regional climate model system for the Baltic Sea region, called BALTIMOS, was developed in the framework of the German climate research program DEKLIM by linking existing model components for the atmosphere, for the ocean including sea ice, and for hydrology. With this system, it is possible to model the complete water and energy cycles for the Baltic Sea catchment for today’s climate, as well as for the future with climate scenarios. The emphasis in this paper is given to the description of the modelling system and on the comparison of the results of the fully coupled BALTIMOS system against the results of the uncoupled atmospheric component REMO for today’s climate. Both simulations are driven at the atmospheric lateral boundaries with ECMWF analysis data from the European Centre for Medium Range Weather Forecast (ECMWF) for 5 years each. In the uncoupled run, the sea surface temperature (SST) and ice surface temperature (IST) analysed by ECMWF are prescribed, while in the coupled run, SST and IST are provided by the ocean/sea ice model BSIOM. Several analysed parameters are very similar for the land part of the Baltic Sea catchment, while there are differences especially for surface and near-surface temperatures for the fraction of the Baltic Sea itself that indicate further research efforts. As no corrections for the modelled air-sea fluxes are applied for the coupled model system, it is a good result that no drift of the coupled model system is visible in the 5-year integration. The present paper gives an overview about the development of the coupled model system and shows results from first integrations of the system.

A long-term satellite study of aerosol effects on convective clouds in Nordic background air

Abstract. Aerosol-cloud interactions constitute a major uncertainty in future climate predictions. This study combines 10 years of ground-based aerosol particle measurements from two Nordic background stations (Vavihill and Hyytiälä) with MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data of convective clouds. The merged data are used to examine how aerosols affect cloud droplet sizes and precipitation from convective clouds over the Nordic countries. From the satellite scenes, vertical profiles of cloud droplet effective radius (re) are created by plotting retrieved cloud top re against cloud top temperature for the clouds in a given satellite scene. The profiles have been divided according to aerosol number concentrations but also meteorological reanalysis parameters from the ECMWF (European Centre for Medium-Range Forecasts). Furthermore, weather radar data from the BALTEX (Baltic Sea Experiment) and precipitation data from several ground-based meteorological measurement stations have been investigated to determine whether aerosols affect precipitation intensity and amount. Small re throughout the entire cloud profiles is associated with high aerosol number concentrations at both stations. However, aerosol number concentrations seem to affect neither the cloud optical thickness nor the vertical extent of the clouds in this study. Cloud profiles with no or little precipitation have smaller droplets than those with more precipitation. Moreover, the amount of precipitation that reaches the ground is affected by meteorological conditions such as the vertical extent of the clouds, the atmospheric instability and the relative humidity in the lower atmosphere rather than the aerosol number concentration. However, lower precipitation rates are associated with higher aerosol number concentrations for clouds with similar vertical extent. The combination of these ground-based and remote-sensing datasets provides a unique long-term study of the effects of aerosols on convective clouds over the Nordic countries.

Climate Change Assessment for the Baltic Sea Basin

The Fourth Assessment Report of the Intergovernmental Panel on Climate Change [IPCC, 2007] has had a big impact on the public perception and acknowledgment of global climate change. However, regional climate change assessments are urgently needed to complement the big picture with regional results and scenarios of higher resolution, which local decision makers and stakeholders can use [Visbeck, 2008; von Storch and Meinke, 2008].An outstanding example of a regional assessment is the BALTEX (Baltic Sea Experiment) Assessment of Climate Change for the Baltic Sea Basin (BACC; http://www.baltex‐research.eu/BACC/), which was compiled by a consortium of 84 scientists from 13 countries around the Baltic Sea [BACC Author Team, 2008]. The assessment covers various disciplines related to climate research and related impacts.

An Integrated Approach toward Retrieving Physically Consistent Profiles of Temperature, Humidity, and Cloud Liquid Water

A method is presented for deriving physically consistent profiles of temperature, humidity, and cloud liquid water content. This approach combines a ground-based multichannel microwave radiometer, a cloud radar, a lidar-ceilometer, the nearest operational radiosonde measurement, and ground-level measurements of standard meteorological properties with statistics derived from results of a microphysical cloud model. All measurements are integrated within the framework of optimal estimation to guarantee a retrieved profile with maximum information content. The developed integrated profiling technique (IPT) is applied to synthetic cloud model output as a test of accuracy. It is shown that the liquid water content profiles obtained with the IPT are significantly more accurate than common methods that use the microwave-derived liquid water path to scale the radar reflectivity profile. The IPT is also applied to 2 months of the European Cloud Liquid Water Network (CLIWA-NET) Baltic Sea Experiment (BALTEX) BRIDGE main experiment (BBC) campaign data, considering liquid-phase, nonprecipitating clouds only. Error analysis indicates root-mean-square uncertainties of less than 1 K in temperature and less than 1 g m−3 in humidity, where the relative error in liquid water content ranges from 15% to 25%. A comparison of the vertically integrated humidity profile from the IPT with the nearest operational radiosonde shows an acceptable bias error of 0.13 kg m−2 when the Rosenkranz gas absorption model is used. However, if the Liebe gas absorption model is used, this systematic error increases to −1.24 kg m−2, showing that the IPT humidity retrieval is significantly dependent on the chosen gas absorption model.

Correlation of precipitation estimates from spaceborne passive microwave sensors and weather radar imagery for BALTEX PIDCAP

This paper describes the evaluation of a combined radar and passive microwave dataset obtained during the PIDCAP study of the Baltic Sea Experiment (BALTEX), where three-dimensional volumes of data from the Gotland radar were obtained timed according to the overpasses of the DMSP-satellites F10 and F13. Both satellites are equipped with a Special Sensor Microwave/Imager (SSM/I), suitable for precipitation retrievals. We compare radar precipitation estimates, convolved to the native resolution of the SSM/I, at different altitudes with polarization and scattering indices ( S 85 ) derived from the SSM/I. For all 22 overpasses investigated here radar precipitation estimates at 3-4 km altitude correlate well with the SSM/I-derived S 85 (average correlation coefficient = 0.70). Although more directly linked to surface precipitation, polarization indices have been found to be less correlated with radar data, due to limitations inherent in the remote sensing of precipitation at higher latitudes. A stratification of the dataset into frontal and convective events revealed significant variations in these relationships for different types of precipitation events, thus reflecting different cloud microphysical processes associated with precipitation initialization. The relationship between S 85 and radar rain estimates at higher altitudes varies considerably for different convective and frontal events. The sensitivity of S 85 to radar-derived rain rate ranges from 3.1 K mm m 1 h m 1 for a strong convective event to about 25 K mm m 1 h m 1 for the frontal and about 70 mm m 1 h m 1 for the small-scale convective events. For extrapolated surface precipitation estimates, sensitivities decrease to 14 mm m 1 h m 1 and 25 mm m 1 h m 1 for frontal and small-scale convective precipitation, respectively.

The Baltic Sea Experiment (BALTEX): A European Contribution to the Investigation of the Energy and Water Cycle over a Large Drainage Basin

The Baltic Sea Experiment (BALTEX) is one of the five continental-scale experiments of the Global Energy and Water Cycle Experiment (GEWEX). More than 50 research groups from 14 European countries are participating in this project to measure and model the energy and water cycle over the large drainage basin of the Baltic Sea in northern Europe. BALTEX aims to provide a better understanding of the processes of the climate system and to improve and to validate the water cycle in regional numerical models for weather forecasting and climate studies. A major effort is undertaken to couple interactively the atmosphere with the vegetated continental surfaces and the Baltic Sea including its sea ice. The intensive observational and modeling phase BRIDGE, which is a contribution to the Coordinated Enhanced Observing Period of GEWEX, will provide enhanced datasets for the period October 1999-February 2002 to validate numerical models and satellite products. Major achievements have been obtained in an improved understanding of related exchange processes. For the first time an interactive atmosphere-ocean-land surface model for the Baltic Sea was tested. This paper reports on major activities and some results.

Editorial: Scientific results of the European NEWBALTIC project

(1 Numerical Studies of the Energy and Water Cycle of the BALTIC Region) stands for two international projects funded by the European Community in the years 1996–2000. The campaign was embedded into the continental-scale experiment BALTEX2(2 Baltic Sea Experiment), a subproject of GEWEX3(3 Global Energy and Water Cycle Experiment) (Raschke, 1994; Bengtsson, 1995). The present special issue emerged from two NEWBALTIC progress meetings held in Sweden: One in June 1999 in Abisko and one in January 2000 at Chalmers University of Technology in Gothenburg. The NEWBALTIC community welcomed the suggestion of Professor Bengtsson, Chairman of the BALTEX Science Steering Group, to present selected contributions of the considerable body of NEWBALTIC results in a special MAP4(4 Meterology and Atmospheric Physics) issue. This collection, it was agreed, might serve as an example for the current state of modelling hydro-meteorological key processes on the continental scale of the Baltic Sea and its environment (see also Raschke et al., 1998, 2001). All papers submitted went through the review process regularly applied by MAP.

Water balance modelling in the Baltic Sea drainage basin - analysis of meteorological and hydrological approaches

Efforts to understand and simulate the global climate in numerical models have led to regional studies of the energy and water balance. The Baltic Basin provides a continental scale test basin where meteorology, oceanography and hydrology all can meet. Using a simple conceptual approach, a large-scale hydrological model of the water balance of the total Baltic Sea Drainage Basin (HBV-Baltic) was used to simulate the basinwide water balance components for the present climate and to evaluate the land surface components of atmospheric climate models. It has been used extensively in co-operative BALTEX (The Baltic Sea Experiment) research and within SWECLIM (Swedish Regional Climate Modelling Programme) to support continued regional climate model development. This helps to identify inconsistencies in both meteorological and hydrological models. One result is that compensating errors are evident in the snow routines of the atmospheric models studied. The use of HBV-Baltic has greatly improved the dialogue between hydrological and meteorological modellers within the Baltic Basin research community. It is concluded that conceptual hydrological models, although far from being complete, play an important role in the realm of continental scale hydrological modelling. Atmospheric models benefit from the experience of hydrological modellers in developing simpler, yet more effective land surface parameterisations. This basic modelling tool for simulating the large-scale water balance of the Baltic Sea drainage basin is the only existing hydrological model that covers the entire basin and will continue to be used until more detailed models can be successfully applied at this scale.

Validation of Integrated Water Vapor from Numerical Models Using Ground-Based GPS, SSM/I, and Water Vapor Radiometer Measurements

Abstract Time series of vertically integrated water vapor (IWV) derived for 25 ground-based global positioning system (GPS) sites in Sweden and Finland are used for validating the IWV from weather forecast models for a 3-month period from August through October of 1995. Results from analyses and forecasts of the Baltic Sea Experiment (BALTEX) Model and Europa Model [operational until December of 1999 at the German Weather Service (DWD)] at horizontal resolutions of 1/6° and 1/2° are evaluated. IWV retrievals from the Special Sensor Microwave Imager (SSM/I) for the Baltic Sea area and, for a second 6-month period in 1997, from a ground-based water vapor radiometer (WVR) at Potsdam are used additionally. The models reproduce the observed temporal and spatial variability of the IWV fields accurately, but a systematic humid bias of 2.5–3 kg m−2 is diagnosed versus GPS. However, radiosondes in the same area indicate a smaller bias of about 1.5–2 kg m−2 and hint at a slight dry bias in the GPS data. The standar...

REMO Cloud Modeling: Improvements and Validation with ISCCP DX Data

Abstract The grid-scale cloud properties of the Regional-Scale Model (REMO) are compared with the cloud retrievals derived from the International Satellite Cloud Climatology Project (ISCCP) “DX” datasets for the Baltic Sea Experiment region in March of 1994. For the uppermost cloud layer, the layer seen by a satellite instrument, the original REMO cloud scheme gives an ice cloud cover amount of about 90%, and the water cloud cover is close to zero. As compared with ISCCP, this result is an overestimation of ice clouds by up to 60% and underestimation of water clouds by up to 40%. To improve the REMO cloud results, a sensitivity study is carried out that shows that ice heterogeneous nucleation is the most influential process in the REMO cloud scheme. Cloud properties derived from the new REMO cloud scheme show that the amount of grid-scale ice clouds has decreased by about 40% and that of grid-scale water clouds has increased by about 20% in comparison with the old version. When compared with the ISCCP clo...

BALTEX precipitation analysis: results from the BRIDGE preparation phase

The Baltic Sea Experiment (BALTEX) is the European contribution to the Global Energy and Water Cycle Experiment (GEWEX). During the preparation phase of the BALTEX main experiment BRIDGE a Precipitation Correction and Analysis (PCA) model has been designed and was tested using 3 years (August 1995 – December 1998) of about 4 000 rain gauge observations collected by the BALTEX Meteorological Data Centre (BMDC). The PCA model consists of two parts: (1) a bias correction and (2) a geostatistical module. The dynamic bias correction reduces the systematic underestimation of the rain gauges due to wind-induced, evaporation and wetting losses taking instrument-specific properties as well as additional information from synoptic observations into account. The mean correction factor has a maximum in February (1.25 – 1.50) and a minimum in August (1.02 – 1.05). The geostatistical module of the PCA model consists of an ordinary block kriging algorithm to estimate area averaged precipitation values on the grid of the meso-scale model REMO (spatial resolution: 16 degree or 18 km). Results, to be operationally produced during BRIDGE, will be daily, monthly and annual meso-scale precipitation fields based on quality checked, bias corrected rain gauge measurements.

The importance of water storage variations for water balance studies of the Baltic Sea

The closing of the water and energy cycle of the Baltic Sea is one of the main aims of BALTEX (Baltic Sea Experiment), which particularily focuses on the exploration, modelling and quantification of the various processes determining the space and time variability of the energy and water budget. On the long-term mean the water budget of the Baltic Sea is determined by river runoff, net precipitation (precipitation minus evaporation) and the in- and outflows through the Baltic Sea entrance area, assuming that the mean sea level remains constant, i.e. the ability of the Baltic Sea to store a huge amount of water is averaged out over the long-term period. For shorter periods, the water storage which can be expressed by the mean sea level plays an important role on the water budget. The objective of the present study is to investigate the variability of the water storage of the Baltic Sea and relate its fluctuations to the different components of the water balance equation. The anomaly of the mean sea level of the Baltic Sea shows a well pronounced seasonal cycle, with negative values between the end of February to the end of June (minimum in the middle of May), and positive anomalies from July to mid-February (maximum in January). There is a high correlation between the mean sea level expressed by the Landsort tide gauge and the local atmospheric conditions over the Baltic Sea. The annual course of the total water balance is controlled by the local atmospheric conditions with the net fresh-water inflow only controls the general outflow conditions. Sea level, precipitation and river runoff have been obtained from observations provided by the SMHI. For the in- and outflow through the entrance area of the Baltic Sea and evaporation over the open ocean, coupled sea ice-ocean model simulations for a 10-years period have been utilized.

Validation of the NWP model HRM with groundbased GPS data

The atmospheric water vapor is a very important variable for the hydrological cycle and for short term numerical weather prediction. Groundbased GPS data are applied to validate the vertically integrated water vapor (IWV) as derived with the HRM model (High resolution Regional Model) of the German Weather Service (DWD) within the BALTEX (Baltic Sea Experiment) region. Data of the PIDCAP period (Pilot Study for Intensive Data Collection and Analysis of Precipitation; August 1 to November 17, 1995) from Sweden and Finland and of the first month (May 2000) of GPS measurements processed by the Geo Forschungs Zentrum (GFZ, Potsdam, Germany) within the BRIDGE baseline period (October 1999 to December 2002) are used. The IWV of the HRM model with ECMWF analysis data as initial fields show significantly lower mean differences to the GPS IWV data than the HRM IWV with the EM3AN analysis data of the Europa-Model of the DWD. The IWV differences of the HRM model and the GPS data can mainly be explained by the differences between the analysis data and the GPS data. The IWVs derived from HRM model are highly correlated with the GPS data (i.e. with a correlation coefficient of 0.937 for the PIDCAP period and a correlation coefficient of 0.881 for May 2000).

Validation of a regional weather forecast model with GPS data

The atmospheric water vapor content is one of the most important parameters for the hydrological cycle. In order to investigate the energy and water balance over the Baltic Sea and its catchment, the hydrostatic regional weather forecast model HRM (High resolution Regional Model) of the German Weather Service (DWD) is validated against groundbased GPS data within the BALTEX (Baltic Sea Experiment) region and the PIDCAP period (Pilot Study for Intensive Data Collection and Analysis of Precipitation; August 1 to November 17, 1995). The vertically integrated water vapor content (IWV) derived from HRM shows a high correlation (coefficient = 0.935) and slightly (≈ 2.69 kg/m2) greater mean values than the GPS data mainly due to greater mean analyses data.Between 1995 and 1998 GPS/MET aboard the Micro-Lab 1 successfully demonstrated the radio occultation technique to probe the Earth's atmosphere through its refraction effects on the signals transmitted by the GPS satellites. Profiles of the water vapor can be obtained from the GPS derived refractivity by using the temperature profiles of the HRM model. For a comparison of the vertical distribution of the specific humidity these water vapor profiles are used. Also lower values than with HRM were found. A comparison of the vertically IWV as derived from GPS/MET and from HRM shows a high correlation (coefficient = 0.90).

MESAN Mesoscale analysis of precipitation

The Mesoscale Analysis System (MESAN) has been running operationally since April, 1997, providing science and consumers of weather information with spatially continuous fields of nine analysed meteorological parameters every hour. Data input to MESAN consists of surface observations from different observation systems, numerical weather prediction model fields, weather radar and satellite imageries, and climate information. Each data source is quality controlled before being subjected to an optimal interpolation (OI) scheme, together with data from the other sources. This paper presents MESAN's accumulated precipitation product. The methods used for interpolation of the multisource data are presented and discussed, as are the methods used to quality control each data source. Results from August-October 1995, using multisource data including gauge observations from the countries in the Baltic Sea Experiment (BALTEX) Region, exemplify the product. OI, used with a variable first guess error, has been compared with conventional inverse distance interpolation of precipitation in two catchments in mountainous terrain. Verification was conducted through modelled runoff, using areally integrated accumulated precipitation, compared with hydrograph observations. Significant improvements using OI were found in one of the catchments. The relative contribution (or importance) of each data source to the analysis has been evaluated using cross validation. Results show that gauge networks are the single most important sources and that radar imagery makes a significant contribution in areas lacking networks of dense gauges, such as the Baltic Sea. Analysis quality improves with the use of a greater number of input data sources. MESAN is an appropriate tool for creating an overall best estimate precipitation analysis and should be useful in applications where such information is required. In validating precipitation produced by numerical weather prediction models, analyses generated without the use of such model fields is recommended.