Precipitation estimate over the Baltic Sea: Present state of the art

Precipitation is one of the main components in the water balance, and probably the component determined with the greatest uncertainties. In the present paper we focus on precipitation (mainly rain) over the Baltic Sea as a part of the BALTEX project to examine the present state of the art concerning different precipitation estimates over that area. Several methods are used, with the focus on 1) interpolation of available synoptic stations; 2) a mesoscale analysis system including synoptic, automatic, and climate stations, as well as weather radar and an atmospheric model; and 3) measurements performed on ships. The investigated time scales are monthly and yearly and also some long-term considerations are discussed. The comparison shows that the differences between most of the estimates, when averaged over an extended period and a larger area, are in the order of 10-20%, which is in the same range as the correction of the synoptic gauge measurements due to wind and evaporation losses. In all data sets using gauge data it is important to include corrections for high winds. To improve the structure of precipitation over sea more focus is to be put on the use of radar data and combinations of radar data and other data. Interpolation methods that do not consider orographic effects must treat areas with large horizontal precipitation gradients with care. Due to the large variability in precipitation in time and space, it is important to use long time periods for climate estimates of precipitation Ship measurements are a valuable contribution to precipitation information over sea, especially for seasonal and annual time scales

SSM/I-derived total water vapour content over the Baltic Sea compared to independent data

In order to investigate the energy and water balance of the Baltic Sea and its catchment area, the commonly used regional models have to be validated against observation data. One of the most important parameters of the hydrological cycle is the vertically integrated atmospheric water vapour content. Satellite observations from SSM/I (Special Sensor Microwave/Imager) can help to provide data over the sea. The accuracy of these results are tested with observations of radiosondes, which are launched from RV Alkor cruising in the Baltic Sea. The bias of both data sets is negligibly small. However, due to the low spatial resolution, problems occur in coastal regions, arising problems in particular in the small-scaled Baltic Sea. Thus, a correcting scheme for disturbing land influences is presented. This satellite-derived data set is compared with REMO-DWD results (REgional Model using physical package of DWD) for the PIDCAP period (Pilot Study for Intensive Data Collection and Analysis of Precipitation) from August to October 1995. Effects of the different temporal and spatial data resolutions on the variance are quantified and eliminated. For this purpose the water vapour content is used, which is derived from the GPS (Global Positioning System) network over Sweden and Finland by ELGERED et al. (1997). SSM/I and cps data indicate that REMO overestimates the total water vapour content by about 2 kgm(-2)

The joint influence of break and noise variance on the break detection capability in time series homogenization

Instrumental climate records of the last centuries suffer from multiple breaks due to relocations and changes in measurement techniques. These breaks are detected by relative homogenization algorithms using the difference time series between a candidate and a reference. Modern multiple changepoint methods use a decomposition approach where the segmentation explaining most variance defines the breakpoints, while a stop criterion restricts the number of breaks. In this 10 study a pairwise multiple breakpoint algorithm consisting of these two components is tested with simulated data for a range of signal-to-noise ratios (SNRs) found in monthly temperature station datasets. The results for low SNRs obtained by this algorithm do not differ much from random segmentations; simply increasing the stop criterion to reduce the number of breaks is shown to be not helpful. This can be understood by considering that in case of multiple breakpoints also a random segmentation explains about half of the break variance. We derive analytical equations for the explained noise and break 15 variance for random and optimal segmentations. From these we conclude that reliable break detection at low, but realistic SNRs needs a new approach. The problem is relevant because the uncertainty of station trends is shown to be climatologically significant also for these small SNRs. An important side-result is a new method to determine the break variance and the number of breaks in a difference time series by studying the explained variance for random break positions

Precipitation Estimates over the Baltic Sea: Present State of the Art

Precipitation is one of the main components in the water balance, and probably the component determined with the greatest uncertainties. In the present paper we focus on precipitation (mainly rain) over the Baltic Sea as a part of the BALTEX project to examine the present state of the art concerning different precipitation estimates over that area. Several methods are used, with the focus on 1) interpolation of available synoptic stations; 2) a mesoscale analysis system including synoptic, automatic, and climate stations, as well as weather radar and an atmospheric model; and 3) measurements performed on ships. The investigated time scales are monthly and yearly and also some long-term considerations are discussed. The comparison shows that the differences between most of the estimates, when averaged over an extended period and a larger area, are in the order of 10-20%, which is in the same range as the correction of the synoptic gauge measurements due to wind and evaporation losses. In all data sets using gauge data it is important to include corrections for high winds. To improve the structure of precipitation over sea more focus is to be put on the use of radar data and combinations of radar data and other data. Interpolation methods that do not consider orographic effects must treat areas with large horizontal precipitation gradients with care. Due to the large variability in precipitation in time and space, it is important to use long time periods for climate estimates of precipitation Ship measurements are a valuable contribution to precipitation information over sea, especially for seasonal and annual time scales