Piia Post

About the relationships between estonian weather elements and European circulation patterns

Abstract There have been several attempts to classify the large-scale circulation within the area of Europe. One of the oldest and most popular one is the German Weather Services Grosswetterlagen, with time-series of daily records beginning in 1881. Grosswetterlagen (atmospheric circulation patterns) are actually classified for Central Europe using Northern Hemispheric weather maps at the sea level and 500 hPa height. Only large-scale features of general circulation are included in the classification scheme. In our work we have investigated the suitability of the Grosswetterlagen classification for an outlying region of Europe. The research area — Estonia — lies in the northeastern part of Europe. Typical weather maps of Grosswetterlagen are used to determine the prevailing air flow over Central Europe and Estonia. 500 hPa wind measured at Tallinn station for the time period 1992–1993 have been used as additional data. Annual cycles of temperature deviation at Parnu station for different circulation patterns are used for determining air masses during these circulation patterns. The upper air flow in Central Europe and Estonia is similar for zonal and half-meridional circulations, But the air masses during circulation patterns from all 3 circulation groups could be very different for these regions. Examples demonstrate the links of circulation patterns to local temperature fields, but give also the reason for further complex investigation of relationships.

Retrieval of Tropospheric BrO and NO2 from UV-Visible Observations

This contribution has been concerned with three different activities. First, global N02 data records from HALOE, POAM-II and POAM-III satellite instruments complemented by ground-based data sets from the NDSC, have been investigated for mutual consistency and exploited to build a global time-latitude stratospheric NO2 profile climatology that may be used for tropospheric NO2 retrieval from ERS2-G0ME. Second, a BrO total column product derived from GOME has been created over the total present lifetime of the ERS-2 satellite (1996 to 2002) and made available to the scientific community through a dedicated web site. In addition, a prototype improved GOME BrO retrieval algorithm has been designed with the aim to determine better global tropospheric BrO columns from the combined use of GOME data and three-dimensional model data, and to provide the stratospheric reference needed in a tropospheric residual approach. Third, ground-based multi-axis DOAS measurements have been conducted at the Observatoire de Haute Provence, (OHP, 44 °N) between January 2001 and June 2002 in support of satellite retrieval activities. Results obtained demonstrate the high sensitivity of the measurements to tropospheric amounts of NO2 and HCHO, as well as the potential of the technique to unravel small mid-latitude free-tropospheric BrO contents. As to the latter point, comparisons between combined GOME-SLIMCAT and MAX-DOAS tropospheric BrO evaluations suggest that approximately half of the mid-latitude BrO total column resides in the troposphere.

A two-parameter approximation in cloudiness variability studies

Abstract In order to separate the influence of clouds on the Earths radiation budget from that of several other meteorological parameters, a simple two-parameter approximation of monthly mean cloudiness is produced on the basis of the Nimbus-7 wide field-of-view radiometer eigth-year measurements (1978–1986). The approximation converts the radiation budget components at the top of the Earths atmosphere into two effective cloud parameters: cloud amount and cloud-top height over the latitude belt 58.5°S–58.5°N. Instead of real three-level cloudiness the approximation treats global cloudiness as one opaque layer with determined albedo for solar radiation. Cloud emissivity is supposed to be 1. The main goal for the approximation is to use these effective parameters for describing the interannual redistribution of cloudiness. Energetical scales of the obtained redistributions inspire an alternative to the widely produced, CO 2 induced global warming.

Time Series Analysis: A New Methodology for Comparing the Temporal Variability of Air Temperature

Temporal variability of three different temperature time series was compared by the use of statistical modeling of time series. The three temperature time series represent the same physical process, but are at different levels of spatial averaging: temperatures from point measurements, from regional Baltan65

Daily temperature and precipitation extremes in the Baltic Sea region derived from the BaltAn65+ reanalysis

Daily 2-m temperature and precipitation extremes in the Baltic Sea region for the time period of 1965–2005 is studied based on data from the BaltAn65 + high resolution atmospheric reanalysis. Moreover, the ability of regional reanalysis to capture extremes is analysed by comparing the reanalysis data to gridded observations. The shortcomings in the simulation of the minimum temperatures over the northern part of the region and in the simulation of the extreme precipitation over the Scandinavian mountains in the BaltAn65+ reanalysis data are detected and analysed. Temporal trends in the temperature and precipitation extremes in the Baltic Sea region, with the largest increases in temperature and precipitation in winter, are detected based on both gridded observations and the BaltAn65+ reanalysis data. However, the reanalysis is not able to capture all of the regional trends in the extremes in the observations due to the shortcomings in the simulation of the extremes.

Local air temperature tolerance: a sensible basis for estimating climate variability

The customary representation of climate using sample moments is generally biased due to the noticeably nonstationary behaviour of many climate series. In this study, we introduce a moment-free climate representation based on a statistical model fitted to a long-term daily air temperature anomaly series. This model allows us to separate the climate and weather scale variability in the series. As a result, the climate scale can be characterized using the mean annual cycle of series and local air temperature tolerance, where the latter is computed using the fitted model. The representation of weather scale variability is specified using the frequency and the range of outliers based on the tolerance. The scheme is illustrated using five long-term air temperature records observed by different European meteorological stations.