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It is shown that the Arctic averaged wintertime temperature variability during the 20th century can be essentially described by two orthogonal modes. These modes were identified by an Empirical Orthogonal Function (EOF) decomposition of the 1892-1999 surface wintertime air temperature anomalies (40degreesN-80degreesN) using a gridded dataset covering high Arctic. The first mode (1st leading EOF) is related to the NAO and has a major contribution to Arctic warming during the last 30 years. The second one (3rd leading EOF) dominates the SAT variability prior to 1970. A correlation between the corresponding principal component PC3 and the Arctic SAT anomalies is 0.79. This mode has the largest amplitudes in the Kara-Barents Seas and Baffin Bay and exhibits no direct link to the large-scale atmospheric circulation variability, in contrast to the other leading EOFs. We suggest that the existence of this mode is caused by long-term sea ice variations presumably due to Atlantic inflow variability.

Recent proxy data obtained from ice core measurements, dendrochronology and valley glaciers provide important information on the evolution of the regional or local climate. General Circulation Models integrated over a long period of time could help to understand the (external and internal) forcing mechanisms of natural climate variability. For a systematic interpretation of in situ paleo proxy records, a combined method of dynamical and statistical modeling is proposed. Local ,paleo records' can be simulated from GCM output by first undertaking a model-consistent statistical downscaling and then using a process-based forward modeling approach to obtain the behavior of valley glaciers and the growth of trees under specific conditions. The simulated records can be compared to actual proxy records in order to investigate whether e.g. the response of glaciers to climatic change can be reproduced by models and to what extent climate variability obtained from proxy records (with the main focus on the last millennium) can be represented. For statistical downscaling to local weather conditions, a multiple linear forward regression model is used. Daily sets of observed weather station data and various large-scale predictors at 7 pressure levels obtained from ECMWF re- analyses are used for development of the model. Daily data give the closest and most robust relationships due to the strong dependence on individual synoptic-scale patterns. For some local variables, the performance of the model can be further increased by developing seasonal specific statistical relationships. The model is validated using both independent and restricted predictor data sets. The model is applied to a long integration of a mixed layer GCM experiment simulating pre-industrial climate variability. The dynamical-statistical local GCM output within a region around Nigardsbreen glacier, Norway is compared to nearby observed station data for the period 1868-1993. Patterns of observed variability on the annual to decadal scale and the mean temperature change due to pre-industrial climatic conditions are realistically simulated for this location. The local output produced by the described method will be used to force a process- based model for the production of ,synthetic' proxy data, e.g. the simulation of a valley glacier.

Using plane-wave pseudopotential calculations based on density-functional theory at the local-density-approximation level we investigate all the possible kappa-Al2O3 structures which are permitted by the known crystal symmetry. We find that structures with sixfold coordinated Al atoms are significantly more stable than those having any or all of the Al atoms in fourfold coordinated sites. This is in agreement with preliminary experimental results.

In this report, we present the results of elaboration of methods of inversion of the GPS /MET satellite data taking diffraction and multipath effects into account. The first results of the GPS /MET program of sounding of the Earth’s atmosphere by means of a Low Earth Orbit satellite implemented with a GPS receiver, indicated that in the lower troposphere, the phase and amplitude of the signal received undergo strong oscillations. This effect is a consequence of multipath propagation resulting from complicated structure of the atmospheric refractivity in the tropical regions. We propose a method of processing the phase measurements, based on the theory of diffraction. The method was tested in processing GPS/MET radio soundings. Comparison of the reconstructed profiles of the temperature and humidity with those derived from the radiosonde measurements extracted from the NMC Global Atmospheric Circulation Model, indicates validity of the method proposed. An approach to the nudging assimilation of the GPS /MET refractometric data is proposed.

The climate and natural variability of the large-scale stratospheric circulation simulated by a newly developed general circulation model are evaluated against available global observations. The simulation consisted of a 30-year annual cycle integration performed with a comprehensive model of the troposphere and stratosphere. The observations consisted of a 15-year dataset from global operational analyses of the troposphere and stratosphere. The model evaluation concentrates on the simulation of the evolution of the extratropical stratospheric circulation in both hemispheres. The December-February climatology of the observed zonal mean winter circulation is found to be reasonably well captured by the model, although in the Northern Hemisphere upper stratosphere the simulated westerly winds are systematically stronger and a cold bias is apparent in the polar stratosphere. This Northern Hemisphere stratospheric cold bias virtually disappears during spring (March-May), consistent with a realistic simulation of the spring weakening of the mean westerly winds in the model. A considerable amount of monthly interannual variability is also found in the simulation in the Northern Hemisphere in late winter and early spring. The simulated interannual variability is predominantly caused by polar warmings of the stratosphere, in agreement with observations. The breakdown of the Northern Hemisphere stratospheric polar vortex appears therefore to occur in a realistic way in the model. However, in early winter the model severely underestimates the interannual variability, especially in the upper troposphere. The Southern Hemisphere winter (June-August) zonal mean temperature is systematically colder in the model, and the simulated winds are somewhat too strong in the upper stratosphere. Contrary to the results for the Northern Hemisphere spring, this model cold bias worsens during the Southern Hemisphere spring (September-November). Significant discrepancies between the model results and the observations are therefore found during the breakdown of the Southern Hemisphere polar vortex. For instance, the simulated Southern Hemisphere stratospheric westerly jet continuously decreases in intensity more or less in situ from June to November, while the observed stratospheric jet moves downward and poleward.

This report presents a further investigation of the capabilities of the satellite radio- occultation system for monitoring of the Earth’s atmosphere (started at Report No.119). Refractometric sounding of the Earth’s atmosphere using a multi-orbit satellite system close to real GPS-LEO satellite system is simulated using data from the ECHAM3 (T106) model. The direct model of the refraction measurements and its linearization, which are necessary for assimilation of refractometric data, are formulated. Computational simula- tions of pressure and temperature retrieval from the refractometric data, including usage of the “first guess” of the meteorological fields, are performed. A method of retrieval of the tropospheric humidity from the radio-occultation data, using the T106 model fields is considered. The problems of processing of the satellite phase observation data, and iono- spheric correction is also discussed. A special attention is dedicated to investigation of the residual ionospheric errors and to methods of their reduction. Statistical characteristics of the super-refraction in the boundary layer are estimated.

A fingerprint method for detecting anthropogenic climate change is applied to new simulations with a coupled ocean-atmosphere general circulation model (CGCM) forced by increasing concentrations of greenhouse gases and aerosols covering the years 1880 to 2050. in addition to the anthropogenic climate change signal, the space-time structure of the natural climate variability for near-surface temperatures is estimated from instrumental data over the last 134 years and two 1000 year simulations with CGCMs. The estimates are compared with paleoclimate data over 570 years. The space—time information on both the signal and the noise is used to maximize the signal—to—noise ratio of a detection variable obtained by applying an optimal filter (fingerprint) to the observed data. The inclusion of aerosols slows the predicted future warming. The probability that the observed increase in nearusurface temperatures in recent decades is of natural origin is estimated to be less than 5 %. However, this number is dependent on the estimated natural variability level, which is still subject to some uncertainty.