2008 report
Progress: 50%
Task 2.1 Objectives
The objectives of Task 2.1 are (i) to better detect Arctic cyclones, (ii) to improve modelling of their interaction with sea ice, and (iii) to quantify the contribution of the cyclones to the transport of heat and moisture. During the months 13-24 the specific objectives were:
- to study the Arctic cyclone activity and cyclone tracks on the basis of available data. This is essential background information to quantify the gaps of the present observational network, which seems to be adequate to detect most synoptic scale cyclones but not mesoscale cyclones,
- To deploy a set of buoys in late winter 2007 which will provide high-resolution information on the atmospheric pressure field over the Arctic ocean to better detect mesoscale cyclones,
- To derive the fields of total water vapour and cloud water content on the basis of remote sensing data, and to study the potential of utilizing these fields in cyclone detection.
Task 2.1 Progress towards the objectives
Changes to the program schedule: none
Percentage of completed task: 50
The work in Task 2.1 has focussed on statistics of Arctic cyclones and wind statistics (University of Tartu, University of Hamburg), role of cyclones in moisture transport to the Arctic (University of Tartu, FMI), retrieval of total water vapour from remote sensing data (University of Bremen), preparation and conduction of field measurements related to cyclones (University of Hamburg), modelling studies related to cyclones (University of Hamburg, FMI, AWI) and integrated remote sensing of ice/snow and atmospheric parameters .
After accomplishing the previous report on statistics of the Arctic cyclone activity and tracks University of Tartu carried out a quality control and new analyses. Data base of cyclones was complemented by data from two years (2003, 2004). Using linear regression analysis trends in variables of Arctic cyclones were recalculated. Results of the analysis indicate that the change tendencies observed during 1948-2002 have mostly continued during 2003-2004 in even higher magnitude. It demonstrates a continuing intensification of cyclonic activity in the Arctic basin. Also, preliminary analysis using database of cyclones developed in the Institute of Meteorology, Hamburg of University, based on ERA-40 is carried out. A manuscript of an article summarising the results of the studies on Arctic cyclones is prepared for publication in a peer reviewed journal.
University of Hamburg used the 6-hourly ERA-40 re-analysis of ECMWF and elaborated a wind statistics for the Arctic for the period 1958-2002. The results were related to the cyclone activity in the same area. Cyclone detection and cyclone tracks were determined applying the methods from Simmonds and Murray.
University of Hamburg studied the influence of cyclones on the sea ice with the coupled ice-ocean model NAOSIM of AWI. As atmospheric forcing artificial cyclones were prescribed. The sensitivity of the cyclone's impact on the sea ice was investigated by systematic variation of parameters such as cyclone pressure gradient, cyclone track speed, and initial ice concentration and thickness.
University of Hamburg successfully deployed on 25 April 2007 sixteen buoys in a regular 400 km times 400 km array on the sea ice in the interior Arctic centred at 88°N, 135°E. Buoys measure continuously position, air pressure and temperature at approximately one-hourly intervals. Many buoys were lost during the summer melting period. At the end of October (six months after deployment) the buoy array consisted of five buoys and the centre was situated at 84°N, 5°E corresponding to about 1000 km distance from the initial position. Buoy data are used to measure the drift of the central Arctic ice sheet and the relative ice motion within the array (deformation, divergence, rotation), to relate these to the passing atmospheric pressure patterns (lows and highs), and to validate operational weather models.
FMI and University of Tartu have applied ERA40 re-analysis data to study the role of cyclones on the moisture transport to the Arctic. The total northward transport has been divided into the contributions of mean meridional circulation, standing eddies and transient eddies.
FMI has contributed to the study on cyclone detection on the basis of AMSU-B data, which is led by the University of Bremen.
FMI has modelled a cyclone-related case of warm air advection over the Arctic sea ice (see Tasks 2.2 and 2.3).
FIMR and FMI in collaboration with University of Alaska, Fairbanks, have made coupled atmosphere / sea-ice modelling experiments for a case of cyclone observed in 1998. The model results have been validated against SHEBA observations and AVHRR data on the snow surface temperature.
For validation, University of Bremen has compared total water vapour (TWV) retrieved with their algorithm from AMSU-B data with TWV retrieved from radiances in the visible/near-infrared range from GOME/SCIAMACHY. The result is that TWV data from these two sources are highly correlated and have only a small bias.
University of Bremen continued the study of the detection of polar lows (intense mesoscale arctic cyclones) in AMSU-B-derived TWV data. Polar lows are visible in these data because high ice clouds usually associated with polar lows strongly scatter microwave radiation, thus partially shielding the sensor from microwave radiation from below the ice clouds. As a result the algorithm basically only retrieves the TWV above the cloud tops which is extremely low. This is the same physical effect that has recently been used to detect tropical deep convection.
AWI carried out successfully Polarstern expedition ARKXXII/2 to the inner Arctic
from end of July to end of September 2007. The routine meteorological observations as well as data from daily soundings were collected and will be analyzed with respect to cyclone activity. Data will be transferred to the DAMOCLES data bank system by AWI.
IOPAN has collected most of the database of the Svalbard station Hornsund including also historical meteorological data and is now starting the analysis.
DTU has worked on development of an integrated retrieval algorithm for ice/snow and atmospheric parameters. The algorithm is an inversion of the RTTOV radiative transfer model for the atmosphere and the MEMLS emissivity model for ice and snow. A preliminary version of the retrieval algorithm using simpler polynomial parameterisations has been running for some time.
