Mini-seminar on polar climate and weather
Matthias Zahn and Tom Bracegirdle will be visiting Erik Kolstad as part of the Bjerknes Visiting Fellow programme from 9-12 March.
Hovedinnhold
Matthias Zahn (Institute of Coastal Research, Helmholtz Centre Geesthacht, Germany):
Past and projected future changes of North Atlantic polar low frequency
Abstract
I will present methodology and results of my work on frequency changes of North Atlantic polar lows. Changes of annual polar low numbers were investigated in the past six decades and in an anthropogenically warmed atmosphere in a projected IPCC future. I will show that by means of dynamical downscaling it is possible to simulate these storms with a Regional Climate Model (RCM). The results are used to develop an automated detection procedure for polar lows, which then is applied to the output fields of long-term RCM simulations.The RCM was driven by NCEP reanalysis data of the past and by global data of IPCC future projections. While there could not be found any systematic changes of polar low frequency for the past, a significant decrease was discovered associated with projected atmospheric warming. This decrease is linked to an increase in atmospheric stability with warming, which is a result of faster rising air temperatures compared to sea surface temperatures.
I will finalise my presentation showing preliminary results of our current project, in which we dynamically downscale NCEP data using a global climate model (GCM) in order to compile a global high resolution long-term hindcast. These data are used to detect tropical cyclones and investigate their climatological properties.
Tom Bracegirdle (British Antarctic Survey, Cambridge, UK):
Constraining multi-model estimates of 21st century regional polar warming
Abstract
In this talk I will present work on potential observational constraints on the large model uncertainty in projected 21st century regional warming over the Arctic and Antarctic. Statistical relationships between future and historical model runs in multi-model ensembles are increasingly exploited to make more constrained projections of climate change. Such ‘emergent relationships’ are particularly significant over the polar regions. A promising approach to reducing model uncertainty is to capture these emergent relationships using a simple ensemble linear regression model. For both the CMIP3 and CMIP5 climate models, this approach gives different and more precise estimated mean changes compared to the equal-weight multi-model mean approach. For example, estimates based on ensemble regression exhibit less warming over the Barents Sea, where most climate models have too much sea ice in their present-day climatology. This has implications for projections of regional extreme weather phenomena such as polar lows.
Past and projected future changes of North Atlantic polar low frequency
Abstract
I will present methodology and results of my work on frequency changes of North Atlantic polar lows. Changes of annual polar low numbers were investigated in the past six decades and in an anthropogenically warmed atmosphere in a projected IPCC future. I will show that by means of dynamical downscaling it is possible to simulate these storms with a Regional Climate Model (RCM). The results are used to develop an automated detection procedure for polar lows, which then is applied to the output fields of long-term RCM simulations.The RCM was driven by NCEP reanalysis data of the past and by global data of IPCC future projections. While there could not be found any systematic changes of polar low frequency for the past, a significant decrease was discovered associated with projected atmospheric warming. This decrease is linked to an increase in atmospheric stability with warming, which is a result of faster rising air temperatures compared to sea surface temperatures.
I will finalise my presentation showing preliminary results of our current project, in which we dynamically downscale NCEP data using a global climate model (GCM) in order to compile a global high resolution long-term hindcast. These data are used to detect tropical cyclones and investigate their climatological properties.
Tom Bracegirdle (British Antarctic Survey, Cambridge, UK):
Constraining multi-model estimates of 21st century regional polar warming
Abstract
In this talk I will present work on potential observational constraints on the large model uncertainty in projected 21st century regional warming over the Arctic and Antarctic. Statistical relationships between future and historical model runs in multi-model ensembles are increasingly exploited to make more constrained projections of climate change. Such ‘emergent relationships’ are particularly significant over the polar regions. A promising approach to reducing model uncertainty is to capture these emergent relationships using a simple ensemble linear regression model. For both the CMIP3 and CMIP5 climate models, this approach gives different and more precise estimated mean changes compared to the equal-weight multi-model mean approach. For example, estimates based on ensemble regression exhibit less warming over the Barents Sea, where most climate models have too much sea ice in their present-day climatology. This has implications for projections of regional extreme weather phenomena such as polar lows.
03.03.2015