de.mpg.escidoc.pubman.appbase.FacesBean
English
 
Contact usLogin
  Advanced SearchBrowse

Item


Journal Article

Released

Implications on atmospheric dynamics and the effect on black carbon transport into the Eurasian Arctic based on the choice of land surface model schemes and reanalysis data in model simulations with WRF

Cavazos Guerra, C., Lauer, A., Herber, A. B., Butler, T. M., Rinke, A., Dethloff, K. (2016 online): Implications on atmospheric dynamics and the effect on black carbon transport into the Eurasian Arctic based on the choice of land surface model schemes and reanalysis data in model simulations with WRF. - Atmospheric Chemistry and Physics Discussion, p. 1-40.
DOI: http://doi.org/10.5194/acp-2016-942


http://publications.iass-potsdam.de/pubman/item/escidoc:1885913
Resources

1885913_discuss.pdf
(Publisher version), 3MB

IASS-Authors
http://publications.iass-potsdam.de/cone/persons/resource/CCG

Cavazos Guerra ,  Carolina
IASS Institute for Advanced Sustainability Studies Potsdam;

http://publications.iass-potsdam.de/cone/persons/resource/TBU

Butler ,  Tim M.
IASS Institute for Advanced Sustainability Studies Potsdam;

Abstract
A realistic simulation of physical and dynamical processes in the Arctic atmosphere and its feedbacks with the surface conditions is still a challenge for state-of-the-art Arctic climate models. This is of critical importance because studies of, for example, transport of pollutants from middle latitudes into the Arctic rely on the skill of the model in correctly representing atmospheric circulation including the key mechanisms and pathways of pollutant transport. In this work the performance of the Weather Research and Forecast model (WRF) with two land surface model schemes (Noah and NoahMP) and two reanalysis data sets for creation of lateral boundary conditions (ERA-interim and ASR) is evaluated focusing on meteorological surface properties and atmospheric dynamics. This includes the position and displacement of the polar dome and other features characterizing atmospheric circulation associated to sea ice maxima/minima extent within the Eurasian Arctic. The model simulations analyzed are carried out at 15-km horizontal resolution over a period of five years (2008 to 2012). The WRF model simulations are evaluated against surface meteorological data from automated weather stations and vertical profiles from radiosondes. Results show that the model is able to reproduce the main features of the atmospheric dynamics and vertical structure of the Arctic atmosphere reasonably well. The influence of the choice of the reanalyses used as initial and lateral boundary condition and of the LSM on the model results is complex and no combination is found to be clearly superior in all variables analyzed. The model results show that a more sophisticated formulation of land surface processes does not necessarily lead to significant improvements in the model results. This suggests that other factors such as the decline of the Arctic sea ice, stratosphere-troposphere interactions, atmosphere-ocean interaction, and boundary layer processes are also highly important and can have a significant influence on the model results. The “best” configuration for simulating Arctic meteorology and processes most relevant for pollutant transport (ASR + NoahMP) is then used in a simulation with WRF including aerosols and chemistry (WRF-Chem) to simulate black carbon (BC) concentrations in and around the Arctic and to assess the role of the modeled atmospheric circulation in the simulated BC concentrations inside the Arctic domain. Results from simulations with chemistry are evaluated against aerosol optical depth from several Aeronet stations and BC concentrations and particle number concentrations from several stations from the EBAS database. The results with WRF-Chem show a strong dependency of the simulated BC concentration on the modeled meteorology and the transport of the pollutants around our domain. The results also show that biases in the modeled BC concentrations can also be related to the emission data. Significant improvements of the models and of our understanding of the impact of anthropogenic BC emissions on the Arctic strongly depends on the availability of suitable, long-term observational data of concentrations of BC and particulate matter, vertical profiles of temperature and humidity and wind.