Simulating black carbon and dust and their radiative forcing in seasonal snow: a case study over North China with field campaign measurements

Abstract

Abstract.A state-of-the-art regional model, the Weather Research and Forecasting (WRF) model (Skamarock et al., 2008) coupled with a chemistry component (Chem) (Grell et al., 2005), is coupled with the snow, ice, and aerosol radiative (SNICAR) model that includes the most sophisticated representation of snow metamorphism processes available for climate study. The coupled model is used to simulate black carbon (BC) and dust concentrations and their radiative forcing in seasonal snow over North China in January-February of 2010, with extensive field measurements used to evaluate the model performance. In general, the model simulated spatial variability of BC and dust mass concentrations in the top snow layer (hereafter BCS and DSTS, respectively) are consistent with observations. The model generally moderately underestimates BCS in the clean regions but significantly overestimates BCS in some polluted regions. Most model results fall within the uncertainty ranges of observations. The simulated BCS and DSTS are highest with > 5000 ng g −1 and up to 5 mg g −1 , respectively, over the source regions and reduce to < 50 ng g −1 and < 1 µg g −1 , respectively, in the remote regions. BCS and DSTS introduce a similar magnitude of radiative warming (∼ 10 W m −2 ) in the snowpack, which is comparable to the magnitude of surface radiative cooling due to BC and dust in the atmosphere. This study represents an effort in using a regional modeling framework to simulate BC and dust and their direct radiative forcing in snowpack.Although a variety of observational data sets have been used to attribute model biases, some uncertainties in the results remain, which highlights the need for more observations, particularly concurrent measurements of atmospheric and snow aerosols and the deposition fluxes of aerosols, in future campaigns.

The impact of atmospheric mineral aerosol deposition on the albedo of snow & sea ice: are snow and sea ice optical properties more important than mineral aerosol optical properties?

“…Chýlek et al, 1983;Warren, 1984;Clarke and Noone, 1985;Warren and Clarke, 1990;Grenfell et al, 2002;Lee Taylor and Madronich, 2002;Jacobson, 2004;Flanner et al, 2007;Doherty et al, 2010;Reay et al, 2012;Ye et al, 2012;King, 2013, 2014). Field observations and modelling simulations have also shown that increases in dust deposition to snow lead to radiative forcing that affects the energy balance of snow (Woo and Dubreuil, 1985;Aoki et al, 1998;Painter et al, 2007Painter et al, , 2012Huang et al, 2011;Wang et al, 2013;Zhang et al, 2013;Zhao et al, 2014;Yasunari et al, 2014). However, although anthropogenic deposits in polar snow and ice have been well characterised, studies on the effects of natural mineral aerosol deposits are more scarce.…”

Observations and model simulations of snow albedo reduction in seasonal snow due to insoluble light-absorbing particles during 2014 Chinese survey

“…AOD measurements were collected in cloudfree conditions between 11:00 and 13:00 (Beijing local time) to prevent the effects of optical distortions due to large solar zenith angles. Then, the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua and Terra satellites was used to retrieve the AOD and fire spot datasets (Kaufman et al, 1997;Zhang et al, 2013b;Zhao et al, 2014). The retrieved MODIS AOD is reliable and accurate when applied to three visible channels over vegetated land and ocean surfaces Ichoku et al, 2002a;.…”

“…However, models did not capture these potential large sources of local dust in snowpack and may overestimate BC forcing processes (Painter et al, 2007(Painter et al, , 2010(Painter et al, , 2012. Recently, several seasonal snow collection campaigns were performed across northern China, the Himalayas, North America, Greenland and the Arctic (Cong et al, 2015;Dang and Hegg, 2014;Doherty et al, 2010Doherty et al, , 2014Huang et al, 2011;Xu et al, 2009Xu et al, , 2012Zhao et al, 2014). However, determining the effects of ILAPs on snow albedo reduction continues to be challenging (Huang et al, 2011;Wang et al, 2013aWang et al, , 2015Ye et al, 2012;Zhang et al, 2013a).…”

Sensitivity of biogenic volatile organic compounds to land surface parameterizations and vegetation distributions in California

“…CLM4 in global and region applications has been shown to be accurate in describing snow, soil and vegetation processes Jin and Miller, 2007;Zhao et al, 2014). CLM4 includes 5 layers for snow, 10 layers for soil and 1 layer for vegetation.…”