Improving snow albedo processes in WRF/SSiB regional climate model to assess impact of dust and black carbon in snow on surface energy balance and hydrology over western U.S.

© 2015. American Geophysical Union. All Rights Reserved. Two important factors that control snow albedo are snow grain growth and presence of light-absorbing impurities (aerosols) in snow. However, current regional climate models do not include such processes in a physically based manner in their land surface models. We improve snow albedo calculations in the Simplified Simple Biosphere (SSiB) land surface model coupled with the Weather Research and Forecasting (WRF) regional climate model (RCM), by incorporating the physically based SNow ICe And Radiative (SNICAR) scheme. SNICAR simulates snow albedo evolution due to snow aging and presence of aerosols in snow. The land surface model is further modified to account for deposition, movement, and removal by meltwater of such impurities in the snowpack. This paper presents model development technique, validation with in situ observations, and preliminary results from RCM simulations investigating the impact of such impurities in snow on surface energy and water budgets. By including snow-aerosol interactions, the new land surface model is able to realistically simulate observed snow albedo, snow grain size, dust in snow, and surface water and energy balances in offline simulations for a location in western U.S. Preliminary results with the fully coupled RCM show that over western U.S., realistic aerosol deposition in snow induces a springtime average radiative forcing of 16W/m2 due to a 6% albedo reduction, a regional surface warming of 0.84°C, and a snowpack reduction of 11mm

Improving snow albedo processes in WRF/SSiB regional climate model to assess impact of dust and black carbon in snow on surface energy balance and hydrology over western U.S.

© 2015. American Geophysical Union. All Rights Reserved. Two important factors that control snow albedo are snow grain growth and presence of light-absorbing impurities (aerosols) in snow. However, current regional climate models do not include such processes in a physically based manner in their land surface models. We improve snow albedo calculations in the Simplified Simple Biosphere (SSiB) land surface model coupled with the Weather Research and Forecasting (WRF) regional climate model (RCM), by incorporating the physically based SNow ICe And Radiative (SNICAR) scheme. SNICAR simulates snow albedo evolution due to snow aging and presence of aerosols in snow. The land surface model is further modified to account for deposition, movement, and removal by meltwater of such impurities in the snowpack. This paper presents model development technique, validation with in situ observations, and preliminary results from RCM simulations investigating the impact of such impurities in snow on surface energy and water budgets. By including snow-aerosol interactions, the new land surface model is able to realistically simulate observed snow albedo, snow grain size, dust in snow, and surface water and energy balances in offline simulations for a location in western U.S. Preliminary results with the fully coupled RCM show that over western U.S., realistic aerosol deposition in snow induces a springtime average radiative forcing of 16W/m2 due to a 6% albedo reduction, a regional surface warming of 0.84°C, and a snowpack reduction of 11mm

Spring land temperature anomalies in northwestern US and the summer drought over Southern Plains and adjacent areas

Recurrent drought and associated heatwave episodes are important features of the US climate. Many studies have examined the connection between ocean surface temperature changes and conterminous US droughts. However, remote effects of large-scale land surface temperature variability, over shorter but still considerable distances, on US regional droughts have been largely ignored. The present study combines two types of evidence to address these effects: climate observations and model simulations. Our analysis of observational data shows that springtime land temperature in northwest US is significantly correlated with summer rainfall and surface temperature changes in the US Southern Plains and its adjacent areas. Our model simulations of the 2011 Southern Plains drought using a general circulation model and a regional climate model confirm the observed relationship between land temperature anomaly and drought, and suggest that the long-distance effect of land temperature changes in the northwest US on Southern Plains droughts is probably as large as the more familiar effects of ocean surface temperatures and atmospheric internal variability. We conclude that the cool 2011 springtime climate conditions in the northwest US increased the probability of summer drought and abnormal heat in the Southern Plains. The present study suggests a strong potential for more skillful intra-seasonal predictions of US Southern Plains droughts when such facts as ones presented here are considered

Spring land temperature anomalies in northwestern US and the summer drought over Southern Plains and adjacent areas

Recurrent drought and associated heatwave episodes are important features of the US climate. Many studies have examined the connection between ocean surface temperature changes and conterminous US droughts. However, remote effects of large-scale land surface temperature variability, over shorter but still considerable distances, on US regional droughts have been largely ignored. The present study combines two types of evidence to address these effects: climate observations and model simulations. Our analysis of observational data shows that springtime land temperature in northwest US is significantly correlated with summer rainfall and surface temperature changes in the US Southern Plains and its adjacent areas. Our model simulations of the 2011 Southern Plains drought using a general circulation model and a regional climate model confirm the observed relationship between land temperature anomaly and drought, and suggest that the long-distance effect of land temperature changes in the northwest US on Southern Plains droughts is probably as large as the more familiar effects of ocean surface temperatures and atmospheric internal variability. We conclude that the cool 2011 springtime climate conditions in the northwest US increased the probability of summer drought and abnormal heat in the Southern Plains. The present study suggests a strong potential for more skillful intra-seasonal predictions of US Southern Plains droughts when such facts as ones presented here are considered

Spring Land Surface and Subsurface Temperature Anomalies and Subsequent Downstream Late Spring-Summer Droughts/Floods in North America and East Asia

Sea surface temperature (SST) variability has been shown to have predictive value for land precipitation, although SSTs are unable to fully predict intraseasonal to interannual hydrologic extremes. The possible remote effects of large-scale land surface temperature (LST) and subsurface temperature (SUBT) anomalies in geographical areas upstream and closer to the areas of drought/flood have largely been ignored. Here evidence from climate observations and model simulations addresses these effects. Evaluation of observational data using Maximum Covariance Analysis identifies significant correlations between springtime 2-m air temperature (T2 m) cold (warm) anomalies in both the western U.S. and the Tibetan Plateau and downstream drought (flood) events in late spring/summer. To support these observational findings, climate models are used in sensitivity studies, in which initial LST/SUBT anomaly is imposed to produce observed T2 m anomaly, to demonstrate a causal relationship for two important cases: between spring warm T2 m/LST/SUBT anomalies in western U.S. and the extraordinary 2015 flood in Southern Great Plains and adjacent regions and between spring cold T2 m/LST/SUBT anomalies in the Tibetan Plateau and the severe 2003 drought south of the Yangtze River region. The LST/SUBT downstream effects in North America are associated with a large-scale atmospheric stationary wave extending eastward from the LST/SUBT anomaly region. The effects of SST in these cases are also tested and compared with the LST/SUBT effects. These results suggest that consideration of LST/SUBT anomalies has the potential to add value to intraseasonal prediction of dry and wet conditions, especially extreme drought/flood events. The results suggest the importance of developing land data and models capable of preserving observed soil memory

Spring Land Surface and Subsurface Temperature Anomalies and Subsequent Downstream Late Spring-Summer Droughts/Floods in North America and East Asia

Sea surface temperature (SST) variability has been shown to have predictive value for land precipitation, although SSTs are unable to fully predict intraseasonal to interannual hydrologic extremes. The possible remote effects of large-scale land surface temperature (LST) and subsurface temperature (SUBT) anomalies in geographical areas upstream and closer to the areas of drought/flood have largely been ignored. Here evidence from climate observations and model simulations addresses these effects. Evaluation of observational data using Maximum Covariance Analysis identifies significant correlations between springtime 2-m air temperature (T2 m) cold (warm) anomalies in both the western U.S. and the Tibetan Plateau and downstream drought (flood) events in late spring/summer. To support these observational findings, climate models are used in sensitivity studies, in which initial LST/SUBT anomaly is imposed to produce observed T2 m anomaly, to demonstrate a causal relationship for two important cases: between spring warm T2 m/LST/SUBT anomalies in western U.S. and the extraordinary 2015 flood in Southern Great Plains and adjacent regions and between spring cold T2 m/LST/SUBT anomalies in the Tibetan Plateau and the severe 2003 drought south of the Yangtze River region. The LST/SUBT downstream effects in North America are associated with a large-scale atmospheric stationary wave extending eastward from the LST/SUBT anomaly region. The effects of SST in these cases are also tested and compared with the LST/SUBT effects. These results suggest that consideration of LST/SUBT anomalies has the potential to add value to intraseasonal prediction of dry and wet conditions, especially extreme drought/flood events. The results suggest the importance of developing land data and models capable of preserving observed soil memory

Radiative forcing by light-absorbing particles in snow

As one of the brightest natural surfaces on Earth, the darkening of snow by light-absorbing particles (LAPs) — dust, black carbon or microbial growth — can trigger albedo feedbacks and accelerate snowmelt. Indeed, an increase in black carbon deposition following the industrial revolution has led to the recognition that LAP radiative forcing has contributed to a reduction in the global cryosphere, with corresponding climatic impacts. This Review synthesizes our current understanding of the distribution of radiative forcing by LAPs in snow, and discusses the challenges that need to be overcome to constrain global impacts, including the limited scope of local-scale observations, limitations of remote sensing technology and the representation of LAP-related processes in Earth system models