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Planton 1989 ), which characterize the state of the land surface and forecast the evolution of the lowest layer of the model atmosphere. The surface energy balance relies strongly upon the soil and near-surface conditions and plays a critical role in determining the prognostic variables in land surface models. Vegetation coverage, atmospheric conditions, and the physical properties of the soil impact surface energy fluxes, which both influence and depend heavily upon soil temperature and soil moisture
Planton 1989 ), which characterize the state of the land surface and forecast the evolution of the lowest layer of the model atmosphere. The surface energy balance relies strongly upon the soil and near-surface conditions and plays a critical role in determining the prognostic variables in land surface models. Vegetation coverage, atmospheric conditions, and the physical properties of the soil impact surface energy fluxes, which both influence and depend heavily upon soil temperature and soil moisture
). In such regimes, a high atmospheric demand for evapotranspiration is facing a small soil water supply. An inaccurately estimated critical threshold of the available soil water amount for evapotranspiration can consequently lead to a considerable over or underestimation of the evapotranspiration rates and thus, to biases in the near-surface temperatures. A well-known example for such an incorrect model behavior is the consistently simulated warm bias in summer in southern Europe in different model
). In such regimes, a high atmospheric demand for evapotranspiration is facing a small soil water supply. An inaccurately estimated critical threshold of the available soil water amount for evapotranspiration can consequently lead to a considerable over or underestimation of the evapotranspiration rates and thus, to biases in the near-surface temperatures. A well-known example for such an incorrect model behavior is the consistently simulated warm bias in summer in southern Europe in different model
1. Introduction The land surface components of meteorology modeling systems are responsible for the realistic representation of surface heat and moisture exchange processes and their dependence on vegetation and soil temperature and moisture. The surface fluxes of heat and moisture drive the near-surface air temperature and humidity and the evolution of the planetary boundary layer (PBL). The diurnal evolution of the PBL is of particular importance to air quality modeling applications. Thus
1. Introduction The land surface components of meteorology modeling systems are responsible for the realistic representation of surface heat and moisture exchange processes and their dependence on vegetation and soil temperature and moisture. The surface fluxes of heat and moisture drive the near-surface air temperature and humidity and the evolution of the planetary boundary layer (PBL). The diurnal evolution of the PBL is of particular importance to air quality modeling applications. Thus
2080–99 for eastern North America ( Solomon et al. 2007 ). For the southern Quebec region, an ensemble of simulations project a warming between 3° and 5°C for 2080–99 and an increase in precipitation, mostly during winter and spring, between 5% and 17% ( Logan et al. 2011 ; DesJarlais et al. 2010 ). Projected changes are likely to affect soil moisture and temperature conditions, variables that have important impacts on many important processes such as seed germination and fine root development of
2080–99 for eastern North America ( Solomon et al. 2007 ). For the southern Quebec region, an ensemble of simulations project a warming between 3° and 5°C for 2080–99 and an increase in precipitation, mostly during winter and spring, between 5% and 17% ( Logan et al. 2011 ; DesJarlais et al. 2010 ). Projected changes are likely to affect soil moisture and temperature conditions, variables that have important impacts on many important processes such as seed germination and fine root development of
investigating the impact of land–atmosphere interactions on the distribution of daily surface temperature at the global scale with a focus on the role of soil moisture–atmosphere feedbacks. Soil moisture is a key variable in land–atmosphere interactions: the variations of soil moisture in response to atmospheric conditions (precipitation, radiation, and evaporative demand) impact surface turbulent and radiative heat fluxes, thereby potentially feeding back on atmospheric conditions. For example, low
investigating the impact of land–atmosphere interactions on the distribution of daily surface temperature at the global scale with a focus on the role of soil moisture–atmosphere feedbacks. Soil moisture is a key variable in land–atmosphere interactions: the variations of soil moisture in response to atmospheric conditions (precipitation, radiation, and evaporative demand) impact surface turbulent and radiative heat fluxes, thereby potentially feeding back on atmospheric conditions. For example, low
, for a workshop on the system design for a USCRN soil-climate–monitoring network (at the time of writing, a report from the workshop could be found online at the NIDIS U.S. Drought Portal at http://www.drought.gov/workshops/crn/USCRN_SMST_workshop_summary.pdf ). These discussions provided important input for the final decisions made by the USCRN program. The workshop members suggested the use of an instrument capable of measuring both soil moisture and temperature simultaneously, based on existing
, for a workshop on the system design for a USCRN soil-climate–monitoring network (at the time of writing, a report from the workshop could be found online at the NIDIS U.S. Drought Portal at http://www.drought.gov/workshops/crn/USCRN_SMST_workshop_summary.pdf ). These discussions provided important input for the final decisions made by the USCRN program. The workshop members suggested the use of an instrument capable of measuring both soil moisture and temperature simultaneously, based on existing
air temperature (SAT; precise definitions of common terms in appendix A , section a ) changes as the primary driver of soil temperature increases. However, other factors can be at least as important in determining soil temperature and active layer thickness (ALT; appendix A , section a ): the seasonally asymmetric presence of snow insulation (the snow thermal rectifier) is a major control on soil temperature ( Goodrich 1982 ; Zhang 2005 ). Many studies have shown the potential for changes in
air temperature (SAT; precise definitions of common terms in appendix A , section a ) changes as the primary driver of soil temperature increases. However, other factors can be at least as important in determining soil temperature and active layer thickness (ALT; appendix A , section a ): the seasonally asymmetric presence of snow insulation (the snow thermal rectifier) is a major control on soil temperature ( Goodrich 1982 ; Zhang 2005 ). Many studies have shown the potential for changes in
and spatial resolution, and it appears a necessary development for global mesoscale NWP ( Viterbo and Courtier 1995 ; Koster et al. 2004 ; Ferranti and Viterbo 2006 ). In this paper, the development of a Canadian Land Data Assimilation System (CaLDAS) prototype for the land surface analysis in the NWP context at the Meteorological Service of Canada (MSC) is presented. The focus is put on soil moisture and temperature as principal components driving the water (e.g., through evapotranspiration
and spatial resolution, and it appears a necessary development for global mesoscale NWP ( Viterbo and Courtier 1995 ; Koster et al. 2004 ; Ferranti and Viterbo 2006 ). In this paper, the development of a Canadian Land Data Assimilation System (CaLDAS) prototype for the land surface analysis in the NWP context at the Meteorological Service of Canada (MSC) is presented. The focus is put on soil moisture and temperature as principal components driving the water (e.g., through evapotranspiration
configuration, Heusinkveld et al. (2004) were able to measure the soil heat flux in the Negev Desert. In general, values of the thermal properties of the soil differ from thermal properties of heat flux plates that are used at measurement sites. In those situations, G 0 is inferred from a combination of heat flux plates that are placed at depths that are deeper than a few centimeters and one or more soil temperature sensors. The estimation of G 0 involves an extrapolation toward the surface, for which
configuration, Heusinkveld et al. (2004) were able to measure the soil heat flux in the Negev Desert. In general, values of the thermal properties of the soil differ from thermal properties of heat flux plates that are used at measurement sites. In those situations, G 0 is inferred from a combination of heat flux plates that are placed at depths that are deeper than a few centimeters and one or more soil temperature sensors. The estimation of G 0 involves an extrapolation toward the surface, for which
1. Introduction Soil temperature (ST) represents land surface energy status and heat storage, and it is a key state variable in land–atmosphere interaction. ST affects monthly to interannual climate variations by changing water and heat fluxes between land surface and atmosphere ( Hu and Feng 2004a , b ; Mahanama et al. 2008 ; Wu and Zhang 2014 ). ST facilitates convective development ( Liu and Avissar 1999 ; Xue et al. 2018 ), leading to changes in locations and intensities of
1. Introduction Soil temperature (ST) represents land surface energy status and heat storage, and it is a key state variable in land–atmosphere interaction. ST affects monthly to interannual climate variations by changing water and heat fluxes between land surface and atmosphere ( Hu and Feng 2004a , b ; Mahanama et al. 2008 ; Wu and Zhang 2014 ). ST facilitates convective development ( Liu and Avissar 1999 ; Xue et al. 2018 ), leading to changes in locations and intensities of
