Search Results
1. Introduction Atmospheric aerosols, ozone, water vapor, and NO 2 all play important roles in global radiative and atmospheric chemical processes. Natural activities, for example, major volcanic eruptions, can inject gaseous sulfur dioxide, dust, and other chemicals into the upper atmosphere and therefore affect the radiative forcing of the climate system. Human activities also perturb the balance of atmospheric aerosols and trace gases. Since 1984, the Stratospheric Aerosol and Gas
1. Introduction Atmospheric aerosols, ozone, water vapor, and NO 2 all play important roles in global radiative and atmospheric chemical processes. Natural activities, for example, major volcanic eruptions, can inject gaseous sulfur dioxide, dust, and other chemicals into the upper atmosphere and therefore affect the radiative forcing of the climate system. Human activities also perturb the balance of atmospheric aerosols and trace gases. Since 1984, the Stratospheric Aerosol and Gas
) have been shown to be sensitive to seasonal variation in rainfall and soil water content (Vourlitis et al. 2001; Vourlitis et al. 2002 ; Vourlitis et al. 2004 ; Priante et al. 2004 ). Data collected over the last 4 yr indicates that diel (24 h) trends in NEE and E were primarily driven by variation in radiation and, to a lesser extent, vapor pressure deficit, and temperature; however, meteorological limitations to E and/or NEE may be more severe during the dry season. For example, declines
) have been shown to be sensitive to seasonal variation in rainfall and soil water content (Vourlitis et al. 2001; Vourlitis et al. 2002 ; Vourlitis et al. 2004 ; Priante et al. 2004 ). Data collected over the last 4 yr indicates that diel (24 h) trends in NEE and E were primarily driven by variation in radiation and, to a lesser extent, vapor pressure deficit, and temperature; however, meteorological limitations to E and/or NEE may be more severe during the dry season. For example, declines
available datasets ( section 2.3 ) to judge the impact of climate on the simulated water budgets. PET is estimated using the Hamon method [ Hamon 1963 ; Equation (A1) in appendix A ], the surface-dependent Penman–Monteith method [PM; Monteith 1965 ; Equation (A2) in appendix A ], and the PM method with adjusted vapor pressure data, described in section 2.4 . Details of the simulations to produce the nine scenarios and the comparisons with observed evapotranspiration (ET) and runoff are described
available datasets ( section 2.3 ) to judge the impact of climate on the simulated water budgets. PET is estimated using the Hamon method [ Hamon 1963 ; Equation (A1) in appendix A ], the surface-dependent Penman–Monteith method [PM; Monteith 1965 ; Equation (A2) in appendix A ], and the PM method with adjusted vapor pressure data, described in section 2.4 . Details of the simulations to produce the nine scenarios and the comparisons with observed evapotranspiration (ET) and runoff are described
. 2004 ). Orographic precipitation is formed when air masses interact with the Qilian Mountains ( Roe 2005 ). Gao et al. ( Gao et al. 2004 ) and Chu et al. ( Chu et al. 2005 ) show by model simulation that local circulation driven by daytime thermal heterogeneity between oasis and surrounding deserts [oasis breeze circulation (OBC)] is responsible for conserving water vapor and lowering evapotranspiration (ET) in the oases. They demonstrate that the downdraft associated with the OBC reinforces
. 2004 ). Orographic precipitation is formed when air masses interact with the Qilian Mountains ( Roe 2005 ). Gao et al. ( Gao et al. 2004 ) and Chu et al. ( Chu et al. 2005 ) show by model simulation that local circulation driven by daytime thermal heterogeneity between oasis and surrounding deserts [oasis breeze circulation (OBC)] is responsible for conserving water vapor and lowering evapotranspiration (ET) in the oases. They demonstrate that the downdraft associated with the OBC reinforces
WC of the soil to change; it can also cause the water vapor concentration within the air contained in the pore spaces of the soil to fluctuate ( Li et al. 2014 ). Water vapor fluctuations are bound to cause fluctuations in the vapor pressure. However, whether it can cause Earth–air pressure (EP) to fluctuate has not been reported. This heterothermozone exists as a continuum with the outside atmosphere, and it is generally thought that the air pressure in the soil of this zone is controlled by the
WC of the soil to change; it can also cause the water vapor concentration within the air contained in the pore spaces of the soil to fluctuate ( Li et al. 2014 ). Water vapor fluctuations are bound to cause fluctuations in the vapor pressure. However, whether it can cause Earth–air pressure (EP) to fluctuate has not been reported. This heterothermozone exists as a continuum with the outside atmosphere, and it is generally thought that the air pressure in the soil of this zone is controlled by the
evaporation and vapor flux convergence) was decomposed into its mean and transient parts, completely describing the variance of any budget component through its normalized covariance with the other components. For example, the variance of precipitation may be described through where P is precipitation, E is evaporation, T is the precipitable water tendency, C is the vertically integrated vapor flux convergence, and P ′ indicates the transient component of P on a given time scale. RR2008
evaporation and vapor flux convergence) was decomposed into its mean and transient parts, completely describing the variance of any budget component through its normalized covariance with the other components. For example, the variance of precipitation may be described through where P is precipitation, E is evaporation, T is the precipitable water tendency, C is the vertically integrated vapor flux convergence, and P ′ indicates the transient component of P on a given time scale. RR2008
sonic anemometer (Gill Instruments Ltd., United Kingdom) and water vapor flux was measured with a krypton hygrometer (model KH 2 O, Campbell Scientific, United Kingdom). A detailed description of the set up and operation of the device is given by Elbers ( Elbers 2002 ). Half-hourly average EC data were analyzed and made available by Burose et al. ( Burose et al. 2004 , manuscript submitted to Bound.-Layer Meteor. ). Eddy correlation measurements covered the period between 9 November 2002 and 28
sonic anemometer (Gill Instruments Ltd., United Kingdom) and water vapor flux was measured with a krypton hygrometer (model KH 2 O, Campbell Scientific, United Kingdom). A detailed description of the set up and operation of the device is given by Elbers ( Elbers 2002 ). Half-hourly average EC data were analyzed and made available by Burose et al. ( Burose et al. 2004 , manuscript submitted to Bound.-Layer Meteor. ). Eddy correlation measurements covered the period between 9 November 2002 and 28
were not analyzed in this study. While the atmospheric input data for the top and lateral boundaries prescribed to the model (see section 2.6 .) were identical for all simulations, the physical properties of the soil and the surface were adjusted to represent the particular land use of each simulation. Additionally, all simulations were initialized with the same vertical profile of virtual potential air temperature, horizontal wind speed, and water vapor mixing ratio as well as identical ground
were not analyzed in this study. While the atmospheric input data for the top and lateral boundaries prescribed to the model (see section 2.6 .) were identical for all simulations, the physical properties of the soil and the surface were adjusted to represent the particular land use of each simulation. Additionally, all simulations were initialized with the same vertical profile of virtual potential air temperature, horizontal wind speed, and water vapor mixing ratio as well as identical ground
concentrations are occurring, including surface (snow and sea ice) albedo, clouds, water vapor/lapse rate, and radiative cooling (e.g., Bony et al. 2006 ). To show the response of surface albedo, we calculated changes in Northern Hemisphere extratropical springtime surface albedo, modulated by the dependence of planetary albedo on surface albedo and multiplied by solar insolation (as in Qu and Hall 2006 ), and plotted it as a function of global mean surface temperature ( Figure 2a ). Overall, there is a
concentrations are occurring, including surface (snow and sea ice) albedo, clouds, water vapor/lapse rate, and radiative cooling (e.g., Bony et al. 2006 ). To show the response of surface albedo, we calculated changes in Northern Hemisphere extratropical springtime surface albedo, modulated by the dependence of planetary albedo on surface albedo and multiplied by solar insolation (as in Qu and Hall 2006 ), and plotted it as a function of global mean surface temperature ( Figure 2a ). Overall, there is a
simulation of regional hydrology was sensitive to precipitation and water vapor differences among the driving datasets and that accurate simulation of regional water balance is limited by biases in the forcing data. Satellite-based analyses for the region indicate that vegetation productivity of the region increased during the last two decades of the twentieth century because of earlier spring thaw, and the temporal variability of vegetation productivity simulated by the models from 1980 to 2000 was
simulation of regional hydrology was sensitive to precipitation and water vapor differences among the driving datasets and that accurate simulation of regional water balance is limited by biases in the forcing data. Satellite-based analyses for the region indicate that vegetation productivity of the region increased during the last two decades of the twentieth century because of earlier spring thaw, and the temporal variability of vegetation productivity simulated by the models from 1980 to 2000 was
