Search Results

You are looking at 151 - 160 of 27,351 items for :

  • All content x
Clear All
Xiaolei Fu, Lifeng Luo, Ming Pan, Zhongbo Yu, Ying Tang, and Yongjian Ding

1. Introduction Soil moisture is not only an important variable for meteorology, hydrology, and agriculture applications ( Heathman et al. 2003 ), but it is also the key factor in land–atmosphere interactions ( Yu et al. 2014 ), primarily due to its control of water and energy fluxes in land surface ( Daly and Porporato 2005 ; Qin et al. 2009 ; Al-Hamdan and Cruise 2010 ; Li et al. 2010 ). It affects not only the partitioning of energy between sensible and latent heat in the atmosphere

Full access
E. M. Fischer, S. I. Seneviratne, P. L. Vidale, D. Lüthi, and C. Schär

attributed to past human influence on the climate system. Several model studies suggest that events such as the 2003 summer heat wave will become more frequent, more intense, and longer lasting in the future ( S04 ; Beniston 2004 ; Meehl and Tebaldi 2004 ; Vidale et al. 2007 ). Several studies have suggested that the projected changes in summer climate strongly rely on soil moisture–atmosphere interactions ( Seneviratne et al. 2006b ; Rowell 2005 ; Rowell and Jones 2006 ; Vidale et al. 2007 ). Heat

Full access
Guiting Song, Robert Huva, Yu Xing, and Xiaohui Zhong

representation of unresolved cloud processes in WRF. In Australia Prasad and Kay (2020) illustrated the difficulty of the WRF-Solar model to appropriately capture location and timing of clouds under partly cloudy conditions, while in Southern California López-Coto et al. (2013) tested 72 different configurations of the WRF Model and found overestimation of irradiance, in general, with a tendency for underprediction of temperature and moisture through the vertical. To reduce bias, or more broadly error

Restricted access
Yang Lu, Jianzhi Dong, and Susan C. Steele-Dunne

1. Introduction The dynamics of soil moisture and the partitioning of solar radiation at the land surface is key to hydrology ( McCabe and Wood 2006 ), meteorology ( Andrews et al. 2009 ), water resources management ( Yang et al. 2018 ; Rigden and Salvucci 2015 ), and the terrestrial water cycle ( Kumar et al. 2018 ). Soil moisture and surface heat fluxes can be measured with in situ flux networks ( Dorigo et al. 2011 ; Baldocchi et al. 2001 ), but the extrapolation to regional scale is

Full access
Georgy V. Mostovoy and Valentine G. Anantharaj

1. Introduction Soil moisture (SM) is a key variable of the land–atmosphere system, which along with other environmental variables, controls the rate of evaporation from the surface and the partitioning of the moisture and energy fluxes across the land–atmosphere interface. Hence, SM represents an important input for various environmental and hydrometeorological models. For that reason, accurate specification and prediction of the SM fields at different spatial scales (ranging from local to

Full access
Yang Yang, Michael Uddstrom, Mike Revell, Phil Andrews, Hilary Oliver, Richard Turner, and Trevor Carey-Smith

1. Introduction Soil moisture amount and its variation affect land surface sensible and latent heating fluxes. The ratio of heating and moistening of the near-surface atmosphere affects the buoyancy of air parcels that become updrafts within a boundary layer [see Pielke (2001) for a comprehensive review]. In addition, the latent heat (moisture) flux can control the lifting condensation level corresponding to the depth of the subcloud layer. The depth of the mixed boundary layer

Full access
Christopher L. Castro, Adriana B. Beltrán-Przekurat, and Roger A. Pielke Sr.

1. Introduction Land surface parameters considered at the atmosphere–land interface are soil temperature, snow cover, soil moisture, and vegetation. Soil moisture and vegetation are expected to be the dominant land surface effects. Their variability in space and time may affect the exchange of heat and moisture with the atmosphere. The role of the land surface in providing feedback to the atmosphere has been recognized on a wide range of scales, from the local and regional to global (e

Full access
Luca Ciabatta, Luca Brocca, Christian Massari, Tommaso Moramarco, Silvia Puca, Angelo Rinollo, Simone Gabellani, and Wolfgang Wagner

satellite soil moisture SM data were recently developed ( Crow et al. 2009 ; Pellarin et al. 2013 ; Brocca et al. 2013 ). In the first approach, Crow et al. (2009) assimilated Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E; Jackson et al. 2007 ) SM data into an antecedent precipitation index (API) model, in order to correct the 2–10 day rainfall accumulation in a data assimilation framework. In the second approach, Pellarin et al. (2013) coupled an API model with a

Full access
Minoru Chikira

that the MJO can be explained as a moisture mode, which appears from a set of simplified equations and is characterized by the growth of convective activity through the amplification of moisture. The gross moist stability (GMS; Neelin and Held 1987 ), which was originally defined as the export of moist static energy (MSE) out of the column by a unit divergent circulation, becomes an important quantity in determining the stability of the mode. The mode occurs under the weak temperature gradient

Full access
Rich F. Coleman, James F. Drake, Michael D. McAtee, and Leslie O. Belsma

). After the transition to ARW, a similar warm bias was observed in ARW forecasts. It was thought that in both cases, the warm bias could be attributed to insufficient latent heat flux due to the model failing to include moisture resulting from human activities. Research was undertaken to identify and quantify the sources of anthropogenic moisture in southern California, and to develop a method of incorporating these moisture sources into the WRF modeling system. As precipitation falls through the

Full access