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Shinjiro Kanae, Taikan Oki, and Katumi Musiake

. Thailand, a major part of the Indochina Peninsula, was highly forested in the past, but is not currently highly forested. Some studies have examined a trend in precipitation (or OLR) over the Indochina Peninsula. Chu and Wang (1997) examined OLR over 22.5°N–22.5°S and 40°E–180° from 1974 to 1992. They found an increase in convection during the boreal summer (from April to September) from the Arabian Sea across Southeast Asia to the northwest Pacific. Watanabe and Shinoda (1996) analyzed the trend

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John E. Strack, Roger A. Pielke Sr., and Jimmy Adegoke

rate, and boundary layer structure to the land-cover representation used. A control simulation was first performed using the best representation of the current landscape. The results of this control were verified against observations from ground stations and the SSBLIM aircraft. Three additional simulations, each with a different land-cover representation, were then run and the results compared with the control run. In simulation 2 the AVHRR-derived land cover was used with the Olson grass

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H. Richter, A. W. Western, and F. H. S. Chiew

1. Introduction Atmospheric numerical models from the short-term (hours) high-resolution storm-scale model up to the long-term (decades) climate model require information on the water and energy fluxes from the land surface as a lower boundary condition. Soil moisture, defined as the volumetric soil water content in this study, in combination with soil and vegetation characteristics, plays an important role in this exchange of water and energy between the land surface and the atmospheric

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Kaniska Mallick, Andrew Jarvis, Joshua B. Fisher, Kevin P. Tu, Eva Boegh, and Dev Niyogi

identified as an essential climate variable. Some recent studies have demonstrated significant disagreement among climate models, attributed mainly to the differences in the LSMs associated with them, and λE has been identified as one of the important land surface process variables where major attention is needed ( Pitman 2003 ). To date, the methods for estimating λ E and its internal state variables (canopy conductance g S and boundary layer conductance g B ) have been largely based on

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Joseph A. Santanello Jr., Patricia Lawston, Sujay Kumar, and Eli Dennis

1. Introduction The role of the land surface in numerical weather prediction (NWP) has been traditionally overlooked by the atmospheric modeling community ( Santanello et al. 2018 ), who often employ primitive initialization approaches for soil moisture and temperature based on coarse atmospheric model products. These surface conditions have been treated simply as lower boundary conditions, with early LSM development driven by the atmospheric communities and little emphasis on the accuracy and

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Tetsuzo Yasunari, Kazuyuki Saito, and Kumiko Takata

simulations with different surface boundary conditions were considered in this study. The bare-rock land surface was considered as a nonvegetated surface, and therefore the effects of soil/vegetation were divided into two parts: above the surface and below the surface. Factors above the surface include albedo and roughness length ( Z 0 ). A vegetated surface generally has a lower surface albedo that affects incoming radiation at the surface. Similarly, roughness length directly affects fluxes of momentum

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Kingtse C. Mo and Dennis P. Lettenmaier

for Environmental Prediction (NCEP) and the University of Washington (UW) both routinely produce hydroclimate fields, including soil moisture and runoff, from NLDAS-derivative systems in near–real time with 1–3 days latency that support the U.S. Drought Monitor (USDM; Svoboda et al. 2002 ). Current drought monitoring systems (e.g., the UW and NCEP systems) are able to detect droughts but are challenged by the classification of drought into, for instance, the D0–D4 categories used by the USDM, in

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W. E. Eichinger, H. E. Holder, R. Knight, J. Nichols, D. I. Cooper, L. E. Hipps, W. P. Kustas, and J. H. Prueger

boundary layer is caused by convergence or divergence in the mesoscale flow and is difficult to determine from meteorological measurements. Fortunately, the boundary layer grows into the residual layer from the day before, whose height can be examined to obtain an estimate of the magnitude of the subsidence velocity. Figure 1 contains a plot of a typical lidar return during a convective morning period. The residual layer can be seen extending from the top of the current boundary layer to an altitude

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V. Poitras, L. Sushama, F. Seglenieks, M. N. Khaliq, and E. Soulis

routing scheme that is discussed in the methodology section. An ensemble of ten 30-yr CRCM simulations is analyzed in this paper, of which five correspond to the current climate (1961–90) and the other five are matching pairs of future climate (2041–70), based on the Special Report on Emissions Scenarios (SRES) A2 scenario ( Houghton et al. 2001 ). These five CRCM pairs are driven by five different members of an initial condition ensemble of CGCM3.1 simulations at the lateral boundaries ( Flato and

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Gerrit H. de Rooij

superior performance of the modified Richards equation may be linked to the fact that the current formulation of the fixed-head boundary condition removes the singularity in the soil water characteristic from the simulated section of the soil profile. Averaging water contents and matric heads over vertical intervals in the soil and the groundwater can and should be done in such a way that both mass and potential energy of the water are conserved in the averaging operations. A complete set of equations

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