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David M. Lawrence and Julia M. Slingo

with enhanced surface evaporation into rainfall (the “direct” feedback). Instead, the indirect feedback, which some studies suggest is the dominant feedback (e.g., Schär et al. 1999 ), considers how soil moisture affects precipitation through its influence on boundary layer characteristics and atmospheric stability. The indirect feedback mechanism, illustrated in schematic form in Fig. 1 , works in the following way. Anomalously wet soil generated by a significant rainfall event induces a strong

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M. J. Best, A. Beljaars, J. Polcher, and P. Viterbo

surface schemes within the same GCM. This will allow the attribution of differences in the model as a whole to differences in land surface schemes. We therefore need to design a consistent “plug compatible” structure for the interface between these land surface schemes and the boundary layer schemes. The interface needs not only to cover all the physical processes that are currently treated at the interface, but it should also be compatible with all existing numerical schemes. There are several ways

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George J. Huffman, Robert F. Adler, Mark M. Morrissey, David T. Bolvin, Scott Curtis, Robert Joyce, Brad McGavock, and Joel Susskind

estimates, mostly resulting from geo-IR. In the current release, the 3-hourly images in each day (0000 UTC, . . . , 2100 UTC) are summed to produce the daily value. The daily product is considered more reliable than individual 3-hourly images for two reasons. First, GPI-type IR estimates show better correlation with precipitation as the averaging period increases ( Arkin and Meisner 1987 ). Second, the current procedure does not take into account the time of day (i.e., diurnal cycle biases). As a result

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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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