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Wayne Higgins and David Gochis

Abstract

An international team of scientists from the United States, Mexico, and Central America carried out a major field campaign during the summer of 2004 to develop an improved understanding of the North American monsoon system leading to improved precipitation forecasts. Results from this campaign, which is the centerpiece of the North American Monsoon Experiment (NAME) Process Study, are reported in this issue of the Journal of Climate. In addition to a synthesis of key findings, this brief overview article also raises some important unresolved issues that require further attention. More detailed background information on NAME, including motivating science questions, where NAME 2004 was conducted, when, and the experimental design, was published previously by Higgins et al.

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Sergey Y. Matrosov, Robert Cifelli, and David Gochis

Abstract

The utility of X-band polarimetric radar to provide rainfall estimations with high spatial and temporal resolution in heavy convective precipitation in the presence of hail is explored. A case study involving observations of strong convective cells with a transportable polarimetric X-band radar near Boulder, Colorado, is presented. These cells produced rain–hail mixtures with a significant liquid fraction, causing local flash floods and debris flow in an environmentally sensitive burn area that had been previously affected by wildfire. It is demonstrated that the specific differential phase shift (K DP)–based rainfall estimator provided liquid accumulations that were in relatively good agreement with a network of high-density rain gauges and experimental disdrometers. This estimator was also able to capture the significant variability of accumulated rainfall in a relatively small area of interest, and the corresponding results were not significantly affected by hail. Hail presence, however, was a likely reason for significant overestimation of rainfall retrievals for X-band radar approaches that are based on radar-reflectivity Ze measurements that have been corrected for attenuation in rain. Even greater overestimations were observed with the S-band radar of the weather-service network. In part because of larger range distances, these radar data could not correctly reproduce the spatial variability of rainfall in the burn area.

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Wei Yu, Weiqing Han, and David Gochis

Abstract

Atmospheric intraseasonal variability in the tropical Atlantic is analyzed using satellite winds, outgoing longwave radiation (OLR), and reanalysis products during 2000–08. The analyses focus on assessing the effects of dominant intraseasonal atmospheric convective processes, the Madden–Julian oscillation (MJO), and Rossby waves on surface wind and convection of the tropical Atlantic Ocean and African monsoon area. The results show that contribution from each process varies in different regions. In general, the MJO events dominate the westward-propagating Rossby waves in affecting strong convection in the African monsoon region. The Rossby waves, however, have larger contributions to convection in the western Atlantic Ocean. Both the westward- and eastward-propagating signals contribute approximately equally in the central Atlantic basin. The effects of intraseasonal signals have evident seasonality. Both convection amplitude and the number of strong convective events associated with the MJO are larger during November–April than during May–October in all regions. Convection associated with Rossby wave events is stronger during November–April for all regions, and the numbers of Rossby wave events are higher during November–April than during May–October in the African monsoon region, and are comparable for the two seasons in the western and central Atlantic basins. Of particular interest is that the MJOs originating from the Indo-Pacific Ocean can be enhanced over the tropical Atlantic Ocean while they propagate eastward, amplifying their impacts on the African monsoon. On the other hand, Rossby waves can originate either in the eastern equatorial Atlantic or West African monsoon region, and some can strengthen while they propagate westward, affecting surface winds and convection in the western Atlantic and Central American regions.

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James M. Gilbert, Reed M. Maxwell, and David J. Gochis

Abstract

The boundary layer, land surface, and subsurface are important coevolving components of hydrologic systems. While previous studies have examined the connections between soil moisture, groundwater, and the atmosphere, the atmospheric response to regional water-table drawdown has received less attention. To address this question, a coupled hydrologic–atmospheric model [Parallel Flow hydrologic model (ParFlow) and WRF] was used to simulate the San Joaquin River watershed of central California. This study focuses specifically on the planetary boundary layer (PBL) in simulations with two imposed water-table configurations: a high water table mimicking natural conditions and a lowered water table reflecting historic groundwater extraction in California’s Central Valley, although effect of irrigation was not simulated. An ensemble of simulations including three boundary layer schemes and six initial conditions was performed for both water-table conditions to assess conceptual and initial condition uncertainty. Results show that increased regional water-table depth is associated with a significant increase in peak PBL height for both initial condition and boundary layer scheme conditions, although the choice of scheme interacts to affect the magnitude of peak PBL height change. Analysis of simulated land surface fluxes shows the change in PBL height can be attributed to decreasing midday evaporative fraction under lowered water-table conditions. Furthermore, the sensitivity of PBL height to changes in water-table depth appears to depend on local water-table variation within 10 m of the land surface and the regional average water-table depth. Finally, soil moisture changes associated with lowered water tables are linked to changes in PBL circulation as indicated by vertical winds and turbulence kinetic energy.

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David J. Gochis, W. James Shuttleworth, and Zong-Liang Yang

Abstract

This paper describes the second part of a study to document the sensitivity of the modeled regional moisture flux patterns and hydrometeorological response of the North American monsoon system (NAMS) to convective parameterization. Use of the convective parameterization schemes of Betts–Miller–Janjic, Kain–Fritsch, and Grell was investigated during the initial phase of the 1999 NAMS using version 3.4 of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) running in a pseudoclimate mode. Substantial differences in both the stationary and transient components of the moisture flux fields were found between the simulations, resulting in differences in moisture convergence patterns, precipitation, and surface evapotranspiration. Basin-average calculations of hydrologic variables indicate that, in most of the basins for which calculations were made, the magnitude of the evaporation-minus-precipitation moisture source/sink differs substantially between simulations and, in some cases, even the sign of the source/sink changed. There are substantial differences in rainfall–runoff processes because the basin-average rainfall intensities, proportion of rainfall from convective origin, and the runoff coefficients differ between simulations. The results indicate that, in regions of sustained, deep convection, the selection of the subgrid convective parameterization in a high-resolution atmospheric model can potentially have a hydrometeorological impact in regional analyses, which is at least as important as the effect of land surface forcing.

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Huancui Hu, Francina Dominguez, Praveen Kumar, Jeffery McDonnell, and David Gochis

Abstract

We develop and implement a novel numerical water tracer model within the Noah LSM with multiparameterization options (WT-Noah-MP) that is specifically designed to track individual hydrometeorological events. This approach provides a more complete representation of the physical processes beyond the standard land surface model output. Unlike isotope-enabled LSMs, WT-Noah-MP does not simulate the concentration of oxygen or hydrogen isotopes, or require isotope information to drive it. WT-Noah-MP provides stores, fluxes, and transit time estimates of tagged water in the surface–subsurface system. The new tracer tool can account for the horizontal and vertical heterogeneity of tracer transport in the subsurface by allowing partial mixing in each soil layer. We compared model-estimated transit times at the H. J. Andrews Experimental Watershed in Oregon with those derived from isotope observations. Our results show that including partial mixing in the soil results in a more realistic transit time distribution than the basic well-mixed assumption. We then used WT-Noah-MP to investigate the regional response to an extreme precipitation event in the U.S. Pacific Northwest. The model differentiated the flood response due to direct precipitation from indirect thermal effects and showed that a large portion of this event water was retained in the soil after 6 months. The water tracer addition in Noah-MP can help us quantify the long-term memory in the hydrologic system that can impact seasonal hydroclimate variability through evapotranspiration and groundwater recharge.

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Enrique R. Vivoni, Kinwai Tai, and David J. Gochis

Abstract

Through the use of a mesoscale meteorological model and distributed hydrologic model, the effects of initial soil moisture on rainfall generation, streamflow, and evapotranspiration during the North American monsoon are examined. A collection of atmospheric fields is simulated by varying initial soil moisture in the meteorological model. Analysis of the simulated rainfall fields shows that the total rainfall, intensity, and spatial coverage increase with higher soil moisture. Hydrologic simulations forced by the meteorological fields are performed using two scenarios: (i) fixed soil moisture initializations obtained via a drainage experiment in the hydrologic model and (ii) adjusted initializations to match conditions in the two models. The scenarios indicate that the runoff ratio increases with higher rainfall, although a change is observed from a linear (fixed initialization) to a nonlinear response (adjusted initialization). Variations in basin response are attributed to controls exerted by rainfall, soil, and vegetation properties for varying initial conditions. Antecedent wetness significantly influences the runoff response through the interplay of different runoff generation mechanisms and also controls the evapotranspiration process. The authors conclude that a regional increase in initial soil moisture promotes rainfall generation, streamflow, and evapotranspiration for this warm-season case study.

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David J. Gochis, W. James Shuttleworth, and Zong-Liang Yang

Abstract

This paper documents the sensitivity of the modeled evolution of the North American monsoon system (NAMS) to convective parameterization in terms of thermodynamic and circulation characteristics, stability profiles, and precipitation. The convective parameterization schemes (CPSs) of Betts–Miller–Janjic, Kain–Fritsch, and Grell were tested using version 3.4 of the PSU–NCAR fifth-generation Mesoscale Model (MM5) running in a pseudoclimate mode. Model results for the initial phase of the 1999 NAM are compared with surface climate station observations and seven radiosonde sites in Mexico and the southwestern United States. The results show substantial differences in modeled precipitation, surface climate, and atmospheric stability occuring between the different model simulations, which are attributable to the representation of convection in the model. Moreover, large intersimulation differences in the low-level circulation fields are found. While none of the CPSs tested gave perfect simulation of observations everywhere in the model domain, the Kain–Fritsch scheme generally gave significantly superior estimates of surface and upper air verification error statistics.

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Melissa S. Bukovsky, David J. Gochis, and Linda O. Mearns

Abstract

The authors examine 17 dynamically downscaled simulations produced as part of the North American Regional Climate Change Assessment Program (NARCCAP) for their skill in reproducing the North American monsoon system. The focus is on precipitation and the drivers behind the precipitation biases seen in the simulations of the current climate. Thus, a process-based approach to the question of model fidelity is taken in order to help assess confidence in this suite of simulations.

The results show that the regional climate models (RCMs) forced with a reanalysis product and atmosphere-only global climate model (AGCM) time-slice simulations perform reasonably well over the core Mexican and southwest United States regions. Some of the dynamically downscaled simulations do, however, have strong dry biases in Arizona that are related to their inability to develop credible monsoon flow structure over the Gulf of California. When forced with different atmosphere–ocean coupled global climate models (AOGCMs) for the current period, the skill of the RCMs subdivides largely by the skill of the forcing or “parent” AOGCM. How the inherited biases affect the RCM simulations is investigated. While it is clear that the AOGCMs have a large influence on the RCMs, the authors also demonstrate where the regional models add value to the simulations and discuss the differential credibility of the six RCMs (17 total simulations), two AGCM time slices, and four AOGCMs examined herein. It is found that in-depth analysis of parent GCM and RCM scenarios can identify a meaningful subset of models that can produce credible simulations of the North American monsoon precipitation.

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Stephen W. Nesbitt, David J. Gochis, and Timothy J. Lang

Abstract

This study examines the spatial and temporal variability in the diurnal cycle of clouds and precipitation tied to topography within the North American Monsoon Experiment (NAME) tier-I domain during the 2004 NAME enhanced observing period (EOP, July–August), with a focus on the implications for high-resolution precipitation estimation within the core of the monsoon. Ground-based precipitation retrievals from the NAME Event Rain Gauge Network (NERN) and Colorado State University–National Center for Atmospheric Research (CSU–NCAR) version 2 radar composites over the southern NAME tier-I domain are compared with satellite rainfall estimates from the NOAA Climate Prediction Center Morphing technique (CMORPH) and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) operational and Tropical Rainfall Measuring Mission (TRMM) 3B42 research satellite estimates along the western slopes of the Sierra Madre Occidental (SMO). The rainfall estimates are examined alongside hourly images of high-resolution Geostationary Operational Environmental Satellite (GOES) 11-μm brightness temperatures.

An abrupt shallow to deep convective transition is found over the SMO, with the development of shallow convective systems just before noon on average over the SMO high peaks, with deep convection not developing until after 1500 local time on the SMO western slopes. This transition is shown to be contemporaneous with a relative underestimation (overestimation) of precipitation during the period of shallow (deep) convection from both IR and microwave precipitation algorithms due to changes in the depth and vigor of shallow clouds and mixed-phase cloud depths. This characteristic life cycle in cloud structure and microphysics has important implications for ice-scattering microwave and infrared precipitation estimates, and thus hydrological applications using high-resolution precipitation data, as well as the study of the dynamics of convective systems in complex terrain.

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