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Guo-Yue Niu and Zong-Liang Yang

Abstract

The presence of ice in soil dramatically alters soil hydrologic and thermal properties. Despite this important role, many recent studies show that explicitly including the hydrologic effects of soil ice in land surface models degrades the simulation of runoff in cold regions. This paper addresses this dilemma by employing the Community Land Model version 2.0 (CLM2.0) developed at the National Center for Atmospheric Research (NCAR) and a simple TOPMODEL-based runoff scheme (SIMTOP). CLM2.0/SIMTOP explicitly computes soil ice content and its modifications to soil hydrologic and thermal properties. However, the frozen soil scheme has a tendency to produce a completely frozen soil (100% ice content) whenever the soil temperature is below 0°C. The frozen ground prevents infiltration of snowmelt or rainfall, thereby resulting in earlier- and higher-than-observed springtime runoff. This paper presents modifications to the above-mentioned frozen soil scheme that produce more accurate magnitude and seasonality of runoff and soil water storage. These modifications include 1) allowing liquid water to coexist with ice in the soil over a wide range of temperatures below 0°C by using the freezing-point depression equation, 2) computing the vertical water fluxes by introducing the concept of a fractional permeable area, which partitions the model grid into an impermeable part (no vertical water flow) and a permeable part, and 3) using the total soil moisture (liquid water and ice) to calculate the soil matric potential and hydraulic conductivity. The performance of CLM2.0/SIMTOP with these changes has been tested using observed data in cold-region river basins of various spatial scales. Compared to the CLM2.0/SIMTOP frozen soil scheme, the modified scheme produces monthly runoff that compares more favorably with that estimated by the University of New Hampshire–Global Runoff Data Center and a terrestrial water storage change that is in closer agreement with that measured by the Gravity Recovery and Climate Experiment (GRACE) satellites.

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Xiangbo Feng, Nicholas Klingaman, Shaoqing Zhang, and Liang Guo
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Jing Zhang, Xinyu Guo, Liang Zhao, Yasumasa Miyazawa, and Qun Sun

Abstract

Onshore and offshore currents and the associated volume transport across three isobaths (50, 100, and 200 m) over the continental shelf of the East China Sea were examined using daily reanalysis data in 1993–2012. After being averaged along the isobaths, the velocities across 100 and 50 m are onshore in the bottom layer but offshore in the surface layer. In contrast, those across the 200-m isobath are onshore in the surface and bottom layers but without a clear direction in the midlayer, suggesting a three-layer structure. The surface offshore current across the 100-m isobath mainly arises from the Taiwan Strait Current, while the surface onshore current across the 200-m isobath mainly arises from the Kuroshio, both of which converge in the area between the 100- and 200-m isobaths and flow toward the Tsushima Strait. The control of bottom Ekman dynamics on the onshore bottom currents is important at the 100-m isobath, partly important at the 200-m isobath, and slightly important at the 50-m isobath. The seasonal variations of onshore and offshore currents in the surface layers across the three isobaths are likely caused by local winds, the Taiwan Strait Current, and the Changjiang discharge, while those in midlayer across the 200-m isobath demonstrate a strong geostrophic control and can be interpreted from a traditional viewpoint on the Kuroshio intrusion over the entire water column across the shelf slope. The close connection of bottom onshore currents across the three isobaths suggests that the bottom layer is an important pathway for water exchange of shelf water and the open sea.

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Liang Guo, Andrew G. Turner, and Eleanor J. Highwood

Abstract

The HadGEM2 AGCM is used to determine the most important anthropogenic aerosols in the Indian monsoon using experiments in which observed trends in individual aerosol species are imposed. Sulfur dioxide (SD) emissions are shown to impact rainfall more strongly than black carbon (BC) aerosols, causing reduced rainfall especially over northern India. Significant perturbations due to BC are not noted until its emissions are scaled up in a sensitivity test, resulting in rainfall increases over northern India due to the elevated heat pump mechanism, enhancing convection during the premonsoon, and bringing forward the monsoon onset. Second, the impact of anthropogenic aerosols is compared to that of increasing greenhouse-gas concentrations and observed sea surface temperature (SST) warming. The tropospheric temperature gradient driving the monsoon shows weakening when forced by either SD or imposed SST trends. However, the observed SST trend is dominated by warming in the deep tropics; when the component of SST trend related to aerosol emissions is removed, further warming is found in the extratropical Northern Hemisphere that tends to offset monsoon weakening. This suggests caution is needed when using SST forcing as a proxy for greenhouse warming. Finally, aerosol emissions are decomposed into those from the Indian region and those elsewhere in pairs of experiments with SD and BC. Both local and remote aerosol emissions are found to lead to rainfall changes over India; for SD, remote aerosols contribute around 75% of the rainfall decrease over India, while for BC the remote forcing is even more dominant.

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Liang Wang, Dan Li, Ning Zhang, Jianning Sun, and Weidong Guo

Abstract

Urban heat islands (UHIs) are caused by a multitude of changes induced by urbanization. However, the relative importance of biophysical and atmospheric factors in controlling the UHI intensity remains elusive. In this study, we quantify the magnitude of surface UHIs (SUHIs), or surface urban cool islands (SUCIs), and elucidate their biophysical and atmospheric drivers on the basis of observational data collected from one urban site and two rural grassland sites in and near the city of Nanjing, China. Results show that during the daytime a strong SUCI effect is observed when the short grassland site is used as the reference site whereas a moderate SUHI effect is observed when the tall grassland is used as the reference site. We find that the former is mostly caused by the lower aerodynamic resistance for convective heat transfer at the urban site and the latter is primarily caused by the higher surface resistance for evapotranspiration at the urban site. At night, SUHIs are observed when either the short or the tall grassland site is used as the reference site and are predominantly caused by the stronger release of heat storage at the urban site. In general, the magnitude of SUHI is much weaker, and even becomes SUCI during daytime, with the short grassland site being the reference site because of its larger aerodynamic resistance. The study highlights that the magnitude of SUHIs and SUCIs is mostly controlled by urban–rural differences of biophysical factors, with urban–rural differences of atmospheric conditions playing a minor role.

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Cédric H. David, David R. Maidment, Guo-Yue Niu, Zong-Liang Yang, Florence Habets, and Victor Eijkhout

Abstract

The mapped rivers and streams of the contiguous United States are available in a geographic information system (GIS) dataset called National Hydrography Dataset Plus (NHDPlus). This hydrographic dataset has about 3 million river and water body reaches along with information on how they are connected into networks. The U.S. Geological Survey (USGS) National Water Information System (NWIS) provides streamflow observations at about 20 thousand gauges located on the NHDPlus river network. A river network model called Routing Application for Parallel Computation of Discharge (RAPID) is developed for the NHDPlus river network whose lateral inflow to the river network is calculated by a land surface model. A matrix-based version of the Muskingum method is developed herein, which RAPID uses to calculate flow and volume of water in all reaches of a river network with many thousands of reaches, including at ungauged locations. Gauges situated across river basins (not only at basin outlets) are used to automatically optimize the Muskingum parameters and to assess river flow computations, hence allowing the diagnosis of runoff computations provided by land surface models. RAPID is applied to the Guadalupe and San Antonio River basins in Texas, where flow wave celerities are estimated at multiple locations using 15-min data and can be reproduced reasonably with RAPID. This river model can be adapted for parallel computing and although the matrix method initially adds a large overhead, river flow results can be obtained faster than with the traditional Muskingum method when using a few processing cores, as demonstrated in a synthetic study using the upper Mississippi River basin.

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Chengzu Bai, Ren Zhang, Senliang Bao, X. San Liang, and Wenbo Guo

Abstract

How to extract the causal relations in climate–cyclone interactions is an important problem in atmospheric science. Traditionally, the most commonly used research methodology in this field is time-delayed correlation analysis. This may be not appropriate, since a correlation cannot imply causality, as it lacks the needed asymmetry or directedness between dynamical events. This study introduces a recently developed and very concise but rigorous formula—that is, a formula for information flow (IF)—to fulfill the purpose. A new way to normalize the IF is proposed and then the normalized IF (NIF) is used to detect the causal relation between the tropical cyclone (TC) genesis over the western North Pacific (WNP) and a variety of climate modes. It is shown that El Niño–Southern Oscillation and Pacific decadal oscillation are the dominant factors that modulate the WNP TC genesis. The western Pacific subtropical high and the monsoon trough are also playing important roles in affecting the TCs in the western and eastern regions of the WNP, respectively. With these selected climate indices as predictors, a method of fuzzy graph evolved from a nonparametric Bayesian process (BNP-FG), which is capable of handling situations with insufficient samples, is employed to perform a seasonal TC forecast. A forecast with the classic Poisson regression is also conducted for comparison. The BNP-FG model and the causality analysis are found to provide a satisfactory estimation of the number of TC genesis observed in recent years. Considering its generality, it is expected to be applicable in other climate-related predictions.

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Enrique Rosero, Zong-Liang Yang, Lindsey E. Gulden, Guo-Yue Niu, and David J. Gochis

Abstract

The authors introduce and compare the performance of the unified Noah land surface model (LSM) and its augments with physically based, more conceptually realistic hydrologic parameterizations. Forty-five days of 30-min data collected over nine sites in transition zones are used to evaluate (i) their benchmark, the standard Noah LSM release 2.7 (STD); (ii) a version equipped with a short-term phenology module (DV); and (iii) one that couples a lumped, unconfined aquifer model to the model soil column (GW). Their model intercomparison, enhanced by multiobjective calibration and model sensitivity analysis, shows that, under the evaluation conditions, the current set of enhancements to Noah fails to yield significant improvement in the accuracy of simulated, high-frequency, warm-season turbulent fluxes, and near-surface states across these sites. Qualitatively, the versions of DV and GW implemented degrade model robustness, as defined by the sensitivity of model performance to uncertain parameters. Quantitatively, calibrated DV and GW show only slight improvement in the skill of the model over calibrated STD. Then, multiple model realizations are compared to explicitly account for parameter uncertainty. Model performance, robustness, and fitness are quantified for use across varied sites. The authors show that the least complex benchmark LSM (STD) remains as the most fit version of the model for broad application. Although GW typically performs best when simulating evaporative fraction (EF), 24-h change in soil wetness (ΔW 30), and soil wetness, it is only about half as robust as STD, which also performs relatively well for all three criteria. GW’s superior performance results from bias correction, not from improved soil moisture dynamics. DV performs better than STD in simulating EF and ΔW 30 at the wettest site, because DV tends to enhance transpiration and canopy evaporation at the expense of direct soil evaporation. This same model structure limits performance at the driest site, where STD performs best. This dichotomous performance suggests that the formulations that determine the partitioning of LE flux need to be modified for broader applicability. Thus, this work poses a caveat for simple “plug and play” of functional modules between LSMs and showcases the utility of rigorous testing during model development.

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Liang Guo, Nicholas P. Klingaman, Pier Luigi Vidale, Andrew G. Turner, Marie-Estelle Demory, and Alison Cobb

Abstract

The coastal region of East Asia (EA) is one of the regions with the most frequent impacts from tropical cyclones (TCs). In this study, rainfall and moisture transports related to TCs are measured over EA, and the contribution of TCs to the regional water budget is compared with other contributors, especially the mean circulation of the EA summer monsoon (EASM). Based on ERA-Interim reanalysis (1979–2012), the trajectories of TCs are identified using an objective feature tracking method. Over 60% of TCs occur from July to October (JASO). During JASO, TC rainfall contributes 10%–30% of the monthly total rainfall over the coastal region of EA; this contribution is highest over the south/southeast coast of China in September. TCs make a larger contribution to daily extreme rainfall (above the 95th percentile): 50%–60% over the EA coast and as high as 70% over Taiwan Island. Compared with the mean EASM, TCs transport less moisture over EA. However, as the peak of the mean seasonal cycle of TCs lags two months behind that of the EASM, the moisture transported by TCs is an important source for the water budget over the EA region when the EASM withdraws. This moisture transport is largely performed by westward-moving TCs. These results improve understanding of the water cycle of EA and provide a useful test bed for evaluating and improving seasonal forecasts and coupled climate models.

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Enrique Rosero, Lindsey E. Gulden, Zong-Liang Yang, Luis G. De Goncalves, Guo-Yue Niu, and Yasir H. Kaheil

Abstract

The ability of two versions of the Noah land surface model (LSM) to simulate the water cycle of the Little Washita River experimental watershed is evaluated. One version that uses the standard hydrological parameterizations of Noah 2.7 (STD) is compared another version that replaces STD’s subsurface hydrology with a simple aquifer model and topography-related surface and subsurface runoff parameterizations (GW). Simulations on a distributed grid at fine resolution are compared to the long-term distribution of observed daily-mean runoff, the spatial statistics of observed soil moisture, and locally observed latent heat flux. The evaluation targets the typical behavior of ensembles of models that use realistic, near-optimal sets of parameters important to runoff. STD and GW overestimate the ratio of runoff to evapotranspiration. In the subset of STD and GW runs that best reproduce the timing and the volume of streamflow, the surface-to-subsurface runoff ratio is overestimated and simulated streamflow is much flashier than observations. Both models’ soil columns wet and dry too quickly, implying that there are structural shortcomings in the formulation of STD that cannot be overcome by adding GW’s increased complexity to the model. In its current formulation, GW extremely underestimates baseflow’s contribution to total runoff and requires a shallow water table to function realistically. In the catchment (depth to water table >10 m), GW functions as a simple bucket model. Because model parameters are likely scale and site dependent, the need for even “physically based” models to be extensively calibrated for all domains on which they are applied is underscored.

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