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De-Zheng Sun, Yongqiang Yu, and Tao Zhang

Abstract

By comparing the response of clouds and water vapor to ENSO forcing in nature with that in Atmospheric Model Intercomparison Project (AMIP) simulations by some leading climate models, an earlier evaluation of tropical cloud and water vapor feedbacks has revealed the following two common biases in the models: 1) an underestimate of the strength of the negative cloud albedo feedback and 2) an overestimate of the positive feedback from the greenhouse effect of water vapor. Extending the same analysis to the fully coupled simulations of these models as well as other Intergovernmental Panel on Climate Change (IPCC) coupled models, it is found that these two biases persist. Relative to the earlier estimates from AMIP simulations, the overestimate of the positive feedback from water vapor is alleviated somewhat for most of the coupled simulations. Improvements in the simulation of the cloud albedo feedback are only found in the models whose AMIP runs suggest either a positive or nearly positive cloud albedo feedback. The strength of the negative cloud albedo feedback in all other models is found to be substantially weaker than that estimated from the corresponding AMIP simulations. Consequently, although additional models are found to have a cloud albedo feedback in their AMIP simulations that is as strong as in the observations, all coupled simulations analyzed in this study have a weaker negative feedback from the cloud albedo and therefore a weaker negative feedback from the net surface heating than that indicated in observations. The weakening in the cloud albedo feedback is apparently linked to a reduced response of deep convection over the equatorial Pacific, which is in turn linked to the excessive cold tongue in the mean climate of these models. The results highlight that the feedbacks of water vapor and clouds—the cloud albedo feedback in particular—may depend on the mean intensity of the hydrological cycle. Whether the intermodel variations in the feedback from cloud albedo (water vapor) in the ENSO variability are correlated with the intermodel variations of the feedback from cloud albedo (water vapor) in global warming has also been examined. While a weak positive correlation between the intermodel variations in the feedback of water vapor during ENSO and the intermodel variations in the water vapor feedback during global warming was found, there is no significant correlation found between the intermodel variations in the cloud albedo feedback during ENSO and the intermodel variations in the cloud albedo feedback during global warming. The results suggest that the two common biases revealed in the simulated ENSO variability may not necessarily be carried over to the simulated global warming. These biases, however, highlight the continuing difficulty that models have in simulating accurately the feedbacks of water vapor and clouds on a time scale of the observations available.

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Yongqiang Zhang, Francis H. S. Chiew, Lu Zhang, and Hongxia Li

Abstract

This paper explores the use of the Moderate Resolution Imaging Spectroradiometer (MODIS), mounted on the polar-orbiting Terra satellite, to determine leaf area index (LAI), and use actual evapotranspiration estimated using MODIS LAI data combined with the Penman–Monteith equation [remote sensing evapotranspiration (E RS)] in a lumped conceptual daily rainfall–runoff model. The model is a simplified version of the HYDROLOG (SIMHYD) model, which is used to estimate runoff in ungauged catchments. Two applications were explored: (i) the calibration of SIMHYD against both the observed streamflow and E RS, and (ii) the modification of SIMHYD to use MODIS LAI data directly. Data from 2001 to 2005 from 120 catchments in southeast Australia were used for the study. To assess the modeling results for ungauged catchments, optimized parameter values from the geographically nearest gauged catchment were used to model runoff in the ungauged catchment. The results indicate that the SIMHYD calibration against both the observed streamflow and E RS produced better simulations of daily and monthly runoff in ungauged catchments compared to the SIMHYD calibration against only the observed streamflow data, despite the modeling results being assessed solely against the observed streamflow data. The runoff simulations were even better for the modified SIMHYD model that used the MODIS LAI directly. It is likely that the use of other remotely sensed data (such as soil moisture) and smarter modification of rainfall–runoff models to use remotely sensed data directly can further improve the prediction of runoff in ungauged catchments.

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De-Zheng Sun, Tao Zhang, Yan Sun, and Yongqiang Yu

Abstract

To better understand the causes of climate change in the tropical Pacific on the decadal and longer time scales, the rectification effect of ENSO events is delineated by contrasting the time-mean state of two forced ocean GCM experiments. In one of them, the long-term mean surface wind stress of 1950–2011 is applied, while in the other, the surface wind stress used is the long-term mean surface wind stress of 1950–2011 plus the interannual monthly anomalies over the period. Thus, the long-term means of the surface wind stress in the two runs are identical. The two experiments also use the same relaxation boundary conditions, that is, the SST is restored to the same prescribed values. The two runs, however, are found to yield significantly different mean climate for the tropical Pacific. The mean state of the run with interannual fluctuations in the surface winds is found to have a cooler warm pool, warmer thermocline water, and warmer eastern surface Pacific than the run without interannual fluctuations in the surface winds. The warming of the eastern Pacific has a pattern that resembles the observed decadal warming. In particular, the pattern features an off-equator maximum as the observed decadal warming. The spatial pattern of the time-mean upper-ocean temperature differences between the two experiments is shown to resemble that of the differences in the nonlinear dynamic heating, underscoring the role of the nonlinear ocean dynamics in the rectification. The study strengthens the suggestion that rectification of ENSO can be a viable mechanism for climate change of decadal and longer time scales.

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Huqiang Zhang, Bernard Pak, Ying Ping Wang, Xinyao Zhou, Yongqiang Zhang, and Liang Zhang

Abstract

The terrestrial water cycle in the Australian Community Atmosphere Biosphere Land Exchange (CABLE) model has been evaluated across a range of temporal and spatial domains. A series of offline experiments were conducted using the forcing data from the second Global Soil Wetness Project (GSWP-2) for the period of 1986–95, but with its default parameter settings. Results were compared against GSWP-2 multimodel ensembles and a range of observationally driven datasets. CABLE-simulated global mean evapotranspiration (ET) and runoff agreed well with the GSWP-2 multimodel climatology and observations, and the spatial variations of ET and runoff across 150 large catchments were well captured. Nevertheless, at regional scales it underestimated ET in the tropics and had some significant runoff errors. The model sensitivity to a number of selected parameters is further examined. Results showed some significant model uncertainty caused by its sensitivity to soil wilting point as well as to the root water uptaking efficiency and canopy water storage parameters. The sensitivity was large in tropical rain forest and midlatitude forest regions, where the uncertainty caused by the model parameters was comparable to a large part of its difference against the GSWP-2 multimodel mean. Furthermore, the discrepancy among the CABLE perturbation experiments caused by its sensitivity to model parameters was equivalent to about 20%–40% of the intermodel difference among the GSWP-2 models, which was primarily caused by different model structure/processes. Although such results are model dependent, they suggest that soil/vegetation parameters could be another source of uncertainty in estimating global surface energy and water budgets.

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Yongqiang Zhang, Hongxing Zheng, Francis H. S. Chiew, Jorge Peña- Arancibia, and Xinyao Zhou

Abstract

Land surface and global hydrological models are often used to characterize global water and energy fluxes and stores and to model their future trajectories. This study evaluates estimates of streamflow and evapotranspiration (ET) obtained with a priori parameterization from a land surface model [CSIRO Atmosphere Biosphere Land Exchange (CABLE)] and a global hydrological model (H08) against a global dataset of streamflow from 644 largely unregulated catchments and ET from 98 flux towers and benchmarks their performance against two lumped conceptual daily rainfall–runoff models [modèle du Génie Rural à 4 paramètres Journalier (GR4J) and a simplified version of the HYDROLOG model (SIMHYD)]. The results show that all four models perform poorly in simulating the monthly and annual runoff values, with the rainfall–runoff models outperforming both CABLE and H08. The model biases in runoff are generally reflected as a complementary opposite bias in ET. All models can generally reproduce the observed seasonal and interannual runoff variability. The correlations between the modeled and observed runoff time series are reasonable, with the rainfall–runoff models performing slightly better than CABLE and H08 at the monthly time scale and all four models performing similarly at the annual time scale. The results suggest that while the land surface and global hydrological models cannot adequately simulate the actual runoff time series and long-term average volumes, they can reasonably simulate the monthly and interannual runoff variability and trends and can therefore be reliably used for broadscale or comparative regional and global water and energy balance assessments and simulations of future trajectories. They can be improved through validating the models or calibrating some of the more sensitive and less physically based parameters.

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Yongqiang Zhang, Ray Leuning, Francis H. S. Chiew, Enli Wang, Lu Zhang, Changming Liu, Fubao Sun, Murray C. Peel, Yanjun Shen, and Martin Jung

Abstract

Satellite and gridded meteorological data can be used to estimate evaporation (E) from land surfaces using simple diagnostic models. Two satellite datasets indicate a positive trend (first time derivative) in global available energy from 1983 to 2006, suggesting that positive trends in evaporation may occur in “wet” regions where energy supply limits evaporation. However, decadal trends in evaporation estimated from water balances of 110 wet catchments do not match trends in evaporation estimated using three alternative methods: 1) , a model-tree ensemble approach that uses statistical relationships between E measured across the global network of flux stations, meteorological drivers, and remotely sensed fraction of absorbed photosynthetically active radiation; 2) , a Budyko-style hydrometeorological model; and 3) , the Penman–Monteith energy-balance equation coupled with a simple biophysical model for surface conductance. Key model inputs for the estimation of and are remotely sensed radiation and gridded meteorological fields and it is concluded that these data are, as yet, not sufficiently accurate to explain trends in E for wet regions. This provides a significant challenge for satellite-based energy-balance methods. Trends in for 87 “dry” catchments are strongly correlated to trends in precipitation (R 2 = 0.85). These trends were best captured by , which explicitly includes precipitation and available energy as model inputs.

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Fan Yang, Qing He, Jianping Huang, Ali Mamtimin, Xinghua Yang, Wen Huo, Chenglong Zhou, Xinchun Liu, Wenshou Wei, Caixia Cui, Minzhong Wang, Hongjun Li, Lianmei Yang, Hongsheng Zhang, Yuzhi Liu, Xinqian Zheng, Honglin Pan, Lili Jin, Han Zou, Libo Zhou, Yongqiang Liu, Jiantao Zhang, Lu Meng, Yu Wang, Xiaolin Qin, Yongjun Yao, Houyong Liu, Fumin Xue, and Wei Zheng

Abstract

As the second-largest shifting sand desert worldwide, the Taklimakan Desert (TD) represents the typical aeolian landforms in arid regions as an important source of global dust aerosols. It directly affects the ecological environment and human health across East Asia. Thus, establishing a comprehensive environment and climate observation network for field research in the TD region is essential to improve our understanding of the desert meteorology and environment, assess its impact, mitigate potential environmental issues, and promote sustainable development. With a nearly 20-yr effort under the extremely harsh conditions of the TD, the Desert Environment and Climate Observation Network (DECON) has been established completely covering the TD region. The core of DECON is the Tazhong station in the hinterland of the TD. Moreover, the network also includes 4 satellite stations located along the edge of the TD for synergistic observations, and 18 automatic weather stations interspersed between them. Thus, DECON marks a new chapter of environmental and meteorological observation capabilities over the TD, including dust storms, dust emission and transport mechanisms, desert land–atmosphere interactions, desert boundary layer structure, ground calibration for remote sensing monitoring, and desert carbon sinks. In addition, DECON promotes cooperation and communication within the research community in the field of desert environments and climate, which promotes a better understanding of the status and role of desert ecosystems. Finally, DECON is expected to provide the basic support necessary for coordinated environmental and meteorological monitoring and mitigation, joint construction of ecologically friendly communities, and sustainable development of central Asia.

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