On the Applicability of Temperature and Precipitation Data from CMIP3 for China

Global Circulation Models (GCMs) contributed to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) and are widely used in global change research. This paper assesses the performance of the AR4 GCMs in simulating precipitation and temperature in China from 1960 to 1999 by comparison with observed data, using system bias (B), root-mean-square error (RMSE), Pearson correlation coefficient (R) and Nash-Sutcliffe model efficiency (E) metrics. Probability density functions (PDFs) are also fitted to the outputs of each model. It is shown that the performance of each GCM varies to different degrees across China. Based on the skill score derived from the four metrics, it is suggested that GCM 15 (ipsl_cm4) and GCM 3 (cccma_cgcm_t63) provide the best representations of temperature and precipitation, respectively, in terms of spatial distribution and trend over 10 years. The results also indicate that users should apply carefully the results of annual precipitation and annual temperature generated by AR4 GCMs in China due to poor performance. At a finer scale, the four metrics are also used to obtain best fit scores for ten river basins covering mainland China. Further research is proposed to improve the simulation accuracy of the AR4 GCMs regarding China

Delay-induced multiple stochastic resonances on scale-free neuronal networks

We study the effects of periodic subthreshold pacemaker activity and time-delayed coupling on stochastic resonance over scale-free neuronal networks. As the two extreme options, we introduce the pacemaker respectively to the neuron with the highest degree and to one of the neurons with the lowest degree within the network, but we also consider the case when all neurons are exposed to the periodic forcing. In the absence of delay, we show that an intermediate intensity of noise is able to optimally assist the pacemaker in imposing its rhythm on the whole ensemble, irrespective to its placing, thus providing evidences for stochastic resonance on the scale-free neuronal networks. Interestingly thereby, if the forcing in form of a periodic pulse train is introduced to all neurons forming the network, the stochastic resonance decreases as compared to the case when only a single neuron is paced. Moreover, we show that finite delays in coupling can significantly affect the stochastic resonance on scale-free neuronal networks. In particular, appropriately tuned delays can induce multiple stochastic resonances independently of the placing of the pacemaker, but they can also altogether destroy stochastic resonance. Delay-induced multiple stochastic resonances manifest as well-expressed maxima of the correlation measure, appearing at every multiple of the pacemaker period. We argue that fine-tuned delays and locally active pacemakers are vital for assuring optimal conditions for stochastic resonance on complex neuronal networks.Comment: 7 two-column pages, 5 figures; accepted for publication in Chao

Environmental impact assessments of the Xiaolangdi Reservoir on the most hyperconcentrated laden river, Yellow River, China

The Yellow River is the most hyperconcentrated sediment-laden river in the world. Throughout recorded history, the Lower Yellow River (LYR) experienced many catastrophic flood and drought events. To regulate the LYR, a reservoir was constructed at Xiaolangdi that became operational in the early 2000s. An annual water-sediment regulation scheme (WSRS) was then implemented, aimed at flood control, sediment reduction, regulated water supply, and power generation. This study examines the eco-environmental and socioenvironmental impacts of Xiaolangdi Reservoir. In retrospect, it is found that the reservoir construction phase incurred huge financial cost and required large-scale human resettlement. Subsequent reservoir operations affected the local geological environment, downstream riverbed erosion, evolution of the Yellow River delta, water quality, and aquatic biodiversity. Lessons from the impact assessment of the Xiaolangdi Reservoir are summarized as follows: (1) The construction of large reservoirs is not merely an engineering challenge but must also be viewed in terms of resource exploitation, environmental protection, and social development; (2) long-term systems for monitoring large reservoirs should be established, and decision makers involved at national policy and planning levels must be prepared to react quickly to the changing impact of large reservoirs; and (3) the key to solving sedimentation in the LYR is not Xiaolangdi Reservoir but instead soil conservation in the middle reaches of the Yellow River basin. Proper assessment of the impacts of large reservoirs will help promote development strategies that enhance the long-term sustainability of dam projects

Wavelet-based variability of Yellow River discharge at 500-. 100-, and 50-year timescales

Water scarcity in the Yellow River, China, has become increasingly severe over the past half century. In this paper, wavelet transform analysis was used to detect the variability of natural, observed, and reconstructed streamflow in the Yellow River at 500-, 100-, and 50-year timescales. The periodicity of the streamflow series and the co-varying relationships between streamflow and atmospheric circulation indices/sunspot number were assessed by means of continuous wavelet transform (CWT) and wavelet transform coherence (WTC) analyses. The CWT results showed intermittent oscillations in streamflow with increasing periodicities of 1–6 years at all timescales. Significant multidecadal and century-scale periodicities were identified in the 500-year streamflow series. The WTC results showed intermittent interannual covariance of streamflow with atmospheric circulation indices and sunspots. At the 50-year timescale, there were significant decadal oscillations between streamflow and the Arctic Oscillation (AO) and the Pacific Decadal Oscillation (PDO), and bidecadal oscillations with the PDO. At the 100-year timescale, there were significant decadal oscillations between streamflow and Niño 3.4, the AO, and sunspots. At the 500-year timescale, streamflow in the middle reaches of the Yellow River showed prominent covariance with the AO with an approximately 32-year periodicity, and with sunspots with an approximately 80-year periodicity. Atmospheric circulation indices modulate streamflow by affecting temperature and precipitation. Sunspots impact streamflow variability by influencing atmospheric circulation, resulting in abundant precipitation. In general, for both the CWT and the WTC results, the periodicities were spatially continuous, with a few gradual changes from upstream to downstream resulting from the varied topography and runoff. At the temporal scale, the periodicities were generally continuous over short timescales and discontinuous over longer timescales

The Gravity Environment of Zhouqu Debris Flow of August 2010 and Its Implication for Future Recurrence

This study investigates the geological background of the August 7-8, 2010 Zhouqu debris flows in the northwestern Chinese province of Gansu, and possible future occurrence of such hazards in the peri-Tibetan Plateau (TP) regions. Debris flows are a more predictable type of landslide because of its strong correlation with extreme precipitation. However, two factors affecting the frequency and magnitude of debris flows: very fine scale precipitation and degree of fracture of bedrock, both defy direct observations. Annual mean Net Primary production (NPP) is used as a surrogate for regional precipitation with patchiness filtered out, and gravity satellite measured regional mass changes as an indication of bedrock cracking, through the groundwater as the nexus. The GRACE measurements indicate a region (to the north east of TP) of persistent mass gain (started well before the 2008 Wenchuan earthquake), likely due to increased groundwater percolation. While in the neighboring agricultural region further to the north east, there are signal of decreased fossil water reservoir. The imposed stress fields by large scale increase/decrease groundwater may contribute to future geological instability of this region. Zhouqu locates right on the saddle of the gravity field anomaly. The region surrounding the Bay of Bangle (to the southeast of TP) has a similar situation. To investigate future changes in extreme precipitation, the other key player for debris flows, the “pseudo-climate change” experiments of a weather model forced by climate model provided perturbations on the thermal fields are performed and endangered locations are identified. In the future warmer climate, extreme precipitation will be more severe and debris will be more frequent and severe

Ensemble flood forecasting: current status and future opportunities

Ensemble flood forecasting has gained significant momentum over the past decade due to the growth of ensemble numerical weather and climate prediction, expansion in high performance computing, growing interest in shifting from deterministic to risk-based decision-making that accounts for forecast uncertainty, and the efforts of communities such as the international Hydrologic Ensemble Prediction Experiment (HEPEX), which focuses on advancing relevant ensemble forecasting capabilities and fostering its adoption. With this shift, comes the need to understand the current state of ensemble flood forecasting, in order to provide insights into current capabilities and areas for improvement, thus identifying future research opportunities to allow for better allocation of research resources. In this paper, we provide an overview of current research activities in ensemble flood forecasting and discuss knowledge gaps and future research opportunities, based on a review of 70 papers focussing on various aspects of ensemble flood forecasting around the globe. Future research directions include opportunities to improve technical aspects of ensemble flood forecasting, such as data assimilation techniques and methods to account for more sources of uncertainty, and developing ensemble forecasts for more variables, for example flood inundation, by applying techniques such as machine learning. Further to this, we conclude that there is a need to not only improve technical aspects of flood forecasting, but also to bridge the gap between scientific research and hydro-meteorological model development, and real-world flood management using probabilistic ensemble forecasts, especially through effective communication

The First 30 years of GEWEX

International audienceAbstract The Global Energy and Water Cycle EXchanges (GEWEX) project was created more than thirty years ago within the framework of the World Climate Research Programme (WCRP). The aim of this initiative was to address major gaps in our understanding of Earth’s energy and water cycles given a lack of information about the basic fluxes and associated reservoirs of these cycles. GEWEX sought to acquire and set standards for climatological data on variables essential for quantifying water and energy fluxes and for closing budgets at the regional and global scales. In so doing, GEWEX activities led to a greatly improved understanding of processes and our ability to predict them. Such understanding was viewed then, as it remains today, essential for advancing weather and climate prediction from global to regional scales. GEWEX has also demonstrated over time the importance of a wider engagement of different communities and the necessity of international collaboration for making progress on understanding and on the monitoring of the changes in the energy and water cycles under ever increasing human pressures. This paper reflects on the first 30 years of evolution and progress that has occurred within GEWEX. This evolution is presented in terms of three main phases of activity. Progress toward the main goals of GEWEX is highlighted by calling out a few achievements from each phase. A vision of the path forward for the coming decade, including the goals of GEWEX for the future, are also described

Effects of frozen soil on soil temperature, spring infiltration, and runoff: results from the PILPS 2(d) experiment at Valdai, Russia

Permission to place copies of these works on this server has been provided by the American Meteorological Society (AMS). The AMS does not guarantee that the copies provided here are accurate copies of the published work. © Copyright 2003 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/AMS) or from the AMS at 617-227-2425 or [email protected] Project for Intercomparison of Land-Surface Parameterization Schemes phase 2(d) experiment at Valdai, Russia, offers a unique opportunity to evaluate land surface schemes, especially snow and frozen soil parameterizations. Here, the ability of the 21 schemes that participated in the experiment to correctly simulate the thermal and hydrological properties of the soil on several different timescales was examined. Using observed vertical profiles of soil temperature and soil moisture, the impact of frozen soil schemes in the land surface models on the soil temperature and soil moisture simulations was evaluated. It was found that when soil-water freezing is explicitly included in a model, it improves the simulation of soil temperature and its variability at seasonal and interannual scales. Although change of thermal conductivity of the soil also affects soil temperature simulation, this effect is rather weak. The impact of frozen soil on soil moisture is inconclusive in this experiment due to the particular climate at Valdai, where the top 1 m of soil is very close to saturation during winter and the range for soil moisture changes at the time of snowmelt is very limited. The results also imply that inclusion of explicit snow processes in the models would contribute to substantially improved simulations. More sophisticated snow models based on snow physics tend to produce better snow simulations, especially of snow ablation. Hysteresis of snow-cover fraction as a function of snow depth is observed at the catchment but not in any of the models

Effects of Frozen Soil on Soil Temperature, Spring Infiltration, and Runoff: Results from the PILPS 2(d) Experiment at Valdai, Russia

The Project for Intercomparison of Land-Surface Parameterization Schemes phase 2(d) experiment at Valdai, Russia, offers a unique opportunity to evaluate land surface schemes, especially snow and frozen soil parameterizations. Here, the ability of the 21 schemes that participated in the experiment to correctly simulate the thermal and hydrological properties of the soil on several different timescales was examined. Using observed vertical profiles of soil temperature and soil moisture, the impact of frozen soil schemes in the land surface models on the soil temperature and soil moisture simulations was evaluated. It was found that when soil-water freezing is explicitly included in a model, it improves the simulation of soil temperature and its variability at seasonal and interannual scales. Although change of thermal conductivity of the soil also affects soil temperature simulation, this effect is rather weak. The impact of frozen soil on soil moisture is inconclusive in this experiment due to the particular climate at Valdai, where the top 1 m of soil is very close to saturation during winter and the range for soil moisture changes at the time of snowmelt is very limited. The results also imply that inclusion of explicit snow processes in the models would contribute to substantially improved simulations. More sophisticated snow models based on snow physics tend to produce better snow simulations, especially of snow ablation. Hysteresis of snow-cover fraction as a function of snow depth is observed at the catchment but not in any of the models