Chiyuan Miao

Recent changes of water discharge and sediment load in the Yellow River basin, China

The Yellow River basin contributes approximately 6% of the sediment load from all river systems globally, and the annual runoff directly supports 12% of the Chinese population. As a result, describing and understanding recent variations of water discharge and sediment load under global change scenarios are of considerable importance. The present study considers the annual hydrologic series of the water discharge and sediment load of the Yellow River basin obtained from 15 gauging stations (10 mainstream, 5 tributaries). The Mann-Kendall test method was adopted to detect both gradual and abrupt change of hydrological series since the 1950s. With the exception of the area draining to the Upper Tangnaihai station, results indicate that both water discharge and sediment load have decreased significantly (p<0.05). The declining trend is greater with distance downstream, and drainage area has a significant positive effect on the rate of decline. It is suggested that the abrupt change of the water discharge from the late 1980s to the early 1990s arose from human extraction, and that the abrupt change in sediment load was linked to disturbance from reservoir construction.

Evaluation of the PERSIANN-CDR Daily Rainfall Estimates in Capturing the Behavior of Extreme Precipitation Events over China

AbstractThis study evaluates the performance of a newly developed daily precipitation climate data record, called Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), in capturing the behavior of daily extreme precipitation events in China during the period of 1983–2006. Different extreme precipitation indices, in the three categories of percentile, absolute threshold, and maximum indices, are studied and compared with the same indices from the East Asia (EA) ground-based gridded daily precipitation dataset. The results show that PERSIANN-CDR depicts similar precipitation behavior as the ground-based EA product in terms of capturing the spatial and temporal patterns of daily precipitation extremes, particularly in the eastern China monsoon region, where the intensity and frequency of heavy rainfall events are very high. However, the agreement between the datasets in dry regions such as the Tibetan Plateau in the west and the Taklama...

Assessment of CMIP5 climate models and projected temperature changes over Northern Eurasia

Assessing the performance of climate models in surface air temperature (SAT) simulation andprojection have received increasing attention during the recent decades. This paper assesses theperformance of the Coupled Model Intercomparison Project phase 5 (CMIP5) in simulatingintra-annual, annual and decadal temperature over Northern Eurasia from 1901 to 2005. Weevaluate the skill of different multi-model ensemble techniques and use the best technique toproject the future SAT changes under different emission scenarios. The results show that most ofthe general circulation models (GCMs) overestimate the annual mean SAT in Northern Eurasiaand the difference between the observation and the simulations primarily comes from the winterseason. Most of the GCMs can approximately capture the decadal SAT trend; however, theaccuracy of annual SAT simulation is relatively low. The correlation coefficient R between eachGCM simulation and the annual observation is in the range of 0.20 to 0.56. The Taylor diagramshows that the ensemble results generated by the simple model averaging (SMA), reliabilityensemble averaging (REA) and Bayesian model averaging (BMA) methods are superior to anysingle GCM output; and the decadal SAT change generated by SMA, REA and BMA are almostidentical during 1901–2005. Heuristically, the uncertainty of BMA simulation is the smallestamong the three multi-model ensemble simulations. The future SAT projection generated by theBMA shows that the SAT in Northern Eurasia will increase in the 21st century by around1.03°C/100yr, 3.11°C/100yr and 7.14°C/100yr under the RCP 2.6, RCP 4.5 and RCP 8.5scenarios, respectively; and the warming accelerates with the increasing latitude. In addition, thespring season contributes most to the decadal warming occurring under the RCP 2.6 and RCP4.5 scenarios, while the winter season contributes most to the decadal warming occurring underthe RCP 8.5 scenario. Generally, the uncertainty of the SAT projections increases with time inthe 21st century.S Online supplementary data available from stacks.iop.org/ERL/9/055007/mmediaKeywords: CMIP5, multi-model ensembles, Northern Eurasia, temperature

Improvement of phytoextraction and antioxidative defense in Solanum nigrum L. under cadmium stress by application of cadmium-resistant strain and citric acid.

Remediation of plant-microorganism-chelates synergy has been proposed as an effective remediation method for enhancing the removal efficiency of heavy metal. Manipulation of the antioxidative system increases plant tolerance, thereby potentially enhancing the uptake capacity to heavy metal. In this study, we investigated the possibility of improving the phytoextraction of Cd and the antioxidative defense of Solanum nigrum L. by application of a new isolated strain (Paecilomyces lilacinus NH1) (PLNH1) and citric acid (CA). The results showed that application of CA or PLNH1 significantly promoted S. nigrums growth under Cd stress, but the synergistic effect of CA and PLNH1 on S. nigrums growth was more obvious. The coexistence of CA and PLNH1 could enhance about 30% of Cd accumulation in different organs of S. nigrum compared to the treatment without the addition of CA and PLNH1, whereas single CA or PLNH1 added treatment only enhanced about 10-15% of Cd accumulation in different organs of S. nigrum. The antioxidative defense in S. nigrum under Cd stress was significantly improved as result of application of CA and PLNH1. The responses of antioxidative enzymes to Cd stress significantly decreased following application of CA and PLNH1, and the oxidative stress experienced by the plant due to Cd in the soil was significantly alleviated.

Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for China

This research compared and evaluated the spatio-temporal similarities and differences of eight widely used gridded datasets. The datasets include daily precipitation over East Asia (EA), the Climate Research Unit (CRU) product, the Global Precipitation Climatology Centre (GPCC) product, the University of Delaware (UDEL) product, Precipitation Reconstruction over Land (PREC/L), the Asian Precipitation Highly Resolved Observational (APHRO) product, the Institute of Atmospheric Physics (IAP) dataset from the Chinese Academy of Sciences, and the National Meteorological Information Center dataset from the China Meteorological Administration (CN05). The meteorological variables focus on surface air temperature (SAT) or precipitation (PR) in China. All datasets presented general agreement on the whole spatio-temporal scale, but some differences appeared for specific periods and regions. On a temporal scale, EA shows the highest amount of PR, while APHRO shows the lowest. CRU and UDEL show higher SAT than IAP or CN05. On a spatial scale, the most significant differences occur in western China for PR and SAT. For PR, the difference between EA and CRU is the largest. When compared with CN05, CRU shows higher SAT in the central and southern Northwest river drainage basin, UDEL exhibits higher SAT over the Southwest river drainage system, and IAP has lower SAT in the Tibetan Plateau. The differences in annual mean PR and SAT primarily come from summer and winter, respectively. Finally, potential factors impacting agreement among gridded climate datasets are discussed, including raw data sources, quality control (QC) schemes, orographic correction, and interpolation techniques. The implications and challenges of these results for climate research are also briefly addressed.

Functional degradation of the water-sediment regulation scheme in the lower Yellow River: Spatial and temporal analyses.

Heavy sedimentation has led to the phenomenon of a secondary perched river in the lower reaches of the Yellow River. The water-sediment regulation scheme (WSRS) using the Xiaolangdi Reservoir was first implemented in 2002 to try to solve this problem. In this study, we analyzed the spatial and temporal effects of the current WSRS (2005-2013) on the lower Yellow River. Our results suggest that the current WSRS is exhibiting a tendency towards functional degradation, meaning that the scheme is no longer as effective as it was initially for the lower Yellow River. Although the main river channel has been fully scoured in the lower reaches since the implementation of the WSRS, we found that the degree of erosion declined gradually in a top-down fashion from the braided reach, through the transitional reach, to the meandering reach. Of the total eroded sediment, 69.64% came from the braided reach and only 6.61% came from the meandering reach. In addition, the reduction in riverbed elevation-a key function of the WSRS-has clearly slowed since 2005. We discuss the mechanisms underlying this functional degradation of the current WSRS and future challenges for the management of the lower Yellow River. Insights gained from this study will likely be of use to those weighing up options for future implementations of the WSRS.

Comparative analysis of CMIP3 and CMIP5 global climate models for simulating the daily mean, maximum, and minimum temperatures and daily precipitation over China

This study assesses the simulations of the daily mean, maximum, and minimum temperatures and daily precipitation over China during the period 1990–1999, based on phase 3 and phase 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). Fourteen CMIP3 models and 14 CMIP5 models were investigated over eight regions across China. Skill scores quantifying the match between the simulated and observed probability density functions (PDFs) were applied to evaluate the performance of the models. For daily mean, maximum, and minimum temperatures, the results revealed that CMIP3 and CMIP5 models captured the basic pattern of the observed PDFs in all regions. However, the probabilities at lower values were overestimated in most models. In all regions except the west of Northwest China (region 7), all CMIP5 models captured more than 80% of the observed PDFs. Compared with performance at the annual time scale, the models tended to perform relatively worse over the period June to August. The performances of the CMIP5 and CMIP3 models were not as good for daily precipitation as for daily temperature, and the skill scores for precipitation were generally lower than 0.7 in all regions. The amount of drizzle (daily precipitation < 5 mm) was overestimated notably in all regions. The amount of very heavy precipitation (daily precipitation ≥ 20 mm) tended to be underestimated in humid regions but overestimated in arid regions. Compared with CMIP3, CMIP5 models showed some improvements in the simulation of daily mean, maximum, and minimum temperatures, but there was a lack of apparent improvement for simulation of daily precipitation.

How well do CMIP5 climate simulations replicate historical trends and patterns of meteorological droughts

Author(s): Nasrollahi, N; Aghakouchak, A; Cheng, L; Damberg, L; Phillips, TJ; Miao, C; Hsu, K; Sorooshian, S | Abstract:

Evaluation and application of Bayesian multi-model estimation in temperature simulations

Use of multi-model ensembles from global climate models to simulate the current and future climate change has flourished as a research topic during recent decades. This paper assesses the performance of multi-model ensembles in simulating global land temperature from 1960 to 1999, using Nash-Sutcliffe model efficiency and Taylor diagrams. The future trends of temperature for different scales and emission scenarios are projected based on the posterior model probabilities estimated by Bayesian methods. The results show that ensemble prediction can improve the accuracy of simulations of the spatiotemporal distribution of global temperature. The performance of Bayesian model averaging (BMA) at simulating the annual temperature dynamic is significantly better than single climate models and their simple model averaging (SMA). However, BMA simulation can demonstrate the temperature trend on the decadal scale, but its annual assessment of accuracy is relatively weak. The ensemble prediction presents dissimilarly accurate descriptions in different regions, and the best performance appears in Australia. The results also indicate that future temperatures in northern Asia rise with the greatest speed in some scenarios, and Australia is the most sensitive region for the effects of greenhouse gas emissions. In addition to the uncertainty of ensemble prediction, the impacts of climate change on agriculture production and water resources are discussed as an extension of this research.

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.