A coupled earth system model（ESM） has been developed at the Nanjing University of Information Science and Technology（NUIST） by using version 5.3 of the European Centre Hamburg Model（ECHAM）, version 3.4 of the Nu...A coupled earth system model（ESM） has been developed at the Nanjing University of Information Science and Technology（NUIST） by using version 5.3 of the European Centre Hamburg Model（ECHAM）, version 3.4 of the Nucleus for European Modelling of the Ocean（NEMO）, and version 4.1 of the Los Alamos sea ice model（CICE）. The model is referred to as NUIST ESM1（NESM1）. Comprehensive and quantitative metrics are used to assess the model＇s major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model＇s assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring–fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific（CP）-ENSO and eastern Pacific（EP）-ENSO; however, the equatorial SST variability,biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden–Julian Oscillation（MJO）, and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version（T159） demonstrates improved simulation with respect to the climatology, interannual variance, monsoon–ENSO lead–lag correlation, spatial structures of the leading mode of the Asian–Australian monsoon rainfall variability, and the eastward propagation of the MJO.展开更多
The Boreal forest is a terrestrial ecosystem highly vulnerable to the impacts of short-term climate and weather variabilities. Detecting abrupt, rapid climate-induced changes in fire weather and related changes in fir...The Boreal forest is a terrestrial ecosystem highly vulnerable to the impacts of short-term climate and weather variabilities. Detecting abrupt, rapid climate-induced changes in fire weather and related changes in fire seasonality can provide important insights to assessing impacts of climate change on forestry. This paper, taking the Sakha Republic of Russia as study area, aims to suggest an approach for detecting signals indicating climate-induced changes in fire weather to express recent fire weather variability by using short-term ranks of major meteorological parameters such as air temperature and atmospheric precipitation. Climate data from the “Global Summary of the Day Product” of NOAA (the United States National Oceanic and Atmospheric Administration) for 1996 to 2018 were used to investigate meteorological parameters that drive fire activity. The detection of the climate change signals is made through a 4-step analysis. First, we used descriptive statistics to grasp monthly, annual, seasonal and peak fire period characteristics of fire weather. Then we computed historical normals for WMO reference period, 1961-1990, and the most recent 30-year period for comparison with the current means. The variability of fire weather is analyzed using standard deviation, coefficient of variation, percentage departures from historical normals, percentage departures from the mean, and precipitation concentration index. Inconsistency and abrupt changes in the evolution of fire weather are assessed using homogeneity analysis whilst a Mann-Kendall test is used to detect significant trends in the time series. The results indicate a significant increase of temperature during spring and fall months, which extends the fire season and potentially contributes to increase of burned areas. We again detected a significant rainfall shortage in September which extended the fire season. Furthermore, this study suggests a new approach in statistical methods appropriate for the detection of climate change signals on fire weather variability using short-term climate ranks and evaluation of its impact on fire seasonality and activity.展开更多
Climate variability significantly impacts agricultural water resources,particularly in regions like Vietnam's Plain of Reeds that heavily utilize rain-fed conditions.This study employs the FAO-AquaCrop model to es...Climate variability significantly impacts agricultural water resources,particularly in regions like Vietnam's Plain of Reeds that heavily utilize rain-fed conditions.This study employs the FAO-AquaCrop model to estimate current and future irrigation water needs for rice cultivation in this critical subregion,aiming to identify optimal sowing schedules(OSS)that enhance rainwater utilization and reduce irrigation dependency.The model was driven by current climate data and future projections(2041-2070 and 2071-2099)derived from downscaled Global Circulation Models under RCP4.5 and RCP8.5 scenarios.The AquaCrop model demonstrated robust performance during validation and calibration,with d-values(0.82-0.93)and R²values(0.85-0.92)indicating strong predictive accuracy for rice yield.Simulation results for efficient irrigation water potential(IWP)under RCP4.5 revealed that strategic shifts in sowing dates can substantially alter water requirements;for instance,advancing the winter-spring sowing to December 5th decreased IWP by 15.6%in the 2041-2070 period,while delaying summer-autumn crop sowing to April 20th increased IWP by 48.6%due to greater reliance on irrigation as rainfall patterns shift.Similar dynamic responses were observed for the 2071-2099 period and for autumn-winter crops.These findings underscore that AquaCrop modeling can effectively predict future irrigation needs and that adjusting cultivation calendars presents a viable,low-cost adaptation strategy.This approach allows farmers in the Plain of Reeds to optimize rainwater use,thereby reducing dependency on supplementary irrigation and mitigating the adverse impacts of climate variability,contributing to more sustainable agricultural water management.展开更多
Extensive flooding swept across large areas of Central Asia,mainly over Kazakhstan and southwestern Russia,from late March to April 2024.It was reported to be the worst flooding in the area in the past 70 years and ca...Extensive flooding swept across large areas of Central Asia,mainly over Kazakhstan and southwestern Russia,from late March to April 2024.It was reported to be the worst flooding in the area in the past 70 years and caused widespread devastation to society and infrastructure.However,the drivers of this record-breaking flood remain unexplored.Here,we show that the record-breaking floods were contributed by both long-term climate warming and interannual variability,with multiple climatic drivers at play across the synoptic to seasonal timescales.First,the heavy snowmelt in March 2024 was associated with above-normal preceding winter snow accumulation.Second,extreme rainfall was at a record-high during March 2024,in line with its increasing trend under climate warming.Third,the snowmelt and extreme rainfall in March were compounded by record-high soil moisture conditions in the preceding winter,which was a result of interannual variability and related to excessive winter rainfall over Central Asia.As climate warming continues,the interplay between the increasing trend of extreme rainfall,interannual variations in soil moisture pre-conditions,as well as shifting timing and magnitudes of spring snowmelt,will further increase and complicate spring flooding risks.This is a growing and widespread challenge for the mid-to high-latitude regions.展开更多
This study characterizes the instrumental record of California climate for the last 170 years.Our goal is to look for hydrologic variability at decadal and longer time scales that would be consistent with paleoclimate...This study characterizes the instrumental record of California climate for the last 170 years.Our goal is to look for hydrologic variability at decadal and longer time scales that would be consistent with paleoclimate estimates of hydrologic variability in California for the last 3000 years.Our study focuses on meteorological summaries of annual precipitation and temperature.The precipitation records go back as far as 1850;the temperature records go back as far as 1880.California hydrologic records show strong variability at the interannual level due to ENSO forcing.They also all show a strong decadal(∼14 yr)cyclicity and evidence for multi-decadal to centennial variability that is consistent with California paleoclimate studies.California temperature records show a long-term warming of 5°F-6°F(2.8°C-3.4°C)associated with global warming,but there is no evidence for a similar long-term trend in hydrologic variability.Long-term Pacific Ocean variability adjacent to central and northern California,Pacific Decadal Oscillation(PDO)and North Pacific Gyre Oscillation(NPGO),show a similar decadal to centennial pattern of variability that we associate with our long-term hydrologic variability.The positive phase of the NPGO and the negative phase of the PDO are associated with the decadal scale(∼14 yr)dry cycles in California for the last 70 years.展开更多
Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into...Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into photosynthesis. It is very sensible for factors affecting on vegetation variability such as climate, soils, plant characteristics and human activities. So, it can be used as an indicator of actual and potential trend of vegetation. In this study we used the actual NPP which was derived from MODIS to assess the response of NPP to climate variables in Gadarif State, from 2000 to 2010. The correlations between NPP and climate variables (temperature and precipitation) are calculated using Pearson’s Correlation Coefficient and ordinary least squares regression. The main results show the following 1) the correlation Coefficient between NPP and mean annual temperature is Somewhat negative for Feshaga, Rahd, Gadarif and Galabat areas and weakly negative in Faw area;2) the correlation Coefficient between NPP and annual total precipitation is weakly negative in Faw, Rahd and Galabat areas and somewhat negative in Galabat and Rahd areas. This study demonstrated that the correlation analysis between NPP and climate variables (precipitation and temperature) gives reliably result of NPP responses to climate variables that is clearly in a very large scale of study area.展开更多
A wide variety of studies have estimated the magnitude of global terrestrial net primary production （NPP）, but its variations, both spatially and temporally, still remain uncertain. By using an improved process-base...A wide variety of studies have estimated the magnitude of global terrestrial net primary production （NPP）, but its variations, both spatially and temporally, still remain uncertain. By using an improved process-based terrestrial ecosystem model （DLEM, Dynamic Land Ecosystem Model）, we provide an estimate of global terrestrial NPP induced by multiple environmental factors and examine the response of terrestrial NPP to climate variability at biome and global levels and along latitudes throughout the first decade of the 21st century. The model simulation estimates an average global terrestrial NPP of 54.6 Pg C yr-1 during 2000-2009, varying from 52.8 Pg C yr-1 in the dry year of 2002 to 56.4 Pg C yr-1 in the wet year of 2008. In wet years, a large increase in terrestrial NPP compared to the decadal mean was prevalent in Amazonia, Africa and Australia. In dry years, however, we found a 3.2% reduction in global terrestrial NPP compared to the decadal mean, primarily due to limited moisture supply in tropical regions. At a global level, precipitation explained approximately 63% of the variation in terrestrial NPP, while the rest was attributed to changes in temperature and other environmental factors. Precipitation was the major factor determining inter-annual variation in terrestrial NPP in low-latitude regions. However, in midand high-latitude regions, temperature variability largely controlled the magnitude of terrestrial NPP. Our results imply that pro- jected climate warming and increasing climate extreme events would alter the magnitude and spatiotemporal patterns of global terrestrial NPP.展开更多
As the largest wetland in the North China Plain （NCP）, the Baiyangdian Lake plays an important role in maintaining water balance and ecological health of NCP. Ir the past few decades, the decreasing streamflow in th...As the largest wetland in the North China Plain （NCP）, the Baiyangdian Lake plays an important role in maintaining water balance and ecological health of NCP. Ir the past few decades, the decreasing streamflow in the Baiyangdian Basin associated with climate vari- ability and human activities has caused a series of water and eco-environmer,tal issues. In this study, we quantified the impacts of climate variability and human activities on streamflow in the water source area of the Baiyangdian Lake, based on analyses of hydrologic changes of the upper Tanghe river catchment （a sub-basin of the Baiyangdian Basin） from 1960 to 2008. Climate elasticity method and hydrological modeling method were used to distinguish the effects of climate variability and human activities. The results showed that the annual streamflow decreased significantly （P〉0.05） by 1.7 mm/a and an abrupt change was identi- fied around the year 1980. The quantification results indicated that climate variations ac- counted for 38%-40% of decreased streamflow, while human activities accounted for 60%--62%. Therefore, the effect of human activities played a dominant role on the decline of the streamflow in the water source area of the Baiyangdian Lake. To keep the ecosystem health of the Baiyangdian Lake, we suggest that minimum ecological water demand and in- tegrated watershed management should be guaranteed in the future.展开更多
Based on a 200 year simulation and reanalysis data (1980–1996), the general characteristics of East Asian monsoon (EAM) were analyzed in the first part of the paper. It is clear from this re-search that the South Asi...Based on a 200 year simulation and reanalysis data (1980–1996), the general characteristics of East Asian monsoon (EAM) were analyzed in the first part of the paper. It is clear from this re-search that the South Asian monsoon (SAM) defined by Webster and Yang (1992) is geographically and dynamically different from the East Asian monsoon (EAM). The region of the monsoon defined by Webster and Yang (1992) is located in the tropical region of Asia (40–110°E, 10–20°N), including the Indian monsoon and the Southeast Asian monsoon, while the EAM de-fined in this paper is located in the subtropical region of East Asia (110–125°E, 20–40°N). The components and the seasonal variations of the SAM and EAM are different and they characterize the tropical and subtropical Asian monsoon systems respectively. A suitable index (EAMI) for East Asian monsoon was then defined to describe the strength of EAM in this paper. In the second part of the paper, the interannual variability of EAM and its relationship with sea surface temperature (SST) in the 200 year simulation were studied by using the composite method, wavelet transformation, and the moving correlation coefficient method. The summer EAMI is negatively correlated with ENSO (El Nino and Southern Oscillation) cycle represented by the NINO3 sea surface temperature anomaly (SSTA) in the preceding April and January, while the winter EAM is closely correlated with the succeeding spring SST over the Pacific in the coupled model. The general differences of EAM between El Nino and La Nina cases were studied in the model through composite analysis. It was also revealed that the dominating time scales of EAM variability may change in the long-term variation and the strength may also change. The anoma-lous winter EAM may have some correlation with the succeeding summer EAM, but this relation-ship may disappear sometimes in the long-term climate variation. Such time-dependence was found in the relationship between EAM and SST in the long-term climate simulation as well. Key words East Asian monsoon - Interannual variability - Coupled climate model The author wishes to thank Profs. Wu G.X., Zhang X.H., and Dr. Yu Y.Q. for providing the coupled model re-sults. Dr. Yu also kindly provided assistance in using the model output. This work was supported jointly by the Na-tional Natural Science Foundation of China key project ’ The analysis on the seasonal-to-interannual variation of the general circulation’ under contract 49735160 and Chinese Academy of Sciences key project ’ The Interannual Va-riability and Predictability of East Asian Monsoon’.展开更多
Climate in China's Mainland can be divided into the monsoon region in the southeast and the westerly region in the northwest as well as the intercross zone, i.e., the monsoon northernmost marginal active zone that...Climate in China's Mainland can be divided into the monsoon region in the southeast and the westerly region in the northwest as well as the intercross zone, i.e., the monsoon northernmost marginal active zone that is oriented from Southwest China to the upper Yellow River, North China, and Northeast China. In the three regions, dry-wet climate changes are directly linked to the interaction of the southerly monsoon flow on the east side of the Tibetan Plateau and the westerly flow on the north side of the Plateau from the inter-annual to inter-decadal timescales. Some basic features of climate variability in the three regions for the last half century and the historical hundreds of years are reviewed in this paper. In the last half century, an increasing trend of summer precipitation associated with the enhancing westerly flow is found in the westerly region from Xinjiang to northern parts of North China and Northeast China. On the other hand, an increasing trend of summer precipitation along the Yangtze River and a decreasing trend of summer precipitation along the monsoon northernmost marginal active zone are associated with the weakening monsoon flow in East Asia. Historical documents are widely distributed in the monsoon region for hundreds of years and natural climate proxies are constructed in the non-monsoon region, while two types of climate proxies can be commonly found over the monsoon northernmost marginal active zone. In the monsoon region, dry-wet variation centers are altered among North China, the lower Yangtze River, and South China from one century to another. Dry or wet anomalies are firstly observed along the monsoon northernmost marginal active zone and shifted southward or southeastward to the Yangtze River valley and South China in about a 70-year timescale. Severe drought events are experienced along the monsoon northernmost marginal active zone during the last 5 centuries. Inter-decadal dry-wet variations are depicted by natural proxies for the last 4-5 centuries in several areas over the non-monsoon region. Some questions, such as the impact of global warming on dry-wet regime changes in China, complex interactions between the monsoon and westerly flows in Northeast China, and the integrated multi-proxy analysis throughout all of China, are proposed.展开更多
The Qinghai-Xizang Plateau, or Tibetan Plateau, is a sensitive region for climate change, where the manifestation of global warming is particularly noticeable. The wide climate variability in this region significantly...The Qinghai-Xizang Plateau, or Tibetan Plateau, is a sensitive region for climate change, where the manifestation of global warming is particularly noticeable. The wide climate variability in this region significantly affects the local land ecosystem and could consequently lead to notable vegetation changes. In this paper, the interannual variations of the plateau vegetation are investigated using a 21-year normalized difference vegetation index （NDVI） dataset to quantify the consequences of climate warming for the regional ecosystem and its interactions. The results show that vegetation coverage is best in the eastern and southern plateau regions and deteriorates toward the west and north. On the whole, vegetation activity demonstrates a gradual enhancement in an oscillatory manner during 1982-2002. The temporal variation also exhibits striking regional differences： an increasing trend is most apparent in the west, south, north and southeast, whereas a decreasing trend is present along the southern plateau boundary and in the central-east region. Covariance analysis between the NDVI and surface temperature/precipitation suggests that vegetation change is closely related to climate change. However, the controlling physical processes vary geographically. In the west and east, vegetation variability is found to be driven predominantly by temperature, with the impact of precipitation being of secondary importance. In the central plateau, however, temperature and precipitation factors are equally important in modulating the interannual vegetation variability.展开更多
Time-variable gravity data from the Gravity Recovery and Climate Experiment （GRACE） satellite mission are used to study terrestrial water storage （TWS） changes over the Pearl River Basin （PRB） for the period 200...Time-variable gravity data from the Gravity Recovery and Climate Experiment （GRACE） satellite mission are used to study terrestrial water storage （TWS） changes over the Pearl River Basin （PRB） for the period 2003-Nov. 2014. TWS estimates from GRACE generally show good agreement with those from two hydrological models GLDAS and WGHM. But they show different capability of detecting significant TWS changes over the PRB. Among them, WGHM is likely to underestimate the seasonal variability of TWS, while GRACE detects long- term water depletions over the upper PRB as was done by hydrological models, and observes significant water increases around the Longtan Reservoir （LTR） due to water impoundment. The heavy drought in 2011 caused by the persistent precipitation deficit has resulted in extreme low surface runoff and water level of the LTR. Moreover, large variability of summer and autumn precipitation may easily trigger floods and droughts in the rainy season in the PRB, especially for summer, as a high correlation of 0.89 was found between precipitation and surface runoff. Generally, the PRB TWS was negatively correlated with El Nifio-Southern Oscillation （ENSO） events. However, the modulation of the Pacific Decadal Oscillation （PDO） may impact this relationship, and the significant TWS anomaly was likely to occur in the peak of PDO phase as they agree well in both of the magnitude and timing of peaks. This indicates that GRACE-based TWS could be a valuable parameter for studying climatic in- fluences in the PRB.展开更多
Using the low-resolution （T31, equivalent to 3.75°× 3.75°） version of the Community Earth System Model （CESM） from the National Center for Atmospheric Research （NCAR）, a global climate simulation ...Using the low-resolution （T31, equivalent to 3.75°× 3.75°） version of the Community Earth System Model （CESM） from the National Center for Atmospheric Research （NCAR）, a global climate simulation was carried out with fixed external forcing factors （1850 Common Era. （C.E.） conditions） for the past 2000 years. Based on the simulated results, spatio-temporal structures of surface air temperature, precipitation and internal variability, such as the E1 Nifio-Southem Oscillation （ENSO）, the Atlantic Multi-decadal Oscilla- tion （AMO）, the Pacific Decadal Oscillation （PDO）, and the North Atlantic Oscillation （NAO）, were compared with reanalysis datasets to evaluate the model performance. The results are as follows： 1） CESM showed a good performance in the long-term simulation and no significant climate drift over the past 2000 years; 2） climatological patterns of global and regional climate changes simulated by the CESM were reasonable compared with the reanalysis datasets; and 3） the CESM simulated internal natural variability of the climate system performs very well. The model not only reproduced the periodicity of ENSO, AMO and PDO events but also the 3-8 years vari- ability of the ENSO. The spatial distribution of the CESM-simulated NAO was also similar to the observed. However, because of weaker total irradiation and greenhouse gas concentration forcing in the simulation than the present, the model performances had some differences from the observations. Generally, the CESM showed a good performance in simulating the global climate and internal natu- ral variability of the climate system. This paves the way for other forced climate simulations for the past 2000 years by using the CESM.展开更多
Studies indicate that the climate has experienced a dramatic change in the Heihe River Basin with scope of temperature rise reaching 0.5-1.1 o C in the 1990s compared to the mean value of the per...Studies indicate that the climate has experienced a dramatic change in the Heihe River Basin with scope of temperature rise reaching 0.5-1.1 o C in the 1990s compared to the mean value of the period 1960-1990, precipitation increased 18.5 mm in the 1990s compared to the 1950s, and 6.5 mm in the 1990s compared to the mean value of the period 1960-1990, water resources decreased 2.6×10 8 m 3 in the 1990s compared to the 1950s, and 0.4×10 8 m 3 in the 1990s compared to the mean value of the period 1960-1990. These changes have exerted a greater effect on the local environment and socio-economy, and also made the condition worsening in water resources utilizations in the Heihe Rver Basin.展开更多
We developed a sophisticated method to depict the spatial and seasonal characterization of net primary productivity (NPP) and climate variables. The role of climate variability in the seasonal variation of NPP exerts ...We developed a sophisticated method to depict the spatial and seasonal characterization of net primary productivity (NPP) and climate variables. The role of climate variability in the seasonal variation of NPP exerts delayed and continuous effects. This study expands on this by mapping the seasonal characterization of NPP and climate variables from space using geographic information system (GIS) technology at the pixel level. Our approach was developed in southeastern China using moderate-resolution imaging spectroradiometer (MODIS) data. The results showed that air temperature,precipitation and sunshine percentage contributed significantly to seasonal variation of NPP. In the northern portion of the study area,a significant positive 32-d lagged correlation was observed between seasonal variation of NPP and climate (P<0.01),and the influences of changing climate on NPP lasted for 48 d or 64 d. In central southeastern China,NPP showed 16-d,48-d,and 96-d lagged correlation with air temperature,precipitation,and sunshine percentage,respectively (P<0.01); the influences of air temperature and precipitation on NPP lasted for 48 d or 64 d,while sunshine influence on NPP only persisted for 16 d. Due to complex topography and vegetation distribution in the southern part of the study region,the spatial patterns of vegetation-climate relationship became complicated and diversiform,especially for precipitation influences on NPP. In the northern part of the study area,all vegetation NPP had an almost similar response to seasonal variation of air temperature except for broad crops. The impacts of seasonal variation of precipitation and sunshine on broad and cereal crop NPP were slightly different from other vegetation NPP.展开更多
In terms of the modular fuzzy neural network (MFNN) combining fuzzy c-mean (FCM) cluster and single-layer neural network, a short-term climate prediction model is developed. It is found from modeling results that the ...In terms of the modular fuzzy neural network (MFNN) combining fuzzy c-mean (FCM) cluster and single-layer neural network, a short-term climate prediction model is developed. It is found from modeling results that the MFNN model for short-term climate prediction has advantages of simple structure, no hidden layer and stable network parameters because of the assembling of sound functions of the self-adaptive learning, association and fuzzy information processing of fuzzy mathematics and neural network methods. The case computational results of Guangxi flood season (JJA) rainfall show that the mean absolute error (MAE) and mean relative error (MRE) of the prediction during 1998-2002 are 68.8 mm and 9.78%, and in comparison with the regression method, under the conditions of the same predictors and period they are 97.8 mm and 12.28% respectively. Furthermore, it is also found from the stability analysis of the modular model that the change of the prediction results of independent samples with training times in the stably convergent interval of the model is less than 1.3 mm. The obvious oscillation phenomenon of prediction results with training times, such as in the common back-propagation neural network (BPNN) model, does not occur, indicating a better practical application potential of the MFNN model.展开更多
Taoer River Basin, which is located in the west of Northeast China, is an agropastoral ecotone. In recent years, the hydrological cycle and water resources have changed significantly with the deterioration of the envi...Taoer River Basin, which is located in the west of Northeast China, is an agropastoral ecotone. In recent years, the hydrological cycle and water resources have changed significantly with the deterioration of the environment. Many water problems such as river blanking, wetland shrinking and salinization have occurred in this region. All of these phenomena were directly caused by changes in stream flow under climate variability and human actiities. In light of the situation, the impact of climate variability and human activities on stream flow should be identified immediately to identify the primary driving factors of basin hydrological processes. To achieve this, statistical tests were applied to identify trends in variation and catastrophe points in mean annual stream flow from 1961 to 2011. A runoff sensitive coefficients method and a SIMHYD model were applied to assess the impacts of stream flow variation. The following conclusions were found： 1 ） The years 1985 and 2000 were confirmed to be catastrophe points in the stream flow series. Thus, the study period could be divided into three periods, from 1961 to 1985 （Period I）, 1986 to 2000 （Period II） and 2001 to 2011 （Period III）. 2） Mean annual observed stream flow was 31.54 mm in Period I, then increased to 65.60 mm in Period II and decreased to 2.92 mm in Period III. 3） Using runoff sensitive coefficients, the contribution of climate variability was 41.93% and 43.14% of the increase in stream flow during Periods II and III, suggesting that the contribution of human activities to the increase was 58.07% and 56.86%, respectively. 4） Climate variability accounted for 42.57% and 44.30% of the decrease in stream flow, while human activities accounted for 57.43% and 55.70% of the decrease, according to the SIMHYD model. 5） In comparison of these two methods, the primary driving factors of stream flow variation could be considered to be human activities, which contributed about 15% more than climate variability. It is hoped that these conclusions will .benefit future regional planning and sustainable development.展开更多
Climate variability and change are among the biggest challenges of the 21st century. Like in many other areas globally, the coastal communities of Tanzania have always been facing climatic variability at various time ...Climate variability and change are among the biggest challenges of the 21st century. Like in many other areas globally, the coastal communities of Tanzania have always been facing climatic variability at various time scales. Using focus group discussion and a household survey, this study analyzes the perceptions of climate variability and change and the strategies for coping and adaptation by the selected coastal rural and peri-urban communities in Tanzania. The perception of climate variability and change is complemented with the time-series analysis of rainfall and temperature data from Julius Nyerere International Airport Met. station and Kisarawe using Instant Statistical Software. Results indicate that households are aware of climate variability and identify indicators of climate change and variability as being decreasing rainfall trends, increasing incidences of droughts, unpredictable rainfall patterns, disappearance of wetlands and failure to predict on-set of rainy season using traditional knowledge. Households primarily attribute reduced crop yields to changes in rainfall pattern and increasing incidences of drought leading to soil moisture stress. The implications are that the agriculture dependent households are now food insecure. As a way of coping to the observed changes, the coastal communities among others have shifted to production of high value horticultural crops and use of forest resources. Nevertheless, the increased use of forest resources is threatening the existence of coastal forests and contributes to the decline of forest resources and disappearance of wildlife in the forest reserves. It is concluded that the communities studied are aware of climate issues as revealed from perceived indicators of climate variability and changes. The results from statistical analysis of 30 years climatic data are consistent with community’s perception of climate variability and change. The study recommends examining the present coping strategies for the sustainability of the coastal forests and in designing of alternative adaptive strategies such as alternative energy options, crop diversification and environmental friendly activities such as beekeeping.展开更多
Much attention has recently been focused on the effects of climate variability and human activities on the runoff. In this study, we analyzed 56-yr(1957–2012) runoff change and patterns in the Jinghe River Basin(JRB)...Much attention has recently been focused on the effects of climate variability and human activities on the runoff. In this study, we analyzed 56-yr(1957–2012) runoff change and patterns in the Jinghe River Basin(JRB) in the arid region of northwest China. The nonparametric Mann–Kendall test and the precipitation-runoff double cumulative curve(PRDCC) were used to identify change trend and abrupt change points in the annual runoff. It was found that the runoff in the JRB has periodically fluctuated in the past 56 yr. Abrupt change point in annual runoff was identified in the JRB, which occurred in the years around 1964 and 1996 dividing the long-term hydrologic series into a natural period(1957 – 1964) and a climate and man-induced period(1965 – 1996 and 1997 – 2012). In the 1965 – 1996 period, human activities were the main factor that decreased runoff with contribution of 88.9%, while climate variability only accounted for 11.1%. However,the impact of climate variability has been increased from 11.1% to 47.5% during 1997 – 2012, showing that runoff in JRB is more sensitive to climate variability during global warming. This study distinguishes theeffect of climate variability from human activities on runoff, which can do duty for a reference for regional water resources assessment and management.展开更多
Global warming and climate change is one of the most extensively researched and discussed topical issues affecting the environment.Although there are enough historical evidence to support the theory that climate chang...Global warming and climate change is one of the most extensively researched and discussed topical issues affecting the environment.Although there are enough historical evidence to support the theory that climate change is a natural phenomenon,many research scientists are widely in agreement that the increase in temperature in the 20 th century is anthropologically related.The associated effects are the variability of rainfall and cyclonic patterns that are being observed globally.In Southeast Asia the link between global warming and the seasonal atmospheric flow during the monsoon seasons shows varying degree of fuzziness.This study investigates the impact of climate change on the seasonality of monsoon Asia and its effect on the variability of monsoon rainfall in Southeast Asia.The comparison of decadal variation of precipitation and temperature anomalies before the 1970 s found general increases which were mostly varying.But beyond the 1970 s,global precipitation anomalous showed increases that almost corresponded with increases in global temperature anomalies for the same period.There are frequent changes and a shift westward of the Indian summer monsoon.Although precipitation is observed to be 70%below normal levels,in some areas the topography affects the intensity of rainfall.These shifting phenomenon of other monsoon season in the region are impacting on the variability of rainfall and the onset of monsoons in Southeast Asia and is predicted to delay for 15 days the onset of the monsoon in the future.The variability of monsoon rainfall in the SEA region is observed to be decadal and the frequency and intensity of intermittent flooding of some areas during the monsoon season have serious consequences on the human,financial,infrastructure and food security of the region.展开更多
基金supported by the Research Innovation Program for college graduates of Jiangsu Province (CXLX13 487)
文摘A coupled earth system model（ESM） has been developed at the Nanjing University of Information Science and Technology（NUIST） by using version 5.3 of the European Centre Hamburg Model（ECHAM）, version 3.4 of the Nucleus for European Modelling of the Ocean（NEMO）, and version 4.1 of the Los Alamos sea ice model（CICE）. The model is referred to as NUIST ESM1（NESM1）. Comprehensive and quantitative metrics are used to assess the model＇s major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model＇s assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring–fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific（CP）-ENSO and eastern Pacific（EP）-ENSO; however, the equatorial SST variability,biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden–Julian Oscillation（MJO）, and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version（T159） demonstrates improved simulation with respect to the climatology, interannual variance, monsoon–ENSO lead–lag correlation, spatial structures of the leading mode of the Asian–Australian monsoon rainfall variability, and the eastward propagation of the MJO.
文摘The Boreal forest is a terrestrial ecosystem highly vulnerable to the impacts of short-term climate and weather variabilities. Detecting abrupt, rapid climate-induced changes in fire weather and related changes in fire seasonality can provide important insights to assessing impacts of climate change on forestry. This paper, taking the Sakha Republic of Russia as study area, aims to suggest an approach for detecting signals indicating climate-induced changes in fire weather to express recent fire weather variability by using short-term ranks of major meteorological parameters such as air temperature and atmospheric precipitation. Climate data from the “Global Summary of the Day Product” of NOAA (the United States National Oceanic and Atmospheric Administration) for 1996 to 2018 were used to investigate meteorological parameters that drive fire activity. The detection of the climate change signals is made through a 4-step analysis. First, we used descriptive statistics to grasp monthly, annual, seasonal and peak fire period characteristics of fire weather. Then we computed historical normals for WMO reference period, 1961-1990, and the most recent 30-year period for comparison with the current means. The variability of fire weather is analyzed using standard deviation, coefficient of variation, percentage departures from historical normals, percentage departures from the mean, and precipitation concentration index. Inconsistency and abrupt changes in the evolution of fire weather are assessed using homogeneity analysis whilst a Mann-Kendall test is used to detect significant trends in the time series. The results indicate a significant increase of temperature during spring and fall months, which extends the fire season and potentially contributes to increase of burned areas. We again detected a significant rainfall shortage in September which extended the fire season. Furthermore, this study suggests a new approach in statistical methods appropriate for the detection of climate change signals on fire weather variability using short-term climate ranks and evaluation of its impact on fire seasonality and activity.
文摘Climate variability significantly impacts agricultural water resources,particularly in regions like Vietnam's Plain of Reeds that heavily utilize rain-fed conditions.This study employs the FAO-AquaCrop model to estimate current and future irrigation water needs for rice cultivation in this critical subregion,aiming to identify optimal sowing schedules(OSS)that enhance rainwater utilization and reduce irrigation dependency.The model was driven by current climate data and future projections(2041-2070 and 2071-2099)derived from downscaled Global Circulation Models under RCP4.5 and RCP8.5 scenarios.The AquaCrop model demonstrated robust performance during validation and calibration,with d-values(0.82-0.93)and R²values(0.85-0.92)indicating strong predictive accuracy for rice yield.Simulation results for efficient irrigation water potential(IWP)under RCP4.5 revealed that strategic shifts in sowing dates can substantially alter water requirements;for instance,advancing the winter-spring sowing to December 5th decreased IWP by 15.6%in the 2041-2070 period,while delaying summer-autumn crop sowing to April 20th increased IWP by 48.6%due to greater reliance on irrigation as rainfall patterns shift.Similar dynamic responses were observed for the 2071-2099 period and for autumn-winter crops.These findings underscore that AquaCrop modeling can effectively predict future irrigation needs and that adjusting cultivation calendars presents a viable,low-cost adaptation strategy.This approach allows farmers in the Plain of Reeds to optimize rainwater use,thereby reducing dependency on supplementary irrigation and mitigating the adverse impacts of climate variability,contributing to more sustainable agricultural water management.
基金jointly supported by the National Natural Science Foundation of China(Grant Nos.42422502,42275038)the China Meteorological Administration Climate Change Special Program(Grant No.QBZ202306)。
文摘Extensive flooding swept across large areas of Central Asia,mainly over Kazakhstan and southwestern Russia,from late March to April 2024.It was reported to be the worst flooding in the area in the past 70 years and caused widespread devastation to society and infrastructure.However,the drivers of this record-breaking flood remain unexplored.Here,we show that the record-breaking floods were contributed by both long-term climate warming and interannual variability,with multiple climatic drivers at play across the synoptic to seasonal timescales.First,the heavy snowmelt in March 2024 was associated with above-normal preceding winter snow accumulation.Second,extreme rainfall was at a record-high during March 2024,in line with its increasing trend under climate warming.Third,the snowmelt and extreme rainfall in March were compounded by record-high soil moisture conditions in the preceding winter,which was a result of interannual variability and related to excessive winter rainfall over Central Asia.As climate warming continues,the interplay between the increasing trend of extreme rainfall,interannual variations in soil moisture pre-conditions,as well as shifting timing and magnitudes of spring snowmelt,will further increase and complicate spring flooding risks.This is a growing and widespread challenge for the mid-to high-latitude regions.
文摘This study characterizes the instrumental record of California climate for the last 170 years.Our goal is to look for hydrologic variability at decadal and longer time scales that would be consistent with paleoclimate estimates of hydrologic variability in California for the last 3000 years.Our study focuses on meteorological summaries of annual precipitation and temperature.The precipitation records go back as far as 1850;the temperature records go back as far as 1880.California hydrologic records show strong variability at the interannual level due to ENSO forcing.They also all show a strong decadal(∼14 yr)cyclicity and evidence for multi-decadal to centennial variability that is consistent with California paleoclimate studies.California temperature records show a long-term warming of 5°F-6°F(2.8°C-3.4°C)associated with global warming,but there is no evidence for a similar long-term trend in hydrologic variability.Long-term Pacific Ocean variability adjacent to central and northern California,Pacific Decadal Oscillation(PDO)and North Pacific Gyre Oscillation(NPGO),show a similar decadal to centennial pattern of variability that we associate with our long-term hydrologic variability.The positive phase of the NPGO and the negative phase of the PDO are associated with the decadal scale(∼14 yr)dry cycles in California for the last 70 years.
文摘Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into photosynthesis. It is very sensible for factors affecting on vegetation variability such as climate, soils, plant characteristics and human activities. So, it can be used as an indicator of actual and potential trend of vegetation. In this study we used the actual NPP which was derived from MODIS to assess the response of NPP to climate variables in Gadarif State, from 2000 to 2010. The correlations between NPP and climate variables (temperature and precipitation) are calculated using Pearson’s Correlation Coefficient and ordinary least squares regression. The main results show the following 1) the correlation Coefficient between NPP and mean annual temperature is Somewhat negative for Feshaga, Rahd, Gadarif and Galabat areas and weakly negative in Faw area;2) the correlation Coefficient between NPP and annual total precipitation is weakly negative in Faw, Rahd and Galabat areas and somewhat negative in Galabat and Rahd areas. This study demonstrated that the correlation analysis between NPP and climate variables (precipitation and temperature) gives reliably result of NPP responses to climate variables that is clearly in a very large scale of study area.
基金NSF Decadal and Regional Climate Prediction using Earth System Models,No.AGS-1243220NSF Dynamics of Coupled Natural and Human Systems,No.1210360+2 种基金NSF Computer and Network Systems,No.CNS-1059376NASA Land Cover/Land Use Change Program,No.NNX08AL73G S01NASA Interdisciplinary Science Program,No.NNX10AU06G,No.NNX11AD47G
文摘A wide variety of studies have estimated the magnitude of global terrestrial net primary production （NPP）, but its variations, both spatially and temporally, still remain uncertain. By using an improved process-based terrestrial ecosystem model （DLEM, Dynamic Land Ecosystem Model）, we provide an estimate of global terrestrial NPP induced by multiple environmental factors and examine the response of terrestrial NPP to climate variability at biome and global levels and along latitudes throughout the first decade of the 21st century. The model simulation estimates an average global terrestrial NPP of 54.6 Pg C yr-1 during 2000-2009, varying from 52.8 Pg C yr-1 in the dry year of 2002 to 56.4 Pg C yr-1 in the wet year of 2008. In wet years, a large increase in terrestrial NPP compared to the decadal mean was prevalent in Amazonia, Africa and Australia. In dry years, however, we found a 3.2% reduction in global terrestrial NPP compared to the decadal mean, primarily due to limited moisture supply in tropical regions. At a global level, precipitation explained approximately 63% of the variation in terrestrial NPP, while the rest was attributed to changes in temperature and other environmental factors. Precipitation was the major factor determining inter-annual variation in terrestrial NPP in low-latitude regions. However, in midand high-latitude regions, temperature variability largely controlled the magnitude of terrestrial NPP. Our results imply that pro- jected climate warming and increasing climate extreme events would alter the magnitude and spatiotemporal patterns of global terrestrial NPP.
基金National Basic Research Program of China,No.2010CB428406National Natural Science Foundation of China,No.40830636No.40971023
文摘As the largest wetland in the North China Plain （NCP）, the Baiyangdian Lake plays an important role in maintaining water balance and ecological health of NCP. Ir the past few decades, the decreasing streamflow in the Baiyangdian Basin associated with climate vari- ability and human activities has caused a series of water and eco-environmer,tal issues. In this study, we quantified the impacts of climate variability and human activities on streamflow in the water source area of the Baiyangdian Lake, based on analyses of hydrologic changes of the upper Tanghe river catchment （a sub-basin of the Baiyangdian Basin） from 1960 to 2008. Climate elasticity method and hydrological modeling method were used to distinguish the effects of climate variability and human activities. The results showed that the annual streamflow decreased significantly （P〉0.05） by 1.7 mm/a and an abrupt change was identi- fied around the year 1980. The quantification results indicated that climate variations ac- counted for 38%-40% of decreased streamflow, while human activities accounted for 60%--62%. Therefore, the effect of human activities played a dominant role on the decline of the streamflow in the water source area of the Baiyangdian Lake. To keep the ecosystem health of the Baiyangdian Lake, we suggest that minimum ecological water demand and in- tegrated watershed management should be guaranteed in the future.
文摘Based on a 200 year simulation and reanalysis data (1980–1996), the general characteristics of East Asian monsoon (EAM) were analyzed in the first part of the paper. It is clear from this re-search that the South Asian monsoon (SAM) defined by Webster and Yang (1992) is geographically and dynamically different from the East Asian monsoon (EAM). The region of the monsoon defined by Webster and Yang (1992) is located in the tropical region of Asia (40–110°E, 10–20°N), including the Indian monsoon and the Southeast Asian monsoon, while the EAM de-fined in this paper is located in the subtropical region of East Asia (110–125°E, 20–40°N). The components and the seasonal variations of the SAM and EAM are different and they characterize the tropical and subtropical Asian monsoon systems respectively. A suitable index (EAMI) for East Asian monsoon was then defined to describe the strength of EAM in this paper. In the second part of the paper, the interannual variability of EAM and its relationship with sea surface temperature (SST) in the 200 year simulation were studied by using the composite method, wavelet transformation, and the moving correlation coefficient method. The summer EAMI is negatively correlated with ENSO (El Nino and Southern Oscillation) cycle represented by the NINO3 sea surface temperature anomaly (SSTA) in the preceding April and January, while the winter EAM is closely correlated with the succeeding spring SST over the Pacific in the coupled model. The general differences of EAM between El Nino and La Nina cases were studied in the model through composite analysis. It was also revealed that the dominating time scales of EAM variability may change in the long-term variation and the strength may also change. The anoma-lous winter EAM may have some correlation with the succeeding summer EAM, but this relation-ship may disappear sometimes in the long-term climate variation. Such time-dependence was found in the relationship between EAM and SST in the long-term climate simulation as well. Key words East Asian monsoon - Interannual variability - Coupled climate model The author wishes to thank Profs. Wu G.X., Zhang X.H., and Dr. Yu Y.Q. for providing the coupled model re-sults. Dr. Yu also kindly provided assistance in using the model output. This work was supported jointly by the Na-tional Natural Science Foundation of China key project ’ The analysis on the seasonal-to-interannual variation of the general circulation’ under contract 49735160 and Chinese Academy of Sciences key project ’ The Interannual Va-riability and Predictability of East Asian Monsoon’.
基金supported by the National Natural Science Foundation of China(Nos40890053,90502001,and 90711003)
文摘Climate in China's Mainland can be divided into the monsoon region in the southeast and the westerly region in the northwest as well as the intercross zone, i.e., the monsoon northernmost marginal active zone that is oriented from Southwest China to the upper Yellow River, North China, and Northeast China. In the three regions, dry-wet climate changes are directly linked to the interaction of the southerly monsoon flow on the east side of the Tibetan Plateau and the westerly flow on the north side of the Plateau from the inter-annual to inter-decadal timescales. Some basic features of climate variability in the three regions for the last half century and the historical hundreds of years are reviewed in this paper. In the last half century, an increasing trend of summer precipitation associated with the enhancing westerly flow is found in the westerly region from Xinjiang to northern parts of North China and Northeast China. On the other hand, an increasing trend of summer precipitation along the Yangtze River and a decreasing trend of summer precipitation along the monsoon northernmost marginal active zone are associated with the weakening monsoon flow in East Asia. Historical documents are widely distributed in the monsoon region for hundreds of years and natural climate proxies are constructed in the non-monsoon region, while two types of climate proxies can be commonly found over the monsoon northernmost marginal active zone. In the monsoon region, dry-wet variation centers are altered among North China, the lower Yangtze River, and South China from one century to another. Dry or wet anomalies are firstly observed along the monsoon northernmost marginal active zone and shifted southward or southeastward to the Yangtze River valley and South China in about a 70-year timescale. Severe drought events are experienced along the monsoon northernmost marginal active zone during the last 5 centuries. Inter-decadal dry-wet variations are depicted by natural proxies for the last 4-5 centuries in several areas over the non-monsoon region. Some questions, such as the impact of global warming on dry-wet regime changes in China, complex interactions between the monsoon and westerly flows in Northeast China, and the integrated multi-proxy analysis throughout all of China, are proposed.
基金supported by the foundation from:the program of the National Natural Science Foundation of China(40675037)the key program of the Sichuan Province Youth Science and Technology Fund(05ZQ026-023)the opening project of the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics,Chinese Academy of Sciences.
文摘The Qinghai-Xizang Plateau, or Tibetan Plateau, is a sensitive region for climate change, where the manifestation of global warming is particularly noticeable. The wide climate variability in this region significantly affects the local land ecosystem and could consequently lead to notable vegetation changes. In this paper, the interannual variations of the plateau vegetation are investigated using a 21-year normalized difference vegetation index （NDVI） dataset to quantify the consequences of climate warming for the regional ecosystem and its interactions. The results show that vegetation coverage is best in the eastern and southern plateau regions and deteriorates toward the west and north. On the whole, vegetation activity demonstrates a gradual enhancement in an oscillatory manner during 1982-2002. The temporal variation also exhibits striking regional differences： an increasing trend is most apparent in the west, south, north and southeast, whereas a decreasing trend is present along the southern plateau boundary and in the central-east region. Covariance analysis between the NDVI and surface temperature/precipitation suggests that vegetation change is closely related to climate change. However, the controlling physical processes vary geographically. In the west and east, vegetation variability is found to be driven predominantly by temperature, with the impact of precipitation being of secondary importance. In the central plateau, however, temperature and precipitation factors are equally important in modulating the interannual vegetation variability.
基金supported by the National Natural Science Foundation of China (41174020, 41131067)the Fundamental Research Funds for the Central Universities (2014214020203)+1 种基金the open fund of Key Laboratory of Geospace Environment and Geodesy, Ministry of Education (14-02-011)the open fund of Guangxi Key Laboratory of Spatial Information and Geomatics (14-045-24-17)
文摘Time-variable gravity data from the Gravity Recovery and Climate Experiment （GRACE） satellite mission are used to study terrestrial water storage （TWS） changes over the Pearl River Basin （PRB） for the period 2003-Nov. 2014. TWS estimates from GRACE generally show good agreement with those from two hydrological models GLDAS and WGHM. But they show different capability of detecting significant TWS changes over the PRB. Among them, WGHM is likely to underestimate the seasonal variability of TWS, while GRACE detects long- term water depletions over the upper PRB as was done by hydrological models, and observes significant water increases around the Longtan Reservoir （LTR） due to water impoundment. The heavy drought in 2011 caused by the persistent precipitation deficit has resulted in extreme low surface runoff and water level of the LTR. Moreover, large variability of summer and autumn precipitation may easily trigger floods and droughts in the rainy season in the PRB, especially for summer, as a high correlation of 0.89 was found between precipitation and surface runoff. Generally, the PRB TWS was negatively correlated with El Nifio-Southern Oscillation （ENSO） events. However, the modulation of the Pacific Decadal Oscillation （PDO） may impact this relationship, and the significant TWS anomaly was likely to occur in the peak of PDO phase as they agree well in both of the magnitude and timing of peaks. This indicates that GRACE-based TWS could be a valuable parameter for studying climatic in- fluences in the PRB.
基金Under the auspices of National Basic Research Program of China(No.2010CB950102)Strategic and Special Frontier Project of Science and Technology of Chinese Academy of Sciences(No.XDA05080800)+3 种基金National Natural Science Foundation of China(No.41371209,41420104002)Special Research Fund for Doctoral Discipline of Higher Education Institutions(No.20133207110015)Natural Science Foundation of Jiangsu Higher Education Institutions(No.14KJA170002)Priority Academic Program Development of Jiangsu Higher Education Institutions(No.164320H101)
文摘Using the low-resolution （T31, equivalent to 3.75°× 3.75°） version of the Community Earth System Model （CESM） from the National Center for Atmospheric Research （NCAR）, a global climate simulation was carried out with fixed external forcing factors （1850 Common Era. （C.E.） conditions） for the past 2000 years. Based on the simulated results, spatio-temporal structures of surface air temperature, precipitation and internal variability, such as the E1 Nifio-Southem Oscillation （ENSO）, the Atlantic Multi-decadal Oscilla- tion （AMO）, the Pacific Decadal Oscillation （PDO）, and the North Atlantic Oscillation （NAO）, were compared with reanalysis datasets to evaluate the model performance. The results are as follows： 1） CESM showed a good performance in the long-term simulation and no significant climate drift over the past 2000 years; 2） climatological patterns of global and regional climate changes simulated by the CESM were reasonable compared with the reanalysis datasets; and 3） the CESM simulated internal natural variability of the climate system performs very well. The model not only reproduced the periodicity of ENSO, AMO and PDO events but also the 3-8 years vari- ability of the ENSO. The spatial distribution of the CESM-simulated NAO was also similar to the observed. However, because of weaker total irradiation and greenhouse gas concentration forcing in the simulation than the present, the model performances had some differences from the observations. Generally, the CESM showed a good performance in simulating the global climate and internal natu- ral variability of the climate system. This paves the way for other forced climate simulations for the past 2000 years by using the CESM.
基金National Natural Science Foundation of China , No.40235053 Knowledge Innovation Project of CAS+1 种基金 No.KZCX3-SW-329 No.KZCX1-10-03-01
文摘Studies indicate that the climate has experienced a dramatic change in the Heihe River Basin with scope of temperature rise reaching 0.5-1.1 o C in the 1990s compared to the mean value of the period 1960-1990, precipitation increased 18.5 mm in the 1990s compared to the 1950s, and 6.5 mm in the 1990s compared to the mean value of the period 1960-1990, water resources decreased 2.6×10 8 m 3 in the 1990s compared to the 1950s, and 0.4×10 8 m 3 in the 1990s compared to the mean value of the period 1960-1990. These changes have exerted a greater effect on the local environment and socio-economy, and also made the condition worsening in water resources utilizations in the Heihe Rver Basin.
基金Project supported by the National High-Tech Research and Development Program (863) of China (No. 2006AA120101)the National Natural Science Foundation of China (Nos. 40871158 and 40875070)the Key Technologies Research and Development Program of China (No. 2006BAD10A01)
文摘We developed a sophisticated method to depict the spatial and seasonal characterization of net primary productivity (NPP) and climate variables. The role of climate variability in the seasonal variation of NPP exerts delayed and continuous effects. This study expands on this by mapping the seasonal characterization of NPP and climate variables from space using geographic information system (GIS) technology at the pixel level. Our approach was developed in southeastern China using moderate-resolution imaging spectroradiometer (MODIS) data. The results showed that air temperature,precipitation and sunshine percentage contributed significantly to seasonal variation of NPP. In the northern portion of the study area,a significant positive 32-d lagged correlation was observed between seasonal variation of NPP and climate (P<0.01),and the influences of changing climate on NPP lasted for 48 d or 64 d. In central southeastern China,NPP showed 16-d,48-d,and 96-d lagged correlation with air temperature,precipitation,and sunshine percentage,respectively (P<0.01); the influences of air temperature and precipitation on NPP lasted for 48 d or 64 d,while sunshine influence on NPP only persisted for 16 d. Due to complex topography and vegetation distribution in the southern part of the study region,the spatial patterns of vegetation-climate relationship became complicated and diversiform,especially for precipitation influences on NPP. In the northern part of the study area,all vegetation NPP had an almost similar response to seasonal variation of air temperature except for broad crops. The impacts of seasonal variation of precipitation and sunshine on broad and cereal crop NPP were slightly different from other vegetation NPP.
基金This reasearch was supported by the Science Foundation of Guangxi under grant No.0339025the Natural Sciences Foundation of China under grant No.40075021.
文摘In terms of the modular fuzzy neural network (MFNN) combining fuzzy c-mean (FCM) cluster and single-layer neural network, a short-term climate prediction model is developed. It is found from modeling results that the MFNN model for short-term climate prediction has advantages of simple structure, no hidden layer and stable network parameters because of the assembling of sound functions of the self-adaptive learning, association and fuzzy information processing of fuzzy mathematics and neural network methods. The case computational results of Guangxi flood season (JJA) rainfall show that the mean absolute error (MAE) and mean relative error (MRE) of the prediction during 1998-2002 are 68.8 mm and 9.78%, and in comparison with the regression method, under the conditions of the same predictors and period they are 97.8 mm and 12.28% respectively. Furthermore, it is also found from the stability analysis of the modular model that the change of the prediction results of independent samples with training times in the stably convergent interval of the model is less than 1.3 mm. The obvious oscillation phenomenon of prediction results with training times, such as in the common back-propagation neural network (BPNN) model, does not occur, indicating a better practical application potential of the MFNN model.
基金National Natural Science Foundation of China,No.91547114,No.41201568,No.41201572
文摘Taoer River Basin, which is located in the west of Northeast China, is an agropastoral ecotone. In recent years, the hydrological cycle and water resources have changed significantly with the deterioration of the environment. Many water problems such as river blanking, wetland shrinking and salinization have occurred in this region. All of these phenomena were directly caused by changes in stream flow under climate variability and human actiities. In light of the situation, the impact of climate variability and human activities on stream flow should be identified immediately to identify the primary driving factors of basin hydrological processes. To achieve this, statistical tests were applied to identify trends in variation and catastrophe points in mean annual stream flow from 1961 to 2011. A runoff sensitive coefficients method and a SIMHYD model were applied to assess the impacts of stream flow variation. The following conclusions were found： 1 ） The years 1985 and 2000 were confirmed to be catastrophe points in the stream flow series. Thus, the study period could be divided into three periods, from 1961 to 1985 （Period I）, 1986 to 2000 （Period II） and 2001 to 2011 （Period III）. 2） Mean annual observed stream flow was 31.54 mm in Period I, then increased to 65.60 mm in Period II and decreased to 2.92 mm in Period III. 3） Using runoff sensitive coefficients, the contribution of climate variability was 41.93% and 43.14% of the increase in stream flow during Periods II and III, suggesting that the contribution of human activities to the increase was 58.07% and 56.86%, respectively. 4） Climate variability accounted for 42.57% and 44.30% of the decrease in stream flow, while human activities accounted for 57.43% and 55.70% of the decrease, according to the SIMHYD model. 5） In comparison of these two methods, the primary driving factors of stream flow variation could be considered to be human activities, which contributed about 15% more than climate variability. It is hoped that these conclusions will .benefit future regional planning and sustainable development.
文摘Climate variability and change are among the biggest challenges of the 21st century. Like in many other areas globally, the coastal communities of Tanzania have always been facing climatic variability at various time scales. Using focus group discussion and a household survey, this study analyzes the perceptions of climate variability and change and the strategies for coping and adaptation by the selected coastal rural and peri-urban communities in Tanzania. The perception of climate variability and change is complemented with the time-series analysis of rainfall and temperature data from Julius Nyerere International Airport Met. station and Kisarawe using Instant Statistical Software. Results indicate that households are aware of climate variability and identify indicators of climate change and variability as being decreasing rainfall trends, increasing incidences of droughts, unpredictable rainfall patterns, disappearance of wetlands and failure to predict on-set of rainy season using traditional knowledge. Households primarily attribute reduced crop yields to changes in rainfall pattern and increasing incidences of drought leading to soil moisture stress. The implications are that the agriculture dependent households are now food insecure. As a way of coping to the observed changes, the coastal communities among others have shifted to production of high value horticultural crops and use of forest resources. Nevertheless, the increased use of forest resources is threatening the existence of coastal forests and contributes to the decline of forest resources and disappearance of wildlife in the forest reserves. It is concluded that the communities studied are aware of climate issues as revealed from perceived indicators of climate variability and changes. The results from statistical analysis of 30 years climatic data are consistent with community’s perception of climate variability and change. The study recommends examining the present coping strategies for the sustainability of the coastal forests and in designing of alternative adaptive strategies such as alternative energy options, crop diversification and environmental friendly activities such as beekeeping.
基金supported by the International S&T Cooperation Program of China (Grant No. 2010DFA92720-12)the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KZCX2-YW-GJ04)+2 种基金the Natural Science Foundation of China (Grant Nos. 41130531, 41375101)the Ministry of Water Resources Special Funds for Scientific Research on Public Causes (Grant No. 201301103)the Program for Innovative Research Team in University (Grant No. IRT1180)
文摘Much attention has recently been focused on the effects of climate variability and human activities on the runoff. In this study, we analyzed 56-yr(1957–2012) runoff change and patterns in the Jinghe River Basin(JRB) in the arid region of northwest China. The nonparametric Mann–Kendall test and the precipitation-runoff double cumulative curve(PRDCC) were used to identify change trend and abrupt change points in the annual runoff. It was found that the runoff in the JRB has periodically fluctuated in the past 56 yr. Abrupt change point in annual runoff was identified in the JRB, which occurred in the years around 1964 and 1996 dividing the long-term hydrologic series into a natural period(1957 – 1964) and a climate and man-induced period(1965 – 1996 and 1997 – 2012). In the 1965 – 1996 period, human activities were the main factor that decreased runoff with contribution of 88.9%, while climate variability only accounted for 11.1%. However,the impact of climate variability has been increased from 11.1% to 47.5% during 1997 – 2012, showing that runoff in JRB is more sensitive to climate variability during global warming. This study distinguishes theeffect of climate variability from human activities on runoff, which can do duty for a reference for regional water resources assessment and management.
文摘Global warming and climate change is one of the most extensively researched and discussed topical issues affecting the environment.Although there are enough historical evidence to support the theory that climate change is a natural phenomenon,many research scientists are widely in agreement that the increase in temperature in the 20 th century is anthropologically related.The associated effects are the variability of rainfall and cyclonic patterns that are being observed globally.In Southeast Asia the link between global warming and the seasonal atmospheric flow during the monsoon seasons shows varying degree of fuzziness.This study investigates the impact of climate change on the seasonality of monsoon Asia and its effect on the variability of monsoon rainfall in Southeast Asia.The comparison of decadal variation of precipitation and temperature anomalies before the 1970 s found general increases which were mostly varying.But beyond the 1970 s,global precipitation anomalous showed increases that almost corresponded with increases in global temperature anomalies for the same period.There are frequent changes and a shift westward of the Indian summer monsoon.Although precipitation is observed to be 70%below normal levels,in some areas the topography affects the intensity of rainfall.These shifting phenomenon of other monsoon season in the region are impacting on the variability of rainfall and the onset of monsoons in Southeast Asia and is predicted to delay for 15 days the onset of the monsoon in the future.The variability of monsoon rainfall in the SEA region is observed to be decadal and the frequency and intensity of intermittent flooding of some areas during the monsoon season have serious consequences on the human,financial,infrastructure and food security of the region.
