Responses of Annual Variability of Vegetation NPP to Climate Variables Using Satellite Techniques in Gadarif State, Sudan

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.

Application of Predictive Model for Efficient Cassava (Manihot esculenta Crantz) Yield in the Face of Climate Variability in Enugu State, Nigeria

Climate variability as occasioned by conditions such as extreme rainfall and temperature, rainfall cessation, and irregular temperatures has considerable impact on crop yield and food security. This study develops a predictive model for cassava yield (Manihot esculenta Crantz) amidst climate variability in rainfed zone of Enugu State, Nigeria. This study utilized data of climate variables and tonnage of cassava yield spanning from 1971 to 2012;as well as information from a questionnaire and focus group discussion from farmers across two seasons in 2023 respectively. Regression analysis was employed to develop the predictive model equation for seasonal climate variability and cassava yield. The rainfall and temperature anomalies, decadal change in trend of cassava yield and opinion of farmers on changes in rainfall season were also computed in the study. The result shows the following relationship between cassava and all the climatic variables: R2 = 0.939;P = 0.00514;Cassava and key climatic variables: R2 = 0.560;P = 0.007. The result implies that seasonal rainfall, temperature, relative humidity, sunshine hours and radiation parameters are key climatic variables in cassava production. This is supported by computed rainfall and temperature anomalies which range from −478.5 to 517.8 mm as well as −1.2˚C to 2.3˚C over the years. The questionnaire and focus group identified that farmers experienced at one time or another, late onset of rain, early onset of rain or rainfall cessation over the years. The farmers are not particularly sure of rainfall and temperature characteristics at any point in time. The implication of the result of this study is that rainfall and temperature parameters determine the farming season and quantity of productivity. Hence, there is urgent need to address the situation through effective and quality weather forecasting network which will help stem food insecurity in the study area and Nigeria at large. The study made recommendations such as a comprehensive early warning system on climate variability incidence which can be communicated to local farmers by agro-meteorological extension officers, research on crops that can grow with little or no rain, planning irrigation scheme, and improving tree planting culture in the study area.

Analysing the Potential Impact of Climate Change on the Hydrological Regime of the Upper Benue River Basin (North Cameroon)

In this study, we analyse the climate variability in the Upper Benue basin and assess its potential impact on the hydrology regime under two different greenhouse gas emission scenarios. The hydrological regime of the basin is more vulnerable to climate variability, especially precipitation and temperature. Observed hydroclimatic data (1950-2015) was analysed using a statistical approach. The potential impact of future climate change on the hydrological regime is quantified using the GR2M model and two climate models: HadGEM2-ES and MIROC5 from CMIP5 under RCP 4.5 and RCP 8.5 greenhouse gas emission scenarios. The main result shows that precipitation varies significantly according to the geographical location and time in the Upper Benue basin. The trend analysis of climatic parameters shows a decrease in annual average precipitation across the study area at a rate of -0.568 mm/year which represents about 37 mm/year over the time 1950-2015 compared to the 1961-1990 reference period. An increase of 0.7°C in mean temperature and 14% of PET are also observed according to the same reference period. The two climate models predict a warming of the basin of about 2°C for both RCP 4.5 and 8.5 scenarios and an increase in precipitation between 1% and 10% between 2015 and 2100. Similarly, the average annual flow is projected to increase by about +2% to +10% in the future for both RCP 4.5 and 8.5 scenarios between 2015 and 2100. Therefore, it is primordial to develop adaptation and mitigation measures to manage efficiently the availability of water resources.

Responses of runoff to changes in climate and human activities in the Liuhe River Basin, China

Since the 1950s,numerous soil and water conservation measures have been implemented to control severe soil erosion in the Liuhe River Basin(LRB),China.While these measures have protected the upstream soil and water ecological environment,they have led to a sharp reduction in the downstream flow and the deterioration of the river ecological environment.Therefore,it is important to evaluate the impact of soil and water conservation measures on hydrological processes to assess long-term runoff changes.Using the Soil and Water Assessment Tool(SWAT)models and sensitivity analyses based on the Budyko hypothesis,this study quantitatively evaluated the effects of climate change,direct water withdrawal,and soil and water conservation measures on runoff in the LRB during different periods,including different responses to runoff discharge,hydrological regime,and flood processes.The runoff series were divided into a baseline period(1956-1969)and two altered periods,i.e.,period 1(1970-1999)and period 2(2000-2020).Human activities were the main cause of the decrease in runoff during the altered periods,contributing 86.03%(-29.61 mm),while the contribution of climate change was only 13.70%(-4.70 mm).The impact of climate change manifests as a decrease in flood volume caused by a reduction in precipitation during the flood season.Analysis of two flood cases indicated a 66.00%-84.00%reduction in basin runoff capacity due to soil and water conservation measures in the upstream area.Soil and water conservation measures reduced the peak flow and total flood volume in the upstream runoff area by 77.98%and 55.16%,respectively,even with nearly double the precipitation.The runoff coefficient in the reservoir area without soil and water conservation measures was 4.0 times that in the conservation area.These results contribute to the re-evaluation of soil and water conservation hydrological effects and provide important guidance for water resource planning and water conservation policy formulation in the LRB.

A Study on Reconstruction of Surface Wind Speed in China Due to Various Climate Variabilities

Using European Centre for Medium-Range Weather Forecasts Reanalysis V5(ERA5)reanalysis data,this study investigated the reconstruction effects of various climate variabilities on surface wind speed in China from 1979 to 2022.The results indicated that the reconstructed annual mean wind speed and the standard deviation of the annual mean wind speed,utilizing various climate variability indices,exhibited similar spatial modes to the reanalysis data,with spatial correlation coefficients of 0.99 and 0.94,respectively.In the reconstruction of six major wind power installed capacity provinces/autonomous regions in China,the effects were notably good for Hebei and Shanxi provinces,with the correlation coefficients for the interannual regional average wind speed time series being 0.65 and 0.64,respectively.The reconstruction effects of surface wind speed differed across seasons,with spring and summer reconstructions showing the highest correlation with reanalysis data.The correlation coefficients for all seasons across most regions in China ranged between 0.4 and 0.8.Among the reconstructed seasonal wind speeds for the six provinces/autonomous regions,Shanxi Province in spring exhibited the highest correlation with the reanalysis,with a coefficient of 0.61.The large-scale climate variability indices showed good reconstruction effects on the annual mean wind speed in China,and could explain the interannual variability trends of surface wind speed in most regions of China,particularly in the main wind energy provinces/autonomous regions.

Recent Advances in Understanding Multi-scale Climate Variability of the Asian Monsoon

Studies of the multi-scale climate variability of the Asian monsoon are essential to an advanced understanding of the physical processes of the global climate system.In this paper,the progress achieved in this field is systematically reviewed,with a focus on the past several years.The achievements are summarized into the following topics:(1)the onset of the South China Sea summer monsoon;(2)the East Asian summer monsoon;(3)the East Asian winter monsoon;and(4)the Indian summer monsoon.Specifically,new results are highlighted,including the advanced or delayed local monsoon onset tending to be synchronized over the Arabian Sea,Bay of Bengal,Indochina Peninsula,and South China Sea;the basic features of the record-breaking mei-yu in 2020,which have been extensively investigated with an emphasis on the role of multi-scale processes;the recovery of the East Asian winter monsoon intensity after the early 2000s in the presence of continuing greenhouse gas emissions,which is believed to have been dominated by internal climate variability(mostly the Arctic Oscillation);and the accelerated warming over South Asia,which exceeded the tropical Indian Ocean warming,is considered to be the main driver of the Indian summer monsoon rainfall recovery since 1999.A brief summary is provided in the final section along with some further discussion on future research directions regarding our understanding of the Asian monsoon variability.

Indicator of climate variability:low treeline displacement in arid valleys of mountain areas,China

As climate change intensifies,finding an ecological indicator to quickly and accurately reflect the impact on mountain ecosystems is necessary.The low treeline/timberline,highly sensitive to climate variability and changes significantly within 5–10years,provides a new way to study the response to regional climate variability.This study explored the distribution and vertical displacement patterns of the low treeline in the Upper Minjiang River of China,using SPOT remote sensing images in 1999 and 2013and long-term positional observations.Using the Geodetector model,the study investigated the dominant climatic factors influencing the low treeline displacement.The results showed that the low treeline was located at 1700–3200 m elevation on sunny slopes(southeast,south,southwest,and west slopes)with slopes over 25°.From 1999 to 2013,the low treeline moved downward by 6 m from 2561±264m to 2555±265 m,along with a warm–humid climate tendency.The downward displacement was greater on slopes over 25°and shady slopes(-20 m and-10 m,respectively)than on slopes≤25°and sunny slopes.Additionally,the downward was greater in the warm and humid Zagunao River Basin(-15 m)compared to the arid valley center(-7 m)and the cold Heishui River Basin(-3 m).Meanwhile,the low treeline displacement correlated negatively with precipitation and relative humidity variations at the significance level of 0.05,with correlation coefficients of-0.572and-0.551,respectively.Variations in relative humidity and temperature significantly affected the spatial differentiation of low treeline displacement with influencing power of 0.246(p=0.036<0.05)and 0.183(p=0.032<0.05),respectively.Thus,the low treeline is a moisture-limited line,and its formation and variation are closely related to regional water–heat balance.The study clarifies the indicative value of the low treeline for climate variability in mountain areas and can provide references for ecological restoration in arid valleys.

Spatial Pattern of Cotton Yield Variability and Its Response to Climate Change in Cotton Belt of Pakistan

Cotton is a revenue source for cotton-producing countries;as the second-largest crop in Pakistan,it significantly contributes to its economy.Over the past few decades,cotton productivity has become unstable in Pakistan,and climate change is one of the main factors that impact cotton yield.Due to climate change,it becomes very important to understand the change trend and its impact on cotton yield at the regional level.Here,we investigate the relationship of standardized cotton yield variability with the variability of climate factors using a 15-yr moving window.The piecewise regression was fitted to obtain the trend-shifting point of climate factors.The results show that precipitation has experienced an overall decreasing trend of–0.64 mm/yr during the study period,with opposing trends of–1.39 mm/yr and 1.52 mm/yr before and after the trend-shifting point,respectively.We found that cotton yield variability increased at a rate of 0.17%/yr,and this trend was highly correlated with the variability of climate factors.The multiple regression analysis explains that climate variability is a dominant factor and controlled 81%of the cotton production in the study area from 1990 to 2019,while it controlled 73%of the production from 1990 to 2002 and 84%from 2002 to 2019.These findings reveal that climate factors affact the distinct spatial pattern of changes in cotton yield variability at the tehsil level.

Agro-Climatic Risks Analysis in Climate Variability Context in Ségou Region

In the Sahel region, the population depends largely on rain-fed agriculture. In West Africa in particular, climate models turn out to be unable to capture some basic features of present-day climate variability. This study proposes a contribution to the analysis of the evolution of agro-climatic risks in the context of climate variability. Some statistical tests are used on the main variables of the rainy season to determine the trends and the variabilities described by the data series. Thus, the paper provides a statistical modeling of the different agro-climatic risks while the seasonal variability of agro-climatic parameters was analyzed as well as their inter annual variability. The study identifies the probability distributions of agroclimatic risks and the characterization of the rainy season was clarified.

The Influence of Climate Change and Variability on Spatio-Temporal Rainfall and Temperature Distribution in Zanzibar

Climate change has resulted in serious social-economic ramifications and extremely catastrophic weather events in the world, Tanzania and Zanzibar in particular, with adaptation being the only option to reduce impacts. The study focuses on the influence of climate change and variability on spatio-temporal rainfall and temperature variability and distribution in Zanzibar. The station observation datasets of rainfall, Tmax and Tmin acquired from Tanzania Meteorological Authority (TMA) and the Coordinated Regional Climate Downscaling Experiment program (CORDEX) projected datasets from the Regional climate model HIRHAM5 under driving model ICHEC-EC-EARH, for the three periods of 1991-2020 used as baseline (HS), 2021-2050 as near future (NF) and 2051-2080 far future (FF), under two representative concentration pathways (RCP) of 4.5 and 8.5, were used. The long-term observed Tmax and Tmin were used to produce time series for observing the nature and trends, while the observed rainfall data was used for understanding wet and dry periods, trends and slope (at p ≤ 0.05) using the Standardized Precipitation Index (SPI) and the Mann Kendall test (MK). Moreover, the Quantum Geographic Information System (QGIS) under the Inverse Distance Weighting (IDW) interpolation techniques were used for mapping the three decades of 1991-2000 (hereafter D1), 2001-2010 (hereafter D2) and 2011-2020 (hereafter D3) to analyze periodical spatial rainfall distribution in Zanzibar. As for the projected datasets the Climate Data Operator Commands (CDO), python scripts and Grid analysis and Display System (GrADS) soft-wares were used to process and display the results of the projected datasets of rainfall, Tmax and Tmin for the HS, NF and FF, respectively. The results show that the observed Tmax increased by the rates of 0.035℃ yr-1 and 0.0169℃ yr-1, while the Tmin was increased by a rate of 0.064℃ yr-1 and 0.104℃ yr-1 for Unguja and Pemba, respectively. The temporal distribution of wetness and dryness indices showed a climate shift from near normal to moderate wet during 2005 at Zanzibar Airport, while normal to moderately dry conditions, were observed in Pemba at Matangatuani. The decadal rainfall variability and distributions revealed higher rainfall intensity with an increasing trend and good spatial distribution in D3 from March to May (MAM) and October to December (OND). The projected results for Tmax during MAM and OND depicted higher values ranging from 1.7℃ - 1.8℃ to 1.9℃ - 2.0℃ and 1.5℃ to 2.0℃ in FF compared to NF under both RCPs. Also, higher Tmin values of 1.12℃ - 1.16℃ was projected in FF for MAM and OND under both RCPs. Besides, the rainfall projection generally revealed increased rainfall intensity in the range of 0 - 25 mm for Pemba and declined rainfall in the range of 25 - 50 mm in Unguja under both RCPs in perspectives of both NF and FF. Conclusively the study has shown that the undergoing climate change has posed a significant impact on both rainfall and temperature spatial and temporal distributions in Zanzibar (Unguja and Pemba), with Unguja being projected to have higher rainfall deficits while increasing rainfall strengths in Pemba. Thus, the study calls for more studies and formulation of effective adaptation, strategies and resilience mechanisms to combat the projected climate change impacts especially in the agricultural sector, water and food security.

Impact of the Atlantic multidecadal variability on East Asian summer climate in idealized simulations

本文利用基于地球系统模式CESM1开展的北大西洋多年代际振荡理想化数值试验,研究了北大西洋多年代际振荡对东亚夏季气候的影响。结果显示,北大西洋多年代际振荡可以通过中纬度罗斯贝波以及热带开尔文波的传播两种途径影响东亚夏季气候.当北大西洋多年代际振荡处于正位相时,一方面,偏暖的北大西洋通过激发一条从北大西洋向下游传播的中纬度大气罗斯贝波列导致东亚陆地气压降低而西北太平洋气压升高,使得东亚-西北太平洋之间的海陆气压差增强;另一方面,偏暖的北大西洋激发赤道开尔文波东传,激发西北太平洋对流层低层出现反气旋式环流异常.通过以上两种途径,正位相的北大西洋多年代际振荡最终导致东亚夏季风增强,东亚地区夏季出现北湿南干和偏暖的气候。

The Interannual Variability of East Asian Monsoon and Its Relationship with SST in a Coupled Atmosphere-Ocean-Land Climate Model

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’.

An Overview of Dry-wet Climate Variability among Monsoon-Westerly Regions and the Monsoon Northernmost Marginal Active Zone in China

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.

Interannual Variability of the Normalized Difference Vegetation Index on the Tibetan Plateau and Its Relationship with Climate Change

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.

Major Modes of Short-Term Climate Variability in the Newly Developed NUIST Earth System Model(NESM)

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.

Terrestrial water storage changes over the Pearl River Basin from GRACE and connections with Pacific climate variability

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.

Global Climate Internal Variability in a 2000-year Control Simulation with Community Earth System Model(CESM)

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.

Impact of climate change and variability on water resources in Heihe River Basin

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.

Analysis of Climate Variability, Perceptions and Coping Strategies of Tanzanian Coastal Forest Dependent Communities

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.

Effect of Climate Variability and Human Activities on Runoff in the Jinghe River Basin, Northwest China

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.