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Characterizing climatic changes in the high-altitude mountain regions helps scientists and policy makers understand the effects of such changes on water resources, economic development, and the health of ecosystems. This paper proposes a change-point analysis to determine the time and magnitude of summer temperature changes in the summit areas of Romanian Carpathians between 1961 and 2007. Due to their altitude, massiveness, and position, Romanian Carpathians are an important barrier for different types of air masses between Western and Southeastern Europe. The results show that the change in summer temperatures occurred shortly after 1980. The average magnitude of this change is consistent with changes occurring in other parts of Southern Europe in the same time period although the magnitude of changes at individual weather stations may differ substantially. We aided our analysis by a statistical method based on regression models with serially correlated ARMA errors. [ABSTRACT FROM AUTHOR]

This paper presents the results of the first stage of an ongoing project of evaluating the spatial and temporal variability of soil water as fundamental factors for vegetation regeneration in the arid ecosystems in the Blue Nile-eastern Sudan. The specific aim of the present study is to understand the temporal and spatial variations of the major climate variables in the region and discuss its relevance to regional climate variability and changes. In this case, we systematically analyze the major climate variables (maximum and minimum air temperature, relative humidity, and net solar radiation). To evaluate the different characteristics of the climate variables, Mann–Kendall method, two-phase regression scheme, and wavelet transform technique are used; each method has its own strength and weakness, and the results of the three methods complement each other. The results show that the annual and seasonal maximum temperatures are increasing significantly. The annual minimum temperature and minimum temperature in dry seasons are decreasing. The minimum temperature in rainy season is increasing with a smaller rate as compared with the increase of maximum temperature in the season. The difference between maximum and minimum temperature is increasing in all the seasons. Net solar radiation in the region shows a significant increasing trend in all seasons, which corresponds well with the changes of maximum temperature. Besides, significant decreasing trends can be identified for relative humidity in all the seasons. [ABSTRACT FROM AUTHOR]

Haors are large, round-shaped floodplain depressions located in the North-Eastern region of Bangladesh. Extreme events such as heavy rainfall routinely affect the haor basin with flash floods. These haors are predicted to experience severe stress because of changes in rainfall and temperature patterns. The biotic community of the wetlands may not have enough time to adjust itself in such varying temperature and rainfall extremes. This paper evaluates various aspects of the future projections of rainfall and temperature extremes, including magnitudes and frequencies thereof. The impacts of extreme events are examined using Hadley Centre's high-resolution regional climate model known as PRECIS (Providing REgional Climates for Impact Studies). Daily temperature and rainfall simulations of the 17-member ensembles are generated through Hadley Centre Coupled Model (HadCM3). These simulations are used in Rclimdex-a software specially designed for this study. A total of 12 core climate indices are computed, analyzed, and statistically examined (Mann-Whitney U test) over the space of three time slices-(1) short (2020s, i.e., 2011-2040), (2) medium (2050s, i.e., 2041-2070), and (3) long (2080s, i.e., 2071-2098). Here, the 1980s (1971-2000) are considered as the baseline period. The study has found that the highest significant variability in both rainfalls and temperatures was during the pre-monsoon season when flash floods normally occur. Also, rainy days are projected to be less frequent albeit more intense where the deeply flooded haors are located. Though the annual total rainfall does not show any difference in spatial distribution (except for in magnitude), the seasonal patterns of most extreme events show that the probable affected areas have shifted from North-east to further North. In addition, a significant increase in both RX1 (1-day maximum rainfall) and RX5 (5-day maximum rainfall) are projected during the 2080's pre-monsoon season near Sunamganj. This projection also indicates the possible frequent occurrence of flash floods with high volumes. Probability distribution frequencies (PDF) show a rightward shift in time indicating an increase in the amount of total rainfall in the future. Exceptions are, however, found in case of PDFs for consecutive dry days (CDD) and consecutive wet days (CWD). The decrease in CWD is found to be more pronounced than that of CDD. All these projections made in this study are expected to contribute further in the advancements of the Master Planning of the haor area that was done by the government of Bangladesh in 2012. [ABSTRACT FROM AUTHOR]

This paper designs a comprehensive approach based on the engineering machine/ system concept, to model, analyze, and assess the level of carbon dioxide (CO) exchange between the atmosphere and terrestrial ecosystems, which is an important factor in understanding changes in global climate. The focus of this article is on spatial patterns and on the correlation between levels of CO fluxes and a variety of influencing factors in eco-environments. The engineering/machine concept used is a system protocol that includes the sequential activities of design, test, observe, and model. This concept is applied to explicitly include various influencing factors and interactions associated with CO fluxes. To formulate effective models of a large and complex climate system, this article introduces a modeling technique that will be referred to as stochastic filtering analysis of variance (SF-ANOVA). The CO flux data observed from some sites of AmeriFlux are used to illustrate and validate the analysis, prediction, and globalization capabilities of the proposed engineering approach and the SF-ANOVA technique. The SF-ANOVA modeling approach was compared to stepwise regression, ridge regression, and neural networks. The comparison indicated that the proposed approach is a valid and effective tool with similar accuracy and less complexity than the other procedures. [ABSTRACT FROM AUTHOR]

Net Ecosystem CO2 Exchange (NEE) was studied during the summer season (June–August) at a high Arctic heath ecosystem for 5 years in Zackenberg, NE Greenland. Integrated over the 80 day summer season, the heath is presently a sink ranging from −1.4 g C m−2 in 1997 to −23.3 g C m−2 in 2003. The results indicate that photosynthesis might be more variable than ecosystem respiration on the seasonal timescale. The years focused on in this paper differ climatically, which is reflected in the measured fluxes. The environmental conditions during the five years strongly indicated that time of snow-melt and air temperature during the growing season are closely related to the interannual variation in the measured fluxes of CO2 at the heath. Our estimates suggest that net ecosystem CO2 uptake is enhanced by 0.16 g C m−2 per increase in growing degree-days during the period of growth. This study emphasises that increased summer time air temperatures are favourable for this particular ecosystem in terms of carbon accumulation. [ABSTRACT FROM AUTHOR]

A lack of information for surface water vapor pressure (WVP) represents a major impediment to model-assisted ecosystem analysis for understanding plant-environment interactions or for projecting biospheric responses to global climate change. This paper reports on a generic algorithm that captures global variation in monthly WVP. The algorithmsolves WVP in terms of reduction from saturation WVP as a negative exponential function of potential evapotranspiration; the reduction rate per unit potential evapotranspiration in turn varies with monthly precipitation and a series of variables that distinguish local climate regimes. Data input to the algorithm is limited to monthly air temperature and precipitation, plus latitude, longitude and elevation. The algorithm is specified through regression fitting to monthly climate normal data from 852 stations around the world. It accounts for 96%of the variance in the WVP data, with a root mean square error of 0.17 kPa, or 12% of the data mean. The algorithm closely reproduces five-year sequential monthly WVP data for each of five selected United States locations representitative of diverse climate regimes: the average error generally falls within 112% of the data mean, and the absolute error within 10.2 kPa. Its projections also compare favorably against the WVP output from the General Circulation Models for temperature and precipitation conditions under the scenario of a doubled atmospheric carbon-dioxide concentration: the two fall within 110% of eachother for 75% of a total 264 data cases, or within 120% for 94% of the cases. These statistics suggest that the spatially-based algorithmis useful for projecting temporal variation in WVP, and for extrapolative applications beyond the fluctuation range of present climate. [ABSTRACT FROM AUTHOR]

Interpretation of tower-based eddy covariance (EC) carbon dioxide flux ( F) measurements in urban areas is challenging because of the location bias of EC instruments. This bias results from EC point measurements taken above a complex CO source/sink surface that is spatially heterogeneous at scales approaching or exceeding those of the turbulent flux source areas. This makes it difficult to accomplish traditional measurement objectives such as calculating spatially unbiased ecosystem-wide cumulative F totals or objectively comparing F during different environmental conditions (e.g., day vs. night or seasonal differences). This study uses a multiyear F dataset measured over a residential area of Vancouver, BC, Canada from a 30-m flux tower in close proximity to a busy traffic intersection on one side. The F measurements are analyzed using surface geospatial data and turbulent flux source area models to exploit location bias to develop methods to statistically model individual emissions and uptake processes in terms of environmental controls and surface land cover. The empirical relations between controls and measured F are used to spatially and temporally downscale individual CO emissions/uptake processes that are then used to create high-resolution maps (20 m) and calculate ecosystem-wide F at temporal resolutions of 30 min to 1 year. At this site, the modeled ecosystem-wide annual net F total is calculated as 6.42 kg C m year with traffic emissions estimated to account for 68.8 % of the total net emissions. Building sources contribute 27.9 %, respiration from soil and vegetation is 5.5 %, respiration from humans 5.0 %, and photosynthesis offsets are −7.2 % of the annual net total. The statistical models developed here are then tested by direct comparison to independent EC measurements using land cover scalings derived from 30-min source area models. Results are also scaled to ecosystem-averaged land cover to compare results to independent emissions/uptake models. [ABSTRACT FROM AUTHOR]

The sensitivity of land surface energy partitioning to near-surface air temperature ( T) is a critical issue to understand the interaction between land surface and climatic system. Thus, studies with in situ observed data compiled from various climates and ecosystems are required. The relations derived from such empirical analyses are useful for developing accurate estimation methods of energy partitioning. In this study, the effect of T on land surface energy partitioning is evaluated by using flux measurement data compiled from a global network of eddy covariance tower sites (FLUXNET). According to the analysis of 25 FLUXNET sites (60 site-years) data, the Bowen ratio is found to have a linear relation with the bulk surface resistance normalized by aerodynamic and climatological resistance parameters in general, of which the slope and intercept are dependent on T. Energy partitioning in warmer atmosphere is less sensitive to changes in land surface conditions. In addition, a negative relation is found between Bowen ratio and T, and this relation is stronger above less vegetated surface and under low vapor pressure deficit and low received radiative energy condition. The empirical results obtained in this study are expected to be useful in gaining better understanding of alternating surface energy partitioning under increasing T. [ABSTRACT FROM AUTHOR]

Changing climate could affect the functioning of grassland ecosystems through variation in climate forcings and by altering the interactions of forcings with ecological processes. Both the short and long-term effects of changing forcings and ecosystem interactions are a critical part of future impacts to ecosystem ecology and hydrology. To explore these interactions and identify possible characteristics of climate change impacts to mesic grasslands, we employ a low-dimensional modeling framework to assess the IPCC A1B scenario projections for the Central Plains of the United States; forcings include increased precipitation variability, increased potential evaporation, and earlier growing season onset. These forcings are also evaluated by simulations of vegetation photosynthetic capacity to explore the seasonal characteristics of the vegetation carbon assimilation response for species at the Konza Prairie in North Central Kansas, USA. The climate change simulations show decreases in mean annual soil moisture and and carbon assimilation and increased variation in water and carbon fluxes during the growing season. Simulations of the vegetation response show increased variation at the species-level instead of at a larger class scale, with important heterogeneity in how individual species respond to climate forcings. Understanding the drivers and relationships behind these ecosystem responses is important for understanding the likely scale of climate change impacts and for exploring the mechanisms shaping growing season dynamics in grassland ecosystems. [ABSTRACT FROM AUTHOR]

The variability of extreme summer precipitation over Circum-Bohai-Sea region during 1961-2008 was investigated based on the daily precipitation data of 63 meteorological stations using the linear regression method, the non-parametric Mann-Kendall test, and the continuous wavelet transform method. The results showed that there were large spatial differences in the trends of extreme summer precipitation indices. Decreasing trends were found in summer total precipitation, extreme precipitation frequency, intensity and proportion, the maximum consecutive wet days (CWD), and the maximum 1- and 5-day precipitation, and the largest decrease was observed in the central coast area (except CWD), although the trends were not statistically significant at the 5% level at most places. Inversely, the maximum consecutive dry days exhibited non-significant increasing trends. Additionally, the significant 2-4-year periods were detected for eight indices, showing the significant interannual variability of extreme summer precipitation. Overall, the results of this study indicated that in the last 48 years, there was severe water stress over Circum-Bohai-Sea region, especially in the central coast area, which exerted negative effects on economic development and natural ecosystems. [ABSTRACT FROM AUTHOR]

In semi-arid Africa, rainfall variability is an important issue for ecosystems and agricultural activities. However, due to its discrete nature in time and space, rainfall is difficult to measure, quantify, and predict. In the dry tropics, a good proxy for rainfall is vegetation activity since this parameter is well correlated with rainfall variations. In this study, over 20 years of Normalized Difference Vegetative Index (NDVI) data from the Advanced Very High Resolution Radiometers are used. The goal is to assess the skill of linear statistical models in estimating regional NDVI interannual variability based on ocean and atmospheric fields (but not rainfall) and then to hindcast it with a 1- to 2-month lead-time. Three semi-arid areas of ∼150 000 km2 located in Western, Southern, and Eastern Tropical Africa are considered for this purpose. The predictors are: the Niño3.4 sea surface temperature index, the main modes of National Center for Environmental Prediction (NCEP) surface temperature variability in a window centered over Africa, and regional-scale indices based on NCEP surface temperatures and atmospheric variables (relative humidity, geopotential heights, and winds). The regional indices, which are physically and statistically robust, are generally asynchronous with the NDVI predictand. The statistical models, based on linear multiple regressions, give significant results, and the correlation between observed and cross-validated NDVI is 0.67 in Southern Africa, 0.76 for the long rains and 0.83 for the short rains in Eastern Africa, and 0.88 in Western Africa. The results have implications for (1) better understanding the role of El Niño/Southern Oscillation in semi-arid Africa, and (2) highlight the importance of regional climate processes for vegetation growth at these scales, notably the role played by the Mediterranean Sea and its influence on the West African monsoon. The predictability of NDVI over these African regions is discussed. [ABSTRACT FROM AUTHOR]

Dryness analysis is a major topic in the study of rainfall regime, mainly in regions with water shortage. The present study suggests a new approach for analyzing dry spells and their annual distribution and introduces a new term: dry days since last rain (DDSLR hereafter). The main goals of this study are to analyze and present the different annual courses of the DDSLR across the Mediterranean region. Daily rainfall totals for the period of 1931–2006 at 41 stations served as the main database. Two annual courses of the DDSLR, the median (50 percentile) and the 90 percentile, are presented for each Julian day in each station. Correlation matrices between stations according to their annual courses were calculated. A cluster analysis was performed on these correlations matrices according to which the stations were grouped. The main conclusions of the present study can be summarized as follows: Four regions were found in the Mediterranean basin according to their annual course of the DDSLR: Region Ia spread over the southern Mediterranean and has the most severe dryness conditions reaching maximum dryness in August and September. Region Ib is located mainly in northeastern Iberian Peninsula, south France, and northwestern Italy. Dryness is less severe than in Region Ia. The maximum dryness conditions are in July and August. Region IIa is located in the northeastern study area, with a bi-modal moderate dryness conditions. Maximum dryness is in August–October and a secondary dry period in January–March. Region IIb is located in the northwestern study area with a bi-modal moderate dryness conditions. Maximum dryness is in January–March and a secondary dry period in October. Both regions Ia and Ib can be combined into a single major region I. This region represents the classical Mediterranean rainfall regime with a very distinguishable dry period during summer. Similarly, regions IIa and IIb can be combined into a single major region II. This region benefits from rainfall all year round and therefore is not considered as having a classical Mediterranean climate. Uncertainty regarding the DDSLR distribution (from year to year) is much crucial in region II, since ecosystems are not adapted to long dry periods and their prolongation may have very severe environmental consequences. [ABSTRACT FROM AUTHOR]

In many instances, snow cover and duration are a major controlling factor on a range of environmental systems in mountain regions. When assessing the impacts of climatic change on mountain ecosystems and river basins whose origin lie in the Alps, one of the key controls on such systems will reside in changes in snow amount and duration. At present, regional climate models or statistical downscaling techniques, which are the principal methods applied to the derivation of climatic variables in a future, changing climate, do not provide adequate information at the scales required for investigations in which snow is playing a major role. A study has thus been undertaken on the behavior of snow in the Swiss Alps, in particular the duration of the seasonal snow-pack, on the basis of observational data from a number of Swiss climatological stations. It is seen that there is a distinct link between snow-cover duration and height (i.e., temperature), and that this link has a specific "signature" according to the type of winter. Milder winters are associated with higher precipitation levels than colder winters, but with more solid precipitation at elevations exceeding 1,700-2,000 m above sea-level, and more liquid precipitation below. These results can be combined within a single diagram, linking winter minimum temperature, winter precipitation, and snow-cover duration. The resulting contour surfaces can then be used to assess the manner in which the length of the snow-season may change according to specified shifts in temperature and precipitation. While the technique is clearly empirical, it can be combined with regional climate model information to provide a useful estimate of the length of the snow season with snow cover, for various climate-impacts studies. [ABSTRACT FROM AUTHOR]

Summary Net ecosystem CO2 exchange was measured over a mountain birch forest in northern Finland throughout the growing season. The maximal net CO2 uptake rate of about - 0.5 mg(CO2) m-2 s-1 was observed at the end of July. The highest nocturnal respiration rates in early August were 0.2 mg(CO2) m-2 s-1. The daily CO2 balances during the time of maximal photosynthesis were about -15 g(CO2) m-2 d-1. The mountain birch forest acted as a net sink of CO2 from 30 June to 28 August. During that period the net CO2 balance was -448 g(CO2)m-2. The interannual representativeness of the observed balances was studied using a simplified daily balance model, with daily mean global radiation and air temperature as the input parameters. The year-to-year variation in the phenological development was parameterised as a function of the cumulative effective temperature sum. The daily balance model was used for estimating the variability in the seasonal CO2 balances due to the timing of spring and meteorological factors. The sink term of CO2 in 1996 was lower than the 15-year mean, mainly due to the relatively late emergence of the leaves. [ABSTRACT FROM AUTHOR]

Summary Turbulent fluxes of CO2 were continuously measured by eddy correlation for three months in 1997 over a gramineous fen in a high-arctic environment at Zackenberg (74°28′12″N, 20°34′23″W) in NE-Greenland. The measurements started on 1 June, when there was still a 1–2 m cover of dry snow, and ended 26 August at a time that corresponds to late autumn at this high-arctic site. During the 20-day period with snow cover, fluxes of CO2 to the atmosphere were small, typically 0.005 mg CO2 m-2 s-1 (0.41 g CO2 m-2 d-1), wheres during the thawed period, the fluxes displayed a clear diurnal variation. During the snow-free period, before the onset of vegetation growth, fluxes of CO2 to the atmosphere were typically 0.1 mg CO2 m-2 s-1 in the afternoon, and daily sums reached values up to almost 9 g CO2 m-2 d-1. After 4 July, downward fluxes of CO2 increased, and on sunny days in the middle of the growing season, the net ecosystem exchange rates attained typical values of about -0.23 mg m-2 s-1 at midday and max values of daily sums of -12 g CO2 m-2 d-1. Throughout the measured period the fen ecosystem acted as a net-sink of 130 g CO2 m-2. Modelling the ecosystem respiration during the season corresponded well with eddy correlation and chamber measurements. On the basis of the eddy correlation data and the predicted respiration effluxes, an estimate of the annual CO2 balance the calendar year 1997 was calculated to be a net-sink of 20 g CO2 m-2 yr-1. [ABSTRACT FROM AUTHOR]