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A number of general circulation model studies have assessed the impact of degradation of the land surface in the Sahel, mostly with idealized degradation scenarios. This paper builds on the previous research by testing the sensitivity of Mesoscale Convective Systems (MCS) and associated rainfall amounts to observed vegetation changes using a regional atmospheric model. Over the last 20 years, the vegetation in the Sahel has recovered from the drought in the 1980s and vegetation cover values have increased up to 20%. The sensitivity for both a vegetation increase and a decrease by these realistic amounts is investigated. The model simulations span 42 days of the rainy season and are centred over the region of the Hydrological and Atmospheric Pilot Experiment in the Sahel (HAPEX-Sahel), of which the data are used to evaluate model results. The model is able to correctly reproduce rainfall amounts and atmospheric profiles. Total precipitation is found to be insensitive to the applied vegetation changes, but the latter do have an impact on the rainfall patterns and the location of MCS. The model results indicate that the change in vegetation cover influences the MCS in two different ways: Firstly, the vegetation change is found to affect the surface fluxes and this in turn is found to affect the Convective Available Potential Energy (CAPE) and thereby the strength of the convective systems. The relation between vegetation cover and CAPE turns out to be affected by the time in-between precipitation events. Secondly, a change in atmospheric dynamics, especially the mid-tropospheric zonal flow, is modelled as response to a change in the spatial temperature and humidity distribution. Both mechanisms are likely to play a role in determining the characteristics of the rainfall pattern. [ABSTRACT FROM AUTHOR]

The interannual to decadal variability of precipitation and daily maximum and daily minimum temperature (TMAX and TMIN) in southern Brazil for the 1913–2006 period is investigated using indices for these variables. Relations of these indices and the sea surface temperature (SST) variability in the eastern equatorial Pacific (Niño 3.4 index) and southwestern subtropical Atlantic (SSA index) are also investigated. Analyses are based on the Morlet wavelet transform. The interannual precipitation variability during the 1913–2006 period is mostly due to the high variances that occurred in specific sub-periods. The TMAX and TMIN indices also show significant interannual variability. The coherency and phase difference analyses of the precipitation index and the SST indices show higher coherency with the Niño 3.4 than with the SSA index. On the other hand, examining the coherencies and phase difference between the temperature indices and the SST indices, weaker coherencies with the Niño 3.4 index than with the SSA index are noted. These differences are discussed in the context of previous results. The new results here, with possible application for climate monitoring tasks, refer to the spectral differences between TMIN and TMAX. [ABSTRACT FROM AUTHOR]

Drastic changes were detected in glacial systems of the Antarctic Peninsula in the last decades. The observed phenomena comprise the disintegration of ice shelves, acceleration and thinning of glaciers, and retreat of glacier fronts. However, due to the lack of consistent systematic observations in particular of the higher parts of the glacial systems, it is difficult to predict further responses of the Antarctic Peninsula glaciers to climatic change. The present paper analyses spatial and temporal variations of changes in the dry-snow line altitude on the Antarctic Peninsula as extracted from a time series (1992–2005) of ERS-1/2 SAR and Envisat ASAR data. Upward changes in dry-snow line altitude were observed in general, and are attributed to extreme high-temperature events impacting the central plateaus of the Antarctic Peninsula and the increasing duration of warming periods. A mean decrease in dry-snow line altitude was detected on the west side of the peninsula and is identified as a response to recorded increase in precipitation and accumulation. These results validate the capability of SAR data for deriving superficial parameters of glaciers to be used as indicators of climatic changes in high-latitude regions where operational restrictions limit conventional meteorological observations. [ABSTRACT FROM AUTHOR]

This paper compares precipitation, maximum and minimum air temperature and solar radiation estimates from the Hadley Centre's HadRM3 regional climate model (RCM), (50x50 km grid cells), with observed data from 15 meteorological station in the UK, for the period 1960-90. The aim was to investigate how well the HadRM3 is able to represent weather characteristics for a historical period (hindcast) for which validation data exist. The rationale was to determine if the HadRM3 data contain systematic errors and to investigate how suitable the data are for use in climate change impact studies at particular locations. Comparing modelled and observed data helps assess and quantify the uncertainty introduced to climate impact studies. The results show that the model performs very well for some locations and weather variable combinations, but poorly for others. Maximum temperature estimations are generally good, but minimum temperature is overestimated and extreme cold events are not represented well. For precipitation, the model produces too many small events leading to a serious under estimation of the number of dry days (zero precipitation), whilst also over- or underestimating the mean annual total. Estimates represent well the temporal distribution of precipitation events. The model systematically over-estimates solar radiation, but does produce good quality estimates at some locations. It is concluded that the HadRM3 data are unsuitable for detailed (i.e. daily time step simulation model based) site-specific impacts studies in their current form. However, the close similarity between modelled and observed data for the historical case raises the potential for using simple adjustment methods and applying these to future projection data. [ABSTRACT FROM AUTHOR]

Recent dry years (combined dry winter and summer months) within the UK (2005 and 2006) have enhanced concerns relating to long term water resources and future water provision in large conurbations. This paper examines the mechanisms responsible for precipitation variability for five different areas in Edinburgh (precipitation regions) using composite historic precipitation records for the period 1861–2005. Trend analysis and principal component analysis (PCA) were undertaken to examine precipitation variability over time and space. Annual correlation co-efficients were derived for relationships between precipitation areas, atmospheric–oceanographic variations and geographic parameters. Stepwise regression models were constructed to specify annual precipitation, through atmospheric variations, for each of the precipitation areas. Significant downward trends in precipitation ( p < 0.05) were noted in two out of the five precipitation areas, with one principal component representing precipitation variability over Edinburgh and the Pentland Hills. Precipitation variability is best explained by fluctuations in pressure, altitude and proximity to coast. Precipitation trends cannot be explained by changes in atmospheric circulation patterns. [ABSTRACT FROM AUTHOR]

This paper analyzes the soil–atmosphere feedbacks and uncertainties under current (1960–1990) and plausible future climate conditions (2070–2100, using the A2 greenhouse gases emission scenario). For this purpose, two vegetation descriptions differing only in the grassland and grass-with-trees proportion in some parts of the domain have been created. The combination of these two different climate scenarios and two vegetation descriptions defines four different 30-year experiments, which have been completed using a regional climate model. The domain is centered around the Mediterranean basin and covers most of Europe. The study focuses on the summer season when there are major differences between the two vegetation descriptions and when the impact of land–surface processes on precipitation is largest. Present climate experiments show large evapotranspiration differences over areas where vegetation changes have taken place. Precipitation increases (up to 3 mm day−1 in some regions) follow evapotranspiration increases, although with a more complex spatial structure. These results indicate a high sensitivity at regional scales of summer precipitation processes to vegetation changes. Future climate simulations show very similar changes to those observed in the current climate experiments. This indicates that the impacts of climate change are relatively independent to the land-cover descriptions used in this study. [ABSTRACT FROM AUTHOR]

An Inconvenient Truth (AIT) has earned Al Gore an Oscar and a share of the 2007 Nobel Peace Prize and has been widely acclaimed by the mass media. However, significant errors exist in the film, owing to alarmism and exaggeration. As this forum does not provide for a detailed examination of these errors, this paper will focus only on the portrayal of the hydrologic cycle by AIT--precipitation and floods, soil moisture and droughts, and storminess. AIT argues that precipitation and intense rainfalls, floods, droughts, and the total number, intensity, and duration of tropical cyclones have all increased due exclusively to anthropogenically-driven climate change; indeed, AIT paints a picture of near scientific certainty with an overwhelming bias toward catastrophe scenarios. A closer look at the science, however, reveals that the data do not support these claims and that the scientific community is divided as to what the impact of anthropogenic climate change on the hydrologic cycle will be. Thus, the film gives a false impression of both the current state of climate change and that 'the science is settled'. [ABSTRACT FROM AUTHOR]

Using data of long-term observations at three gauging stations and one climatic station in a forest region in southeast Germany, the impacts of snowmelt on peak flow have been investigated in this paper. Results show that the major climatic feature was found to be a precipitation maximum during the hydrological summer, and the major hydrological feature was a discharge maximum during the hydrological winter. Empirical equations describing snow depth and snow water equivalent for the studied climatic station have been developed for both snow accumulation period and ablation period. Through introducing snowmeltrainfall depth as a new variable, the present work investigates the simultaneous occurrence of snowmelt and rainfall on snow cover, assesses the characteristics of runoff including peak flows, calculates the runoff from the snowmelt and rainfall. A hydrological model has been applied to generate hydrographs resulted from snowmelt and rainfall-on-snow. [ABSTRACT FROM AUTHOR]

The paper presents the results of analysis of present-day scientific data on the dynamics of global hydroclimatic processes (with the establishment of long-term variations in the global water exchange processes) and the features of water abundance in territories under the effect of various natural and anthropogenic factors. Possible transformations of the hydrogeological situation under global climate changes are considered. The basic principles of the concept regarding the assessment of the effect of global hydroclimatic changes on the population health are presented. Medical-environmental data on the consequences of water-triggered environmental crises, taken as analogous natural models, are analyzed. The processes and regularities in the development of human pathology under the conditions of higher and lower water abundance in a territory are identified. The succession, time stages, and phases of the development of infection, parasitic, noninfectious pathologies are determined. Cause-and-effect relationships were established between the observed pathology and the effect of a complex of changing natural, anthropogenic, and social-environmental factors. Methodological approaches to the assessment of medical-environmental consequences of distinct changes in the water abundance in the territories are described. The possible use of subsurface water sources as a reserve of domestic water supply under emergencies are considered. [ABSTRACT FROM AUTHOR]

A revised 25-point Shuman-Shapiro Spatial Filter (RSSSF) has been applied to six atmospheric circulation models and multi-model ensemble (MME) predictions, and its effect on the improvement of model forecast skill scores of the Asian summer precipitation anomaly is discussed in this paper. On the basis of 21-yr model ensemble predictions, the RSSSF can remove the unpredictable ‘noise’ with respect to the 2-grid wavelength in the model precipitation anomaly fields and maintain the large-scale counterpart, which is related to the response of the model to large-scale boundary forcing. Therefore, this could possibly enhance the forecast skill of the Asian summer rainfall anomaly in the models and the MME. The potential improvement of model forecasting skill is found in the Asian summer monsoon region, where the anomaly correlation coefficient (ACC) has been improved by 7–40%, corresponding to the decreased root mean square error (RMSE) in the model and the MME precipitation anomaly forecasts. [ABSTRACT FROM AUTHOR]

This paper compares how well satellite versus weather station measurements of climate predict agricultural performance in Brazil, India, and the United States. Although weather stations give accurate measures of ground conditions, they entail sporadic observations that require interpolation where observations are missing. In contrast, satellites have trouble measuring some ground phenomenon such as precipitation but they provide complete spatial coverage of various parameters over a landscape. The satellite temperature measurements slightly outperform the interpolated ground station data but the precipitation ground measurements generally outperform the satellite surface wetness index. In India, the surface wetness index outperforms station precipitation but this may be reflecting irrigation, not climate. The results suggest that satellites provide promising measures of temperature but that ground station data may still be preferred for measuring precipitation in rural settings. [ABSTRACT FROM AUTHOR]

This study applies the Ricardian technique to estimate the effect of climate change on the smallholder agriculture sector in Sri Lanka. The main contribution of the paper is the use of household-level data to analyze long-term climate impacts on farm profitability. Household-level data allows us to control for a host of factors such as human and physical capital available to farmers as well as adaptation mechanisms at the farm level. We find that non-climate variables explain about half the variation in net revenues. However, our results suggest that climate change will have a significant impact on smallholder profitability. In particular, reductions in precipitation during key agricultural months can be devastating. At the national level, a change in net revenues of between--23% and+22% is likely depending on the climate change scenario simulated. These impacts will vary considerably across geographic areas from losses of 67% to gains that more than double current net revenues. The largest adverse impacts are anticipated in the dry zones of the North Central region and the dry zones of the South Eastern regions of Sri Lanka. On the other hand, the intermediate and wet zones are likely to benefit, mostly due to the predicted increase in rainfall. [ABSTRACT FROM AUTHOR]

The aim of this work is to assess potential future Antarctic surface mass balance changes, the underlying mechanisms, and the impact of these changes on global sea level. To this end, this paper presents simulations of the Antarctic climate for the end of the twentieth and twenty-first centuries. The simulations were carried out with a stretched-grid atmospheric general circulation model, allowing for high horizontal resolution (60 km) over Antarctica. It is found that the simulated present-day surface mass balance is skilful on continental scales. Errors on regional scales are moderate when observed sea surface conditions are used; more significant regional biases appear when sea surface conditions from a coupled model run are prescribed. The simulated Antarctic surface mass balance increases by 32 mm water equivalent per year in the next century, corresponding to a sea level decrease of 1.2 mm year−1 by the end of the twenty-first century. This surface mass balance increase is largely due to precipitation changes, while changes in snow melt and turbulent latent surface fluxes are weak. The temperature increase leads to an increased moisture transport towards the interior of the continent because of the higher moisture holding capacity of warmer air, but changes in atmospheric dynamics, in particular off the Antarctic coast, regionally modulate this signal. [ABSTRACT FROM AUTHOR]

Evaluating the response of climate to greenhouse gas forcing is a major objective of the climate community, and the use of large ensemble of simulations is considered as a significant step toward that goal. The present paper thus discusses a new methodology based on neural network to mix ensemble of climate model simulations. Our analysis consists of one simulation of seven Atmosphere–Ocean Global Climate Models, which participated in the IPCC Project and provided at least one simulation for the twentieth century (20c3m) and one simulation for each of three SRES scenarios: A2, A1B and B1. Our statistical method based on neural networks and Bayesian statistics computes a transfer function between models and observations. Such a transfer function was then used to project future conditions and to derive what we would call the optimal ensemble combination for twenty-first century climate change projections. Our approach is therefore based on one statement and one hypothesis. The statement is that an optimal ensemble projection should be built by giving larger weights to models, which have more skill in representing present climate conditions. The hypothesis is that our method based on neural network is actually weighting the models that way. While the statement is actually an open question, which answer may vary according to the region or climate signal under study, our results demonstrate that the neural network approach indeed allows to weighting models according to their skills. As such, our method is an improvement of existing Bayesian methods developed to mix ensembles of simulations. However, the general low skill of climate models in simulating precipitation mean climatology implies that the final projection maps (whatever the method used to compute them) may significantly change in the future as models improve. Therefore, the projection results for late twenty-first century conditions are presented as possible projections based on the “state-of-the-art” of present climate modeling. First, various criteria were computed making it possible to evaluate the models’ skills in simulating late twentieth century precipitation over continental areas as well as their divergence in projecting climate change conditions. Despite the relatively poor skill of most of the climate models in simulating present-day large scale precipitation patterns, we identified two types of models: the climate models with moderate-to-normal (i.e., close to observations) precipitation amplitudes over the Amazonian basin; and the climate models with a low precipitation in that region and too high a precipitation on the equatorial Pacific coast. Under SRES A2 greenhouse gas forcing, the neural network simulates an increase in precipitation over the La Plata basin coherent with the mean model ensemble projection. Over the Amazonian basin, a decrease in precipitation is projected. However, the models strongly diverge, and the neural network was found to give more weight to models, which better simulate present-day climate conditions. In the southern tip of the continent, the models poorly simulate present-day climate. However, they display a fairly good convergence when simulating climate change response with a weak increase south of 45°S and a decrease in Chile between 30 and 45°S. Other scenarios (A1B and B1) strongly resemble the SRES A2 trends but with weaker amplitudes. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the role that horizontal resolution plays in the simulation of East Asia precipitation. Two sets of numerical experiments are performed using the Regional Climate Model (RegCM2) nested in one-way mode within the CSIRO global coupled atmosphere-ocean model. In the first set we use the actual RegCM2 topography at the selected model resolutions, which are 45, 60, 90, 120, 180, 240 and 360 km. In the second set of the experiments, the same coarse CSIRO model topography is used in all simulations using the different resolutions of the first set. The results demonstrate that the simulation of East Asian precipitation improves as the horizontal resolution is increased. Moreover, it is shown that the simulations using a higher resolution along with the coarse CSIRO topography perform better than the simulations using a coarser model resolution with corresponding model topography. This suggests that over East Asia adequate spatial resolution to resolve the physical and dynamical processes is more important than topography. Lastly, the results indicate that model resolutions of 60 km or higher are needed to accurately simulate the distribution of precipitation over China and East Asia. [ABSTRACT FROM AUTHOR]

The purposes of this paper are to evaluate the new version of the regional model, RegCM3, over South America for two test seasons, and to select a domain for use in an experimental nested prediction system, which incorporates RegCM3 and the European Community-Hamburg (ECHAM) general circulation model (GCM). To evaluate RegCM3, control experiments were completed with RegCM3 driven by both the NCEP/NCAR Reanalysis (NNRP) and ECHAM, using a small control domain (D-CTRL) and integration periods of January–March 1983 (El Niño) and January–March 1985 (La Niña). The new version of the regional model captures the primary circulation and rainfall differences between the two years over tropical and subtropical South America. Both the NNRP-driven and ECHAM-driven RegCM3 improve the simulation of the Atlantic intertropical convergence zone (ITCZ) compared to the GCM. However, there are some simulation errors. Irrespective of the driving fields, weak northeasterlies associated with reduced precipitation are observed over the Amazon. The simulation of the South Atlantic convergence zone is poor due to errors in the boundary condition forcing which appear to be amplified by the regional model. To select a domain for use in an experimental prediction system, sensitivity tests were performed for three domains, each of which includes important regional features and processes of the climate system. The domain sensitivity experiments were designed to determine how domain size and the location of the GCM boundary forcing affect the regional circulation, moisture transport, and rainfall in two years with different large scale conditions. First, the control domain was extended southward to include the exit region of the Andes low level jet (D-LLJ), then eastward to include the South Atlantic subtropical high (D-ATL), and finally westward to include the subsidence region of the South Pacific subtropical high and to permit the regional model more freedom to respond to the increased resolution of the Andes Mountains (D-PAC). In order to quantify differences between the domain experiments, measures of bias, root mean square error, and the spatial correlation pattern were calculated between the model results and the observed data for the seasonal average fields. The results show the GCM driving fields have remarkable control over the RegCM3 simulations. Although no single domain clearly outperforms the others in both seasons, the control domain, D-CTRL, compares most favorably with observations. Over the ITCZ region, the simulations were improved by including a large portion of the South Atlantic subtropical high (D-ATL). The methodology presented here provides a quantitative basis for evaluating domain choice in future studies. [ABSTRACT FROM AUTHOR]

Estimates of forest vegetation carbon storage in China varied due to different methods used in the assessments. In this paper, we estimated the forest vegetation carbon storage from the Fourth Forest Inventory Data (FFID) in China using a modified volume-derived method. Results showed that total carbon storage and mean carbon density of forest vegetation in China were 3.8 Pg C (about 1.1% of the global vegetation carbon stock) and 41.32 Mg/ha, respectively. In addition, based on linear multiple regression equation and factor analysis method, we analyzed contributions of biotic and abiotic factors (including mean forest age, mean annual temperature, annual precipitation, and altitude) to forest carbon storage. Our results indicated that forest vegetation carbon storage was more sensitive to changes of mean annual temperature than other factors, suggesting that global warming would seriously affect the forest carbon storage. [ABSTRACT FROM AUTHOR]

The aim of the paper lies in the identification of possible significant linear trends at monthly, seasonal and annual timescales in the Mediterranean during the second half of the 20th century. Monthly and daily records of 63 stations have been used to elaborate several precipitation indices: sum of daily precipitation (SDP) for rainfall >0.1 mm, >10 mm and >95th percentile, of number of rainy days (RD) >0.1 mm and >10 mm and of mean daily precipitation (MDP) >0.1 mm and >10 mm. For each index the stations have been gathered together by Rotated Principal Component Analyses to determine 8 sub-areas which can be considered as identical for all the timescales at the spatial scale of the research. Trends have been estimated from the scores of each eigenvector retained in all RPCAs. They are mainly non existant or non significant decreasing, even if a few monthly trends appear to be significantly diminishing, primarily during winter months, March in the Atlantic region, October in the Mediterranean Spain, December in the Lions and Genoa Gulfs, January, winter and the year in Greece, winter and the year in Italy and winter in the Near East and increasing in April in the two gulfs. Correlation coefficients between SDP>0.1 mm and other indices have been computed: the significant trends seem mainly related to RD>10 mm, which represents a high percentage of the total rainfall amount. Greece is remarkable: SDP>0.1 mm and >10 mm decrease significantly during January, winter, the rainy season and the entire year whereas SDP>95th percentile increases significantly, in accordance with the climatic change scenarios for the end of this century as does the decreasing of the total monthly and seasonal rainfall. [ABSTRACT FROM AUTHOR]

This paper reconstructs precipitation variability in the southern Canadian Cordillera over the past 3-400 years using dendroclimatological techniques. Fifty-three total ring-width (RW) chronologies, 28 earlywood (EW) and 28 latewood (LW) chronologies were developed from open-grown, low-elevation stands of Pseudotsuga meoziesii (Douglas-fir) and Pious pooderosa (ponderosa pine) across the southern Canadian Cordillera. RW, EW and LW chronologies from both species were used to develop 13 annual (prior July to current June) precipitation reconstructions across the region. The reconstructions range in length from 165 to 688 years, pass verification tests and capture 39-64% of the variance in the instrumental record. Coincident, prolonged intervals of dry conditions are estimated for the years: 1717-1732, 1839-1859, 1917-1941 and 1968-1979. Shorter dry intervals are identified between 1581-1586, 1626-1630, 1641-1653 1701-1708, 1756-1761, 1768-1772, 1793-1800, 1868-1875, 1889-1897 and 1985-1989. The historic drought of the 1920-1930s was the longest but not the most intense across this area in the last 300 years. Wet conditions occur in the majority of reconstructions for the years: 1689-1700, 1750-55, 1778-1789, 1800-1830, 1880-1890, 1898-1916 and 1942-1960. These data, in conjunction with data from adjacent areas, are used to provide the first maps of decadal precipitation anomalies for the region between 1700 and 1990. [ABSTRACT FROM AUTHOR]

This paper measures the economic impacts of climate change on China's agriculture based on the Ricardian model. By using county-level cross-sectional data on agricultural net revenue, climate, and other economic and geographical data for 1275 agriculture dominated counties, we find that under most climate change scenarios both higher temperature and more precipitation would have an overall positive impact on China's agriculture. However, the impacts vary seasonally and regionally. Autumn effect is the most positive, but spring effect is the most negative. Applying the model to five climate scenarios in the year 2050 shows that the East, the Central part, the South, the northern part of the Northeast, and the Plateau would benefit from climate change, but the Southwest, the Northwest and the southern part of the Northeast may be negatively affected. In the North, most scenarios show that they may benefit from climate change. In summary, all of China would benefit from climate change in most scenarios. [ABSTRACT FROM AUTHOR]

The possibility of applying remote sensing data to the identification and monitoring of desertification is demonstrated. The present study includes the investigation of desertification of the territory of Mongolia by the analysis of vegetation dynamics over the period from 1982 to 2016 and its interrelation with climatic, natural, and anthropogenic components. It is found that the main contribution to the vegetation degradation in Mongolia was made by precipitation decrease and air temperature rise. The indirect factors such as livestock, land cultivation, and wildfires increased the influence of climatic factors and gave impetus to the desertification in some arid and semiarid regions. [ABSTRACT FROM AUTHOR]

As an important part of the regional environment, the wet-dry climate condition is determined by precipitation and potential evapotranspiration (expressed as ET ). Based on weather station data, this study first calculated ET by using the FAO56 Penman-Monteith model. Then, the dryness index K (ratio of ET to precipitation) was used to study the spatio-temporal variation of the wet-dry condition in China from 1961 to 2015; moreover, dominant climatic factors of the wet-dry condition change were discussed. The annual precipitation and ET of the Qinling-Huaihe line were close to a balance ( K≈1.0). The annual precipitation in most areas exceeded the ET in the south of this line and the east of Hengduan Mountains ( K<1.0), where the climate is wet. Furthermore, the precipitation in the northwest inland areas of China, where the climate is dry, was markedly lower than ET ( K≥4.0). The overall annual K of China fluctuated around the 55-year mean and its linear trend was not significant. However, a relatively wet period of about 10 yr (1987-1996) was recorded. The overall annual K of China showed strong cyclicality on the time scale of 3, 7-8, 11 and 26-28 yr, and regional differences of the annual K trends and cyclicality were large. The degrees of wetness in the Northwest China and western Qinghai-Tibet Plateau were substantially increased, whereas the degrees of dryness in the Yunnan-Guizhou Plateau, Sichuan Basin, and Loess Plateau were markedly increased. The linear trend of the annual K in most regions of China was not significant, and the annual K of most areas in China showed strong cyclicality on the 8-14 yr time scale. Precipitation was the dominant factor of wet-dry condition change in most areas, especially in North China, where the annual K change was highly correlated with precipitation. [ABSTRACT FROM AUTHOR]

This article discusses the expected climate changes in Belarus as a result of two types of land transformation—rewetting degraded peatlands and increasing forest cover. The analysis was performed for the growing season (May–September) based on long-term earth remote sensing data, mesoscale modeling of atmospheric processes, and balance calculations using ERA5 reanalysis. It is shown that, as a result of waterlogging, the daytime temperature of the land surface for the southern part of Belarus (below the latitude of Minsk) decreases within 1.5°С due to increased evaporation and, for the northern part, 0.5 increased due to albedo regularity. At night, waterlogging, depending on the soil and climatic conditions, can cause both an increase and decrease a specific value of the land surface temperature (LST) within 1°C. Evapotranspiration due to waterlogging in the northern regions of Belarus decreases and it increases in the southern regions, which is associated with a significant ratio between evaporation and transpiration in these regions. During the afforestation of cropland, the daytime LST of Belarus decreases within 2°C and, at night, increase. The total evapotranspiration for the growing season due to the increase in forest cover reaches 100 mm, and potential (maximum possible) evaporation remains at the same level, which contributes to an increase in soil moisture at an increased amount of atmospheric precipitation. The above changes in the physical characteristics of the land surface as a result of reclamation cause a decrease in the surface air temperature in the reclamated region within 0.4°C and an increase in the amount of atmospheric precipitation within 2% of the climatic normals. At the same time, the maximum in the spatial distribution of secondary precipitation due to western transport shifts to the east relative to the reclaimed region. [ABSTRACT FROM AUTHOR]

Three consecutive dry summers in western Europe (2018–2019–2020) had widespread negative impacts on society and ecosystems, and started societal debate on (changing) drought vulnerability and adaptation measures. We investigate the occurrence of multi-year droughts in the Rhine basin, with a focus on event probability in the present and in future warmer climates. Additionally, we investigate the temporally compounding physical drivers of multi-year drought events. A combination of multiple reanalysis datasets and multi-model large ensemble climate model simulations was used to provide a robust analysis of the statistics and physical processes of these rare events. We identify two types of multi-year drought events (consecutive meteorological summer droughts and long-duration hydrological droughts), and show that these occur on average about twice in a 30 year period in the present climate, though natural variability is large (zero to five events can occur in a single 30 year period). Projected decreases in summer precipitation and increases in atmospheric evaporative demand, lead to a doubling of event probability at 1 ∘ C additional global warming relative to present-day and an increase in the average length of events. Consecutive meteorological summer droughts are forced by two, seemingly independent, summers of lower than normal precipitation and higher than normal evaporative demand. The soil moisture response to this temporally compound meteorological forcing has a clear multi-year imprint, resulting in a relatively larger reduction of soil moisture content in the second year of drought, and potentially more severe drought impacts. Long-duration hydrological droughts start with a severe summer drought followed by lingering meteorologically dry conditions. This limits and slows down the hydrological recovery of soil moisture content, leading to long-lasting drought conditions. This initial exploration provides avenues for further investigation of multi-year drought hazard and vulnerability in the region, which is advised given the projected trends and vulnerability of society and ecosystems. [ABSTRACT FROM AUTHOR]

Little guidance is available to assist wetland managers in developing climate adaptation plans. To facilitate development of recommendations for adaptation strategies, it is essential to first determine if or how wetland managers are addressing these challenges. We used an online survey to solicit feedback from wetland managers and biologists in the Southern Great Plains of North America to gain information on perceptions of wetland managers regarding climate change; assess how the effects of climate change are being addressed through management; and identify barriers to implementing climate change adaptation. The majority of wetland managers (63%) agreed they are currently experiencing effects of climate change in wetlands, and most respondents (76%) reported that changes in the timing of water availability throughout the year was the most likely impact. Managers reported using a diversity of approaches in managing for changing precipitation, with management of native and invasive plant species being the two most common practices. Lack of funding and personnel were the most commonly identified factors limiting manager's response to changing precipitation patterns. In addition, >50% of managers indicated uncertainty about the effects of climate change on wetlands as a barrier to management, which may relate to limited access to peer-reviewed science. While most of the management practices reported were short-term measures and may not reflect long-term adaptation for climate change, the fact that many managers are considering climate change in their management suggests that there is considerable opportunities to continue developing capacity for climate change adaptation in the region. [ABSTRACT FROM AUTHOR]

This study aims to assess climate model performance at Wadi El Abid basin (northeastern Tunisia), using Hydrologiska Byråns Vattenbalansavdelning (HBV)-light rainfall-runoff model (RRM). We evaluate time series of daily precipitation and mean daily temperature simulated by eleven couple of regional climate models (RCMs) downscaling five general circulation models (GCMs), provided by the Coordinated Downscaling Experiment–European Domain (EURO-CORDEX), over 1970–2000 historical period. The hydrological performance of regional climate models forced by Global Circulation Models (GCM-RCMs) is achieved using six discharge metrics, evaluating the runoff simulated by RRM forced by climate models' data. Quantile Delta Mapping bias correction technique was used to correct the distribution of precipitation and temperature time series simulated by GCM-RCMs. HBV-light model performed highly over the historical period with Kling-Gupta Efficiency around 0.80 and bias almost null. Quantile Delta Mapping (QDM) reduces greatly the bias in precipitation simulated by GCM-RCMs; nevertheless, disagreement between observed and bias-corrected precipitation is still present at monthly time scale after the application of QDM. This disagreement was transmitted to simulated runoff with further accentuation due to the high elasticity of runoff to precipitation. This finding shows the capacity of the hydrological evaluation of the climate model to highlight the hydrological consequences of certain weaknesses of the GCM-RCM simulations that are not well detectable by the separate evaluation of the climate variables. The hydrological rating of GCM-RCMs shows that IPSL-IPSL-CM5A-MR-IPSL-INERIS-WRF331F was low performing even though it was after bias correction. It is recommended to a modeler, to build their impact studies over the study catchment on the ensemble projection from the remaining ten best-performing GCM-RCMs. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the performance of six models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) models in reproducing the monthly cycle of precipitation and maximum surface air temperature of the Hodna region in central Algeria during the baseline period 1901–2014. The six climate models selected are as follows: ACCESS-ESM4, BCC-CSM2-MR, CanESM5, GFDL-ESM1-5, IPSL-EM6A-LR, and MIROC6. The best-performing models are determined by comparing observation (CRU-TS) and historical data. The evaluation procedure is performed using the compromise programming method and multiple statistical metrics including mean bias error (MB), root mean square error (RMSE), and pattern determination coefficient (R2). The first two best-performing models are used for precipitation (IPSL-EM6A-LR) and maximum surface air temperature (GFDL-ESM4). Four future periods are considered: 2021–2040, 2041–2060, 2061–2080, and 2081–2100 for SSP1-2.6 and SSP3-7.0. For the most optimist scenario, the maximum surface air temperature may increase in the next decades in comparison with observed and simulated values by 2 °C, but then almost stabilizes and reaches an average monthly increase of 28.53 °C. The same is shown in the precipitation projection of 48.75 mm/month by 2100. Eventually, the SSP1-2.6 scenario does not show any current signs in the current Hodna basin climate on a global scale. Future precipitation projections under Hodna's SSP3-7.0 may decrease with an average value of 10 mm in a monthly scale. This decrease becomes mostly in the center and southeastern parts. Maximum surface air temperature can rise steadily from 28 to 31 °C and reach its maximum of 4.5 °C by 2100. The outcomes of this study will evaluate how projected changes will affect droughts and floods. [ABSTRACT FROM AUTHOR]

We present a detailed downscaling simulation methodology for generating precipitation events, conditioned on external climate covariates, on a network of meteorological stations. These events can be input to hydrological models. To simulate an event on a future day t, the method uses the K-nearest neighbor algorithm to identify close neighbors from the historical record, and resamples a past event with resampling probabilities determined from external covariates. This preserves the spatial dependence of precipitation on the network, and other important distributional features of precipitation. Large numbers of arbitrary tuning parameters and model assumptions are reduced through the use of a multivariate Gaussian model relating climate covariates to historical precipitation. The approach is demonstrated by simulating daily precipitation, maximum temperature, and minimum temperature on a network of 93 locations in North Carolina, all conditioned on climate model output. The downscaling is based on a regional climate model (RCM) embedded within a global NCEP reanalysis model. The method is demonstrated using precipitation in North Carolina with the Canadian climate RCM as an NCEP driven RCM. [ABSTRACT FROM AUTHOR]

Climate change has great impacts on hydrological processes worldwide. The Tibetan Plateau (TP), the 'Water Tower' of Asia, poses significant influences on Asian climate and is also one of the most sensitive areas to climate change. Therefore, it is of importance to investigate the plausible future hydrological regimes in the TP based on the climate scenarios provided by General Circulation Models (GCMs). In this study, the Variable Infiltration Capacity model was coupled with Shuffled Complex Evolution developed at the University of Arizona to explore the responses of hydrological processes to climate change in the Lhasa River basin, the tributary of the Yarlung Zangbo River in the southern TP. A downscaling framework based on Automatic Statistical Downscaling was used to generate the future climate data from two GCMs (Echam5 and Miroc3.2_Medres) under three scenarios (A1B, A2 and B1) for the period of 2046-2065. Results show increases for both air temperature and annual precipitation in the future climate. Evaporation, runoff and streamflow will experience a rising trend, whereas spring snow cover will reduce dramatically. These changes present significant spatial and temporal variations. The alteration of hydrological processes may challenge the local water resource management. This study is helpful for policy makers to tackle climate change related issues in terms of mitigation and adaptation. [ABSTRACT FROM AUTHOR]

The increasing concern about climate change has increased the necessity for precise figures about deviations in statistical characteristics of rainfall events in both temporal and spatial scales. Many areas across Australia have high variability patterns of rainfall and inadequate rainfall records which has various effects on the availability of food and water. Modelling spatial and temporal rainfall is essential for prediction and simulation purposes in numerous aspects of planning, agriculture, forestry, meteorology and hydrology. Two different models are generally used to describe the two main features of rainfall: the occurrence and the amount. This paper describes the occurrence probability of 5-day average rainfall (successive 5-day rainfall mean) in Australia. Daily accumulated rainfall observations of 105 meteorological stations spanning from 1950 to 2013 were collected from Australian Bureau of Meteorology for the study. Logistic regression is applied to predict rainfall probability of occurrence in all the meteorological stations using nine observational rainfall stations as case studies. Weather conditions such as the 5-day periods which is defined as the consecutive 5-day average rainfall in a year and the annual rainfall which is defined as the annual daily rainfall mean factors were used as the predictors. The fitted logistic regression models predicted the occurrence and non-occurrence 5-day average rainfall events quite well with good accuracies. The predictors significantly affected the fitted models in all stations. Analysis of the levels of each of the predictors showed that the parameters of the 5-day period factors were more influential in all the models, particularly during the rainy season in most stations relative to that of the annual factors. The fitted models could be used to simulate rainfall probabilities for the stations with insufficient rainfall histories and could assist agronomist and various stakeholders in the planning of their various operations. [ABSTRACT FROM AUTHOR]

In this study, we analyse possible future climatic changes in three catchments, namely, Pyshma, Vagai and Loktinka located in the Western Siberian lowland region, and the resulting impact on hydrological regimes. It involved downscaling the GCM outputs based on the established statistical relationship between large-scale atmospheric variables and station data and simulating the effects of climate change on hydrological regimes via hydrological modelling. This was done for RCP 2.6, 4.5 and 8.5 based on second-generation Canadian Earth System Model used in the IPCC fifth assessment report. This paper provides the first climate change projections on a local scale in these catchments. The statistical downscaling showed that there will be an increase in both maximum and minimum temperature at all stations under all scenarios. The mean annual daily precipitation increased in Loktinka and Pyshma basins under all scenarios, but there was no clear trend in Vagai basin. The possible increase in annual precipitation is mostly due to the projected increase in autumn and winter precipitation. Annual streamflow tends to increase in all catchments under all scenarios. [ABSTRACT FROM AUTHOR]

Spatio-temporal variations in precipitation are affecting agricultural production in China in the context of climate change. Based on daily precipitation data from 63 national meteorological stations on the Huang-Huai-Hai Plain from 1963 to 2012, this paper analysed the spatio-temporal variations in precipitation in terms of precipitation days and intensity, using spatial interpolation, linear trend estimation and wavelet analysis. The results indicated that: (i) from 1963 to 2012, the number of annual precipitation days and intensity decreased gradually from the southeast to the northwest. Additionally, the distribution of the extreme precipitation index was similar to that of the annual precipitation index; (ii) the number of annual precipitation days and heavy precipitation days gradually decreased, while precipitation intensity and extreme precipitation days and extreme rainfall intensity remained relatively stable or decreased. The spatial patterns of annual variation trends were considerably different. The annual precipitation days and intensity trends are consistent with the overall trend, while that of the extreme rainfall index in some regions differs from the overall trend; (iii) the precipitation index displayed different periodic oscillations during the period, and the precipitation index values differed at different time scales. However, all the precipitation index values exhibited a 28-yr oscillation. [ABSTRACT FROM AUTHOR]

Despite the reduction in S and N emissions, acid deposition continues to be a problem for the inland water in Northeast Asia. However, catchment-scale studies on acid deposition in the Asian part of Russia are limited. Based on the long-term data of the Acid Deposition Monitoring Network in East Asia (EANET), we evaluated the effects of acid deposition on the stream water (SW) chemistry in a catchment of the Komarovka River (KMR) located in the Far East of Russia for the period 2005–2019. The SW pH has been decreasing over the last decade, with an increase in acidifying agents, such as SO42– and NO3–. The N/S ratio increased in SW due to a rise in NO3–, which plays a key role in acidification. In contrast, the rainwater pH has been rising at the nearby EANET site. There were transition periods from a decreasing trend to an increasing trend of S and dissolved inorganic nitrogen (DIN) in 2011 and 2014, respectively. Moreover, because of changing precipitation patterns, the contribution of warm season deposition to acidification has increased, which may accelerate the leaching of S and DIN from the forested catchment. The recent increase in S and DIN deposition and increased warm-season precipitation appeared to cause acidification of SW at KMR. The N leaching at KMR was largely influenced by the precipitation patterns, while DIN deposition and forest conditions should be taken into consideration. An interlinkage between air pollution and climate change should be carefully assessed to understand the forested catchment. [ABSTRACT FROM AUTHOR]

We present an analysis of a present-day climate simulation (1990-2009) for the Southern Africa region with the RegCM4 regional climate model (RCM, dx = 25 km ~0.22°) driven by the Community Atmospheric Model version 4 (CAM4) global climate model (GCM, dx = 1°). We assess the capability of the models to simulate the observed climate of the region with emphasis on precipitation, 2-m mean, minimum, and maximum temperature and large-scale circulation. The analysis focuses on seasonal climatologies, annual cycles, interannual variability, and extreme events. In addition to evaluating the performance of the models, we also attempt to assess the added value of the regional model compared to the driving one. With a few exceptions, we find that the models reproduce reasonably well the mean spatial patterns of 2-m temperature and precipitation, along with the associated seasonal cycle and interannual variability over selected sub-regions. Extreme indices of temperature and precipitation are also reasonably well reproduced. However, the RegCM4 substantially improves the simulation of daily precipitation frequency and duration of dry and wet events compared to CAM4 due to its higher resolution. The global and regional models exhibit quite different patterns of bias, an indication of the importance of internal variability and process representation for the simulation of surface climate. Given the good performance shown by the nested CAM4-RegCM4 system, we plan to use these models to generate an ensemble of projections for use in impact assessment studies for the region. [ABSTRACT FROM AUTHOR]

Precipitation changes projected for the end of the twenty-first century show an increase of more than 50 per cent in the Arctic regions. This marked increase, which is among the highest globally, has previously been attributed primarily to enhanced poleward moisture transport from lower latitudes. Here we use state-of-the-art global climate models to show that the projected increases in Arctic precipitation over the twenty-first century, which peak in late autumn and winter, are instead due mainly to strongly intensified local surface evaporation (maximum in winter), and only to a lesser degree due to enhanced moisture inflow from lower latitudes (maximum in late summer and autumn). Moreover, we show that the enhanced surface evaporation results mainly from retreating winter sea ice, signalling an amplified Arctic hydrological cycle. This demonstrates that increases in Arctic precipitation are firmly linked to Arctic warming and sea-ice decline. As a result, the Arctic mean precipitation sensitivity (4.5 per cent increase per degree of temperature warming) is much larger than the global value (1.6 to 1.9 per cent per kelvin). The associated seasonally varying increase in Arctic precipitation is likely to increase river discharge and snowfall over ice sheets (thereby affecting global sea level), and could even affect global climate through freshening of the Arctic Ocean and subsequent modulations of the Atlantic meridional overturning circulation. [ABSTRACT FROM AUTHOR]

An extensive set of boreal summer seasonal hindcasts from a two tier system is compared with corresponding seasonal hindcasts from two other coupled ocean-atmosphere models for their seasonal prediction skill (for precipitation and surface temperature) of the Asian summer monsoon. The unique aspect of the two-tier system is that it is at relatively high resolution and the SST forcing is uniquely bias corrected from the multi-model averaged forecasted SST from the two coupled ocean-atmosphere models. Our analysis reveals: (a) The two-tier forecast system has seasonal prediction skill for precipitation that is comparable (over the Southeast Asian monsoon) or even higher (over the South Asian monsoon) than the coupled ocean-atmosphere. For seasonal anomalies of the surface temperature the results are more comparable across models, with all of them showing higher skill than that for precipitation. (b) Despite the improvement from the uncoupled AGCM all models in this study display a deterministic skill for seasonal precipitation anomalies over the Asian summer monsoon region to be weak. But there is useful probabilistic skill for tercile anomalies of precipitation and surface temperature that could be harvested from both the coupled and the uncoupled climate models. (c) Seasonal predictability of the South Asian summer monsoon (rainfall and temperature) does seem to stem from the remote ENSO forcing especially over the Indian monsoon region and the relatively weaker seasonal predictability in the Southeast Asian summer monsoon could be related to the comparatively weaker teleconnection with ENSO. The uncoupled AGCM with the bias corrected SST is able to leverage this teleconnection for improved seasonal prediction skill of the South Asian monsoon relative to the coupled models which display large systematic errors of the tropical SST's. [ABSTRACT FROM AUTHOR]

In a transect study involving 15 mature seasonally dry tropical forests growing on uniform geological substrate in the Yucatan Peninsula, Mexico, we analyzed the influence of a large reduction in mean annual precipitation (1,036–537 mm year −1) on carbon (C) and nitrogen (N) pools in soils. We investigated the C content in organic soil and in active fraction pools (organic matter and microbial biomass) and analyzed the dependence of these pools on precipitation. Carbon (total, inorganic and organic, and in microbial biomass) and N (total) concentrations in bulk soil decreased as rainfall increased from <600 mm year −1 >1,000 mm year −1. Additionally, in all organic matter fractions, C and N concentrations generally decreased with greater precipitation. Soil average C mineralization decreased by 61 % from the wettest to the driest region. Reduced precipitation during the dry season increased microbial biomass C and water-extractable C concentrations and decreased the C concentration in organic matter fractions. No other significant changes were observed between seasons in C concentrations, N concentrations or C mineralization. Overall, we conclude that physical (macroclimate) and biological processes are more active in soils in the wettest region, resulting in a faster turnover of organic matter. [ABSTRACT FROM AUTHOR]

Changes in precipitation exert an enormous impact on human life, and it is of vital importance to study regular patterns of meteorological and hydrological events. In order to explore the changing spatial and temporal patterns of precipitation amounts, precipitation extremes and precipitation concentration in Jiangxi province in southeast China between 1960 and 2008, several precipitation indices series were analysed using the Mann-Kendall test in this study. Our results indicate remarkable differences among the stations with negative and positive precipitation trends at the annual, seasonal and monthly scales, significant increasing trends are mainly found during January, August, winter and summer, while significant decreasing trends mostly are observed during October and autumn. For precipitation extremes, most precipitation indices suggest that both the intensity and the days of extreme precipitation are increasing; the mean precipitation amount, especially, on a wet day shows a significant positive trend. When it comes to precipitation concentration, the monthly rainfall heterogeneity shows an insignificant downward trend, while the contribution of the days with greatest rainfall displays an insignificant upward trend. Furthermore, the long-range persistence is detected for changing process of precipitation amount, extreme precipitation and precipitation concentration using the Rescaled Range Analysis. [ABSTRACT FROM AUTHOR]

Based on the NCEP/NCAR reanalysis data, the COBE sea surface temperature (SST) and the GPCC precipitation, the influences of El Niño-South Oscillation (ENSO) on the variability of winter rainfall anomalies in Southeast China is analyzed under the synergistic effect of Indian Ocean Dipole (IOD). Winter precipitation and atmospheric circulation of the years of IOD concurring with ENSO are compared with single IOD or ENSO, to reveal the mechanism of synergistic effects on the variability of winter rainfall anomalies in Southeast China. The results show that the correlation between IOD/ENSO and the winter precipitation in Southeast China has increased since 1980s. These correlations were significant in years of IOD and ENSO co-occurrence compared to years of IOD or ENSO only, which is mainly due to the lagged atmospheric thermal and dynamic responses to an IOD forcing in synergy with ENSO. The positive IOD (PIOD) events can trigger and modify the anticyclone to the east of India, which transports moisture from the tropical Indian Ocean to Southeast China. In addition, El Niño events can strengthen the abnormal anticyclone over Philippines in winter, which is conducive to maintain the water vapor channel from the tropical western Pacific to Southeast China. Information flow analysis shows that the causalities between IOD and ENSO were enhanced after 1980s, causing the significant increase in the frequency of winter abnormal precipitation in the years of IOD and ENSO concurrence. Furthermore, the higher frequency of PIOD with El Niño (compared to negative IOD with La Niña) attained a ratio of 2:1 after the 1980s, enhancing the Southeast China winter precipitation events associated with IOD and ENSO and the generation of interdecadal variability. This study is helpful to understand the mechanisms of winter precipitation changes in Southeast China, and to improve the forecast accuracy of winter extreme precipitation events. [ABSTRACT FROM AUTHOR]

The influence of increased horizontal resolution on regional climate models simulations of 1961-1990 period was investigated with a focus on precipitation. The main attention was paid to the annual cycle of precipitation described by a special characteristic, precipitation half-time. Two models (RegCM3 and ALADIN-CLIMATE/CZ), both of them in two horizontal resolutions (25 and 10 km), were used. An evaluation of model simulations with 25 km resolution on the European domain is presented as well as a more detailed evaluation of both 25 and 10 km versions on the area of the Czech Republic. Generally, the effects of increased horizontal resolution vary with climate model and evaluated characteristic. For the precipitation amount and the dependence of precipitation amount on altitude, the increase in horizontal resolution decreases the accuracy of results in both models. For the simulation of annual precipitation cycle and the precipitation half-time, RegCM3 results improved with the increased horizontal resolution, whereas ALADIN-CLIMATE/CZ results worsened. [ABSTRACT FROM AUTHOR]

Dozens of studies have been done in recent years documenting factors in large-scale models that affect the simulation of the Madden-Julian oscillation (MJO). All of these studies discuss processes that affect heating in some facet. In this study, we examine various heating adjustments in Community Atmospheric Model version 4 (CAM4) to determine what the vertical and horizontal heating distributions need to look like in order to simulate a realistic MJO. Heating is added to CAM4 using two different methods. In the first method, we add top-, bottom-, or middle-heavy heating blobs at various locations for each phase of the MJO. We describe a new technique for adding these heating perturbations in CAM4. In the second method, we add observed latent heating profiles from the tropical rainfall measuring mission Precipitation Radar to CAM4 in order to more accurately depict both the horizontal and vertical distribution of heating throughout the Tropics. We find that a realistic vertical and horizontal distribution of heating is critical for accurate representation of the MJO in CAM4. Observed heating distributions are top-heavy, but merely putting idealized top-heavy heating blobs into CAM4 does not produce an MJO as realistic as inputting the observed spatial distributions. Improvements in the simulation of the MJO are also seen with an interactive ocean, but the improvements are not as large as those seen using realistic heating distributions and prescribed SSTs. [ABSTRACT FROM AUTHOR]

Climate change is projected to have serious environmental, economic, and social impacts on Ghana, particularly on rural farmers whose livelihoods depend largely on rainfall. The extent of these impacts depends largely on awareness and the level of adaptation in response to climate change. This study examines the perception of farmers in Sekyedumase district of Ashanti region of Ghana on climate change and analyzes farmers' adaptation responses to climate change. A hundred and eighty farming households were interviewed in February and October 2009. Results showed that about 92% of the respondents perceived increases in temperature, while 87% perceived decrease in precipitation over the years. The major adaptation strategies identified included crop diversification, planting of short season varieties, change in crops species, and a shift in planting date, among others. Results of logit regression analysis indicated that the access to extension services, credit, soil fertility, and land tenure are the four most important factors that influence farmers' perception and adaptation. The main barriers included lack of information on adaptation strategies, poverty, and lack of information about weather. Even though the communities are highly aware of climate issues, only 44.4% of farmers have adjusted their farming practices to reduce the impacts of increasing temperature and 40.6% to decreasing precipitation, giving lack of funds as the main barrier to implementing adaptation measure. Implications for policymaking will be to make credit facilities more flexible, to invest in training more extension officers and more education on climate change and adaptation strategies. [ABSTRACT FROM AUTHOR]

Compared are the estimates or regional changes in temperature and precipitation on the territory of Russia for two methods of the spatial averaging of meteorological station data, one of which is adapted to the sparse observational network and takes account of the station weights proportional to the area of their influence. Considered are several variants of the zoning with the separation of the different number of regions. Formulated is a criterion of the zoning adequacy to the problem of the revelation and analysis of regional climate changes. Estimated is the representativeness of the network of observations of temperature and precipitation for separate regions. Presented are the estimates of regional trends of air temperature and precipitation for the century interval and for the recent decades obtained on the basis of the full archive of available data for the zoning attached to the administrative division of the Russian Federation into the federal districts. [ABSTRACT FROM AUTHOR]

A distinctive feature of Earth’s sedimentary systems is that they all involve the interaction between a nearly-horizontal “equilibrium line,” controlling mass supply, and a dynamic sedimentary surface. For glacial systems, this is the snow line or firn line, approximating a zero-degree atmospheric isotherm. For sedimentary basin systems it is sea level or baselevel. For deep ocean carbonate sediments it is the calcite compensation depth or lysocline. First-order considerations in each case suggest a positive feedback on mass supply as the surface builds upwards (and negative feedback if the surface drops). In the first two cases, outstanding paleo-climate problems exist wherein recorded past sedimentary cycles have asymmetric amplitudes that appear too large compared to deduced vertical movements of the respective equilibrium lines. These problems are familiarly known as the “100-kiloyear Pleistocene ice age cycle” and the “million year high-order Cretaceous relative sea level cycles.” Here, I discuss the emerging commonalities that surround these two amplified cycles, emphasizing the ubiquitous presence of a relative equilibrium line dynamic, and which for glacial systems has long been seen as providing a mass supply feedback that can reconcile the disparity between the forcing and the response. I suggest that, in the same way that continental ice sheets have been modeled as passive sedimentary systems that can freely oscillate with little or no snowline forcing, sedimentary basin systems may be capable of similar behavior without vertical sea level change and illustrate the concepts with a low-order model. Sedimentary indicators for relative sea level change may be displaying disproportionately large responses to small eustatic sea level changes, due to internal positive feedbacks. [ABSTRACT FROM AUTHOR]

Global Climate Models (GCMs) project moderate warming along with increases in atmospheric CO2 for California Mediterranean type ecosystems (MTEs). In water-limited ecosystems, vegetation acts as an important control on streamflow and responds to soil moisture availability. Fires are also key disturbances in semi-arid environments, and few studies have explored the potential interactions among changes in climate, vegetation dynamics, hydrology, elevated atmospheric CO2 concentrations and fire. We model ecosystem productivity, evapotranspiration, and summer streamflow under a range of temperature and precipitation scenarios using RHESSys, a spatially distributed model of carbon–water interactions. We examine the direct impacts of temperature and precipitation on vegetation productivity and impacts associated with higher water-use efficiency under elevated atmospheric CO2. Results suggest that for most climate scenarios, biomass in chaparral-dominated systems is likely to increase, leading to reductions in summer streamflow. However, within the range of GCM predictions, there are some scenarios in which vegetation may decrease, leading to higher summer streamflows. Changes due to increases in fire frequency will also impact summer streamflow but these will be small relative to changes due to vegetation productivity. Results suggest that monitoring vegetation responses to a changing climate should be a focus of climate change assessment for California MTEs. [ABSTRACT FROM AUTHOR]

In addition to air temperature at 2 m above ground, the following water balance components are considered: precipitation amount, potential and real evapotranspiration, surface runoff, recharge of water into the soil, loss of water from the soil, soil moisture content, and measured river discharge. Monthly air temperature and values of all water balance components (some of calculated using the Palmer method) have been considered for 24 weather stations across Croatia for the period 1951–2000, and for the Zagreb-Grič station for a much longer period, 1862–2000. The Sava River discharge for two hydrological stations (Zagreb and Županja) for the period 1931–2000 has also been used. Twenty-five year moving averages have been calculated from annual mean values and, – for air temperature only, a principal component analysis has been performed. We have found a long-term positive trend in air temperature, and potential and real evapotranspiration; and a negative trend in runoff (discharge) over almost the whole of Croatia, while the moving-average precipitation amounts show cyclical variation. No obvious trend for the recharge of water into the soil and its losses from the soil have been found, however, a negative trend in soil moisture content has been observed. The positive trends in air temperature and potential (real) evapotranspiration and the negative trends in soil moisture content and runoff (discharge) are consistent (to some degree) with recent global climate warming. This fact strengthens the importance of this study. [ABSTRACT FROM AUTHOR]

This paper aims at proposing a way to get round the intrinsic deadlocks of the economic assessment of climate change impacts (absence of consistent baseline scenario and of credible description of adaptation behaviours under uncertainty). First, we use climate scenarios from two models of the PRUDENCE project (HadRM3H and ARPEGE) to search for cities whose present climates can be considered as reasonable analogues of the future climates of 17 European cities. These analogues meet rather strict criteria in terms of monthly mean temperature, total annual precipitations and monthly mean precipitations. Second, we use these analogues as a heuristic tool to understand the main features of the adaptation required by climate change. The availability of two analogues for each city provides a useful estimate of the impact of uncertainty on the required adaptation efforts. Third, we carry out a cost assessment for various adaptation strategies, taking into account the cost of possible ill-adaptations due to wrong anticipations in a context of large uncertainty (from sunk-costs to lock-in in suboptimal adaptation choices). We demonstrate the gap between an enumerative approach under perfect expectation and a calculation accounting for uncertainty and spillover effects on economic growth. [ABSTRACT FROM AUTHOR]

The spatial and temporal variability of winter precipitation and its links to the large-scale atmospheric circulation patterns in Romania are examined. The data set is composed of observed rainfall at 30 meteorological stations during the 1961–1996 period. The large-scale field is represented by the observed geopotential height at 500 hPa (Z500) over the same period, covering the latitudinal belt between 20° N–90° N (resolution 2.5°×2.5°). The Standard Normal Homogeneity Test (SNHT) is applied to detect inhomogeneities in the data, and the Mann-Kendall and Pettitt non-parametric tests are used in order to identify trends and change points in the winter precipitation time series. The empirical orthogonal functions (EOF) technique is used for data reduction in order to highlight the basic patterns of rainfall variability in Romania. The covariance map between precipitation EOF time series (PCs) and the Z500 field, as well as the correlation coefficients between the PCs and circulation indices are calculated in order to identify the influence of large-scale circulation patterns on winter precipitation in Romania. A significant decreasing trend is identified in winter precipitation with a downward shift in winter 1969/1970, most significant from a statistical point of view in the extra-Carpathian region. This change seems to be real since the SNHT test does not reveal any inhomogeneity during the period tested. Significant relationships are found between winter precipitation variability in Romania and the large-scale circulation pattern, such as the North Atlantic Oscillation and the blocking phenomenon in the Atlantic-European sector. The positive phase of the NAO and the reduction in blocking activity could be one of the causes of the decrease in winter precipitation in Romania. [ABSTRACT FROM AUTHOR]