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More intense rainfall may cause a range of negative impacts upon society and the environment. In this study we analyzed trends in extreme ETCCDI (Expert Team on Climate Change Detection and Indices) rainfall indices in Montenegro for the period 1951-2010. Montenegro has been poorly studied in terms of rainfall extremes, yet it contains the wettest Mediterranean region known as Krivo²ije. Several indices of precipitation extremes were assessed including the number of dry days and rainfall totals, and their trends to identify possible changes. The results generally suggest that the number of days with precipitation decreased while rainfall intensity increased particularly in south-western parts of the country. A slight tendency towards intense rainfall events is suggested. Calculated trends for each index are spatially presented and examined using a plotGoogleMaps software package. This study also examined spatial pattern of relationship between extreme rainfall indices and North Atlantic Oscillation. Results suggested negative, mainly statistically significant correlations at annual, winter and autumn scale. [ABSTRACT FROM AUTHOR]

This paper investigates the impact and potential use of the cut cell vertical discretisation for forecasts of 5 days and climate simulations. A first indication of the usefulness of this new method is obtained by a set of five-day forecasts, covering January 1989 by forecasts. The model area was chosen to include much of Asia, the Himalayas and Australia. The cut cell model LMZ provides a much more accurate representation of mountains on model forecasts than the terrain following coordinate used for comparison. Therefore we are in particular interested in potential forecast improvements in the target area downwind of the Himalaya, over South East China, Korea and Japan. The LMZ has been tested so far extensively for one-day forecasts on an European area. Following indications of a reduced temperature error for the short forecasts, this paper investigates the model error for five days in an area influenced by strong orography. The forecasts indicated a strong impact of the cut cell discretisation on forecast quality. The cut cell model is available only of an older (2003) Version of the model LM. It was compared using a control model differing by the use of the terrain following coordinate only. The cut cell model improved the precipitation forecasts of this old control model everywhere by a large margin. An improved version of the terrain following model LM has been developed since then under the name CLM. The CLM has been used and tested in all climates, while the LM was used for small areas in higher latitudes. The precipitation forecasts of cut cell model were compared also to the CLM. As the cut cell model LMZ did not incorporate the developments for CLM since 2003, the precipitation forecast of the CLM was not improved in all aspects. However, for the target area downstream of the Himalaya, the cut cell model improved the prediction of the monthly precipitation forecast even in comparison with the modern model version CLM considerably. The cut cell discretisation seems to improve in particular the localisation of precipitation, while the improvements leading from LM to CLM had a positive effect mainly on amplitude. [ABSTRACT FROM AUTHOR]

As part of the High Definition Clouds and Precipitation for advancing Climate Prediction Observational Prototype Experiment (HOPE), a high spatial density network of 99 silicon photodiode pyranometers was set up around Jülich (10km×12km area) from April to July 2013, to capture the variability in the radiation field at the surface induced by small-scale cloud inhomogeneity. Each of these autonomously operated pyranometer stations was equipped with weather sensors for simultaneous measurements of ambient air temperature and relative humidity. In this paper, we provide the details of this unique setup of the pyranometer network and the data analysis with initial quality screening procedure we adopted. We also present some exemplary cases consisting of the days with clear, broken cloudy and overcast skies to assess our spatio-temporal observations from the network, and validate their consistency with other collocated radiation measurements available during the HOPE period. [ABSTRACT FROM AUTHOR]

The article presents information on a study conducted on the impact of climate change on agriculture. In the study, Community Land Model (CLM)-Crop was validated against observations from two agricultural sites in the U.S., that were planted with maize and soybean. CLM-Crop was compared with the standard CLM3.5, which is associated with crops as grass. The study found that crop yields and productivity had a negative correlation with temperature, and a positive correlation with precipitation.

Recent studies have drawn attention to a significant weakening trend of the South Asian monsoon circulation and an associated decrease in regional rainfall during the last few decades. While surface temperatures over the region have steadily risen during this period, most of the CMIP (Coupled Model Intercomparison Project) global climate models have dificulties in capturing the observed decrease of monsoon precipitation, thus limiting our understanding of the regional land surface response to monsoonal changes. This problem is investigated by performing two long-term simulation experiments, with and without anthropogenic forcing, using a variable resolution global climate model having high-resolution zooming over the South Asian region. The present results indicate that anthropogenic effects have considerably influenced the recent weakening of the monsoon circulation and decline of precipitation. It is seen that the simulated increase of surface temperature over the Indian region during the post-1950s is accompanied by a significant decrease of monsoon precipitation and soil moisture. Our analysis further reveals that the land surface response to decrease of soil moisture is associated with significant reduction in evapotranspiration over the Indian land region. A future projection, based on the representative concentration pathway 4.5 (RCP4.5) scenario of the Intergovernmental panel on Climate Change (IPCC), using the same high-resolution model indicates the possibility for detecting the summer-time soil drying signal over the Indian region during the 21st century, in response to climate change. While these monsoon hydrological changes have profound socioeconomic implications, the robustness of the high-resolution simulations provides deeper insights and enhances our understanding of the regional land surface response to the changing South Asian monsoon. [ABSTRACT FROM AUTHOR]

Global climate change has numerous implications for members of mountain communities who feel the impacts in both physical and social dimensions. In the Western Himalayas of India, a majority of residents maintain a livelihood strategy that includes a combination of subsistence or small-scale agriculture, seasonal pastoral migration, male out-migration, and localized natural resource extraction. Particularly under conditions of heavy male outmigration, but throughout the region, mountain women play a key role in providing labor and knowledge related to the management of local natural resources, yet often lack authority in related political and economic decision-making processes. This gap has important implications for addressing the impacts of climate change: while warming temperatures, irregular patterns of precipitation and snowmelt, and changing biological systems present challenges to the viability of these traditional livelihood portfolios throughout the region, mountain women increasingly face new challenges in their roles as household managers that have not adequately been emphasized in larger scale planning for climate change adaptation and mitigation. These challenges are complex in nature, and are shaped not only by gender issues but also interacting factors such as class, caste, ethnicity, and age (among others). In this paper, we review the main arguments behind the discursive gender/climate change nexus, discuss the implications for gendered vulnerabilities and transformation of adaptive capacities in the region, and suggest ways that researchers and policymakers seeking to promote "climate justice" can benefit from the incorporation of gender-based perspectives and frameworks. [ABSTRACT FROM AUTHOR]

We evaluate the isotopic composition of water vapor and precipitation simulated by the LMDZ GCM over Siberia using several datasets: TES and GOSAT satellite observations of tropospheric water vapor, GNIP and SNIP precipitation networks, and daily, in-situ measurements of water vapor and precipitation at the Kourovka site in Western Siberia. We use dD vs. humidity diagrams to explore the complementarity of these two variables to interpret model biases in terms of the representation of processes. LMDZ captures the spatial, seasonal and daily variations reasonably well. It systematically overestimates dD in the vapor and precipitation, a bias that is most likely associated with a misrepresentation of air mass origin. The performance of LMDZ is put in the context of other isotopic models from the SWING2 models. There is significant spread among models in the simulation of dD, and of the dD vs. humidity relationship. This confirms that dD brings additional information compared to humidity only. We specifically investigate the added value of water isotopic measurements to interpret the warm and dry bias feature by most GCMs over mid and high latitude continents in summer. LMDZ simulates the strongest dry bias on days when it simulates the strongest enriched bias in dD. The analysis of the slopes in dD vs. humidity diagrams and of processes controlling dD and humidity variations suggests that the cause of the moist bias could be either a problem in the large-scale advection transporting too much dry and warm air from the south, or insufficient surface evaporation. [ABSTRACT FROM AUTHOR]

A model was developed to simulate spatial, seasonal and interannual variations in vegetation in response to temperature, precipitation and atmospheric CO2 concentrations; the model addresses shortcomings in current implementations. The model uses the minimum of 12 temperature and precipitation constraint functions to simulate NDVI. Functions vary based on the Köppen-Trewartha climate classification to take adaptations of vegetation to climate into account. The simulated NDVI, referred to as the climate constrained vegetation index (CCVI), captured the spatial variability (0.82 < r <0.87), seasonal variability (median r = 0.83) and interannual variability (median global r = 0.24) in NDVI. The CCVI simulated the effects of adverse climate on vegetation during the 1984 drought in the Sahel and during dust bowls of the 1930s and 1950s in the Great Plains in North America. A global CO2 fertilisation effect was found in NDVI data, similar in magnitude to that of earlier estimates (8% for the 20th century). This effect increased linearly with simple ratio, a transformation of the NDVI. Three CCVI scenarios, based on climate simulations using the representative concentration pathway RCP4.5, showed a greater sensitivity of vegetation towards precipitation in Northern Hemisphere mid latitudes than is currently implemented in climate models. This higher sensitivity is of importance to assess the impact of climate variability on vegetation, in particular on agricultural productivity. [ABSTRACT FROM AUTHOR]

Gridded precipitation (PRP) data have been largely used in diagnostic studies on the climate variability in several time scales, as well as to validate model results. The three most used gauge-based PRP datasets are from the Global Precipitation Climatology Centre (GPCC), University of Delaware (UDEL), and Climate Research Unit (CRU). This paper evaluates the performance of these datasets in reproducing spatiotemporal PRP climatological features over the entire South America (SA) for the 1901–2015 period, aiming to identify the differences and similarities among the datasets as well as time intervals and areas with potential uncertainties involved with these datasets. Comparisons of the PRP annual means and variances between the 1901–2015 period and the non-overlapping 30-year subperiods of 1901–1930, 1931–1960, 1961–1990, and the 25-year subperiod of 1991–2015 for each dataset show varying means of the annual PRP over SA depending on the subperiod and dataset. Consistent patterns among datasets are found in most of southeastern SA and southeastern Brazil, where they evolved gradually from less to more rainy conditions from 1901–1930 to the 1991–2015 subperiod. All three datasets present limitations and uncertainties in regions with poor coverage of gauge stations, where the differences among datasets are more pronounced. In particular, the GPCC presents reduced PRP variability in an extensive area west of 50° W and north of 20° S during the 1901–1930 subperiod. In monthly time scale, PRP time series in two areas show differences among the datasets for periods before 1941, which are likely due to spurious or missing data: central Bolivia (CBO), and central Brazil (CBR). The GPCC has less monthly variability before 1940 than the other two datasets in these two areas, and UDEL presents reduced monthly variability before 1940 and spurious monthly values from May to September of the years from 1929 to 1941 in CBO. Thus, studies with these three datasets might lead to different results depending on the study domain and period of analysis, in particular for those including years before 1941. The results here might be relevant for future diagnostic and modelling studies on climate variability from interannual to multidecadal time scales. [ABSTRACT FROM AUTHOR]

Quantifying how C fluxes will change in the future is a complex task for models because of the coupling between climate, hydrology, and biogeochemical reactions. Here we investigate how pedogenesis of the Peoria loess, which has been weathering for the last 13 kyr, will respond over the next 100 yr of climate change. Using a cascade of numerical models for climate (ARPEGE), vegetation (CARAIB) and weathering (WITCH) we explore the effect of an increase in CO2 of 315 ppmv (1950) to 700 ppmv (2100 projection). The increasing CO2 results in an increase in temperature along the entire transect. In contrast, drainage increases slightly for a focus pedon in the South but decreases strongly in the North. These two variables largely determine the behavior of weathering. In addition, although CO2 production rate increases in the soils in response to global warming, the rate of diffusion back to the atmosphere also increases, maintaining a roughly constant or even decreasing CO2 concentration in the soil gas phase. Our simulations predict that temperature increasing in the next 100 yr causes the weathering rates of the silicates to increase into the future. In contrast, the weathering rate of dolomite -- which consumes most of the CO2-decreases due to its retrograde solubility in both end members (South and North) of the transect. We thus infer slower rates of advance of the dolomite reaction front into the subsurface, and faster rates of advance of the silicate reaction front. However, additional simulations for 9 pedons located along the North--South transect show that dolomite weathering will increase in the central part of the Mississippi Valley, owing to a maximum in the response of vertical drainage to the ongoing climate change. The carbonate reaction front can be likened to a terrestrial lysocline because it represents a depth interval over which carbonate dissolution rates increase drastically. However, in contrast to the lower pH and shallower lysocline expected in the oceans with increasing atmospheric CO2, we predict an acceleration of the lysocline deepening in soils in the central area of the Mississippi Valley, but a slowdown of its deepening in the Southern and Northern section. This result illustrates the complex behavior of carbonate weathering facing short term global climate change. Predicting the global response of terrestrial weathering to increased atmospheric CO2 and temperature in the future will mostly depend upon our ability to make precise assessments of which areas of the globe increase or decrease in precipitation and soil drainage. [ABSTRACT FROM AUTHOR]

The article presents a study that demonstrates the usefulness of the Norwegian Climate Center's Earth System Model (NorESM1-M) in the coupled model intercomparison project phase 5 (CMIP5). It outlines the role of the model in providing complementary results to the evaluation of possible man made climate change. It also demonstrates the effectiveness of the model in accurately depicting the changes in the atmospheric water cycle in precipitation events.

The article focuses on the Future Flows Climate dataset which was developed to offer a set of climate change projections for Great Britain. It says that the Future Flows Climate is derived from the ensemble Projection HadRM3-PPE, part of the basis of UK Climate Projection 2009 (UKCP09) and adds projections on available precipitation and potential evapotranspiration. Furthermore, it mentions the limitations of the dataset, as well as the ways to access the data.

This study investigates how warming and changes in precipitation may affect the cycling of carbon (C) in tundra soils, and between high arctic tundra and the atmosphere. We quantified ecosystem respiration (Reco) and soil pore space CO2 in a polar semi-desert under current and future climate conditions simulated by long-term experimental warming (+2 °C, +4 °C), water addition (+50% summer precipitation) and a combination of both (+4 °C x +50% summer precipitation). We also measured the 14C content of Reco and soil CO2 to distinguish young C cycling rapidly between the atmosphere and the ecosystem from older C stored in the soil for centuries to millennia. We identified changes in the amount and timing of precipitation as a key control of the magnitude, seasonality and sources of Reco in a polar semi-desert. Throughout each summer, small (<4 mm) precipitation events during drier periods triggered the release of very old C pulses from the deep soil, while larger precipitation events (>4 mm), more winter snow and experimental irrigation were associated with higher Reco fluxes and the release of recently-fixed (young) plant C. Warmer summers and experimental warming also resulted in higher Reco fluxes (+2 °C > +4 °C), but coincided with losses of older C. We conclude that in high arctic dry tundra systems, future magnitudes and patterns of old C emissions will be controlled as much by the summer precipitation regime and winter snowpack as by warming. The release of older soil C is of concern as it may lead to net C losses from the ecosystem. Therefore, reliable predictions of precipitation amounts, frequency, and timing are required to predict the changing C cycle in the High Arctic. [ABSTRACT FROM AUTHOR]

Climate and land use change in the Mediterranean region is expected to affect natural and agricultural ecosystems by decreases in precipitation, increases in temperature as well as biodiversity loss and anthropogenic degradation of natural resources. Demographic growth in the Eastern and Southern shores will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development pave the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments on the consequences of land use transitions, the influence of management practices and climate change impacts. [ABSTRACT FROM AUTHOR]

JULES-crop is a parametrisation of crops in the Joint UK Land Environment Simulator (JULES). We investigate the sources of the interannual variability in the modelled maize yield, using global runs driven by reanalysis data, with a view to understanding the impact of various approximations in the driving data and initialisation. The standard forcing dataset for JULES consists of a combination of meteorological variables describing precipitation, radiation, temperature, pressure, specific humidity and wind, at subdaily time resolution. We find that the main characteristics of the modelled yield can be reproduced with a subset of these variables and using daily forcing, with inter nal disaggregation to the model timestep. This has implications in particular for the use of the model with seasonal forcing data, which may not have been provided at subdaily resolution for all required driving variables. We also investigate the effect on annual yield of initialising the model with climatology on the sowing date. This approximation has the potential to considerably simplify the use of the model with seasonal forecasts, since obtaining observations or reanalysis output for all the initialisation variables required by JULES for the start date of the seasonal forecast would present significant practical challenges. [ABSTRACT FROM AUTHOR]

Previous work has failed to address fully the response of (autotrophic and het- erotrophic) respiration to grazing and nitrogen (N) addition in different ecosystems, particularly in alpine grasslands outside the growing season. From 2010 to 2011, we combined two methods (static closed chambers and a closed dynamic soil CO2 flux system) in a controlled field experiment in an alpine grassland in the Tianshan Mountains. We examined the effects of grazing and N application on ecosystem respiration (Re) both outside (NGS) and during (GS) the growing season and determined the pattern of Re in relation to climate change. There was no significant change in CO2 emissions under grazing or N application. Heterotrophic respiration (Rh) accounted for 78.5% of Re. Re, Rh and autotrophic respiration (Ra) outside the growing season were equivalent to 12.9, 14.1 and 11.4% of the respective CO2 fluxes during the growing season. In addition, our results indicate that precipitation (soil water content) plays a critical role in Ra in this cold and arid environment. Both Rh and Re were sensitive to soil temperature. Moreover, our results suggest that grazing and N addition exert no significant effect on CO2 emissions in alpine grassland but may alter soil carbon stocks in alpine grassland. [ABSTRACT FROM AUTHOR]

We use the process-based VS (Vaganov-Shashkin) model to investigate whether a regional Pinus halapensis tree-ring chronology from Tunisia can be simulated as a function of climate alone by employing a biological model linking day length and daily temperature and precipitation (AD 1959-2004) from a climate station to ring-width variations. We use two periods to calibrate (1982-2004) and verify (1959-1981) the model. We have obtained highly significant positive correlation between the residual chronology and estimated growth curve (r = 0.76 p < 0.001). The model shows that the average duration of the growing season is 191 days. On average, soil moisture limits tree-ring growth for 128 days and temperature for 63 days. [ABSTRACT FROM AUTHOR]

The migratory locust, Locusta migratoria (L.), a significant grasshopper species known for its ability to form large swarms and cause extensive damage to crops and vegetation, is subject to the influence of climate change. This research paper employs geographic information system (GIS) and MaxEnt ecological modelling techniques to assess the impact of climate change on the distribution patterns of L. migratoria. Occurrence data and environmental variables are collected and analysed to create predictive models for the current and future distribution of the species. The study highlights the crucial role of climate factors, particularly temperature and precipitation, in determining the locust's distribution. The MaxEnt models exhibit high-performance indicators, accurately predicting the potential habitat suitability of L. migratoria. Additionally, specific bioclimatic variables, such as mean temperature and annual precipitation, are identified as significant factors influencing the species' presence. The generated future maps indicate how this species will invade new regions especially in Europe. Such results predict the risk of this destructive species for many agriculture communities as a direct result of a warming world. The research provides valuable insights into the complex relationship between locust distribution and environmental factors, enabling the development of effective strategies for locust management and early warning systems to mitigate the impact on agriculture and ecosystems. [ABSTRACT FROM AUTHOR]

The hydrological cycle is predicted to become more intense in future climates, with both larger precipitation events and longer times between events. Redistribution of precipitation may occur both within and across seasons, and the resulting wide fluctuations in soil water content may dramatically affect plants. Though these responses remain poorly understood, recent research in this emerging field suggests the effects of redistributed precipitation may differ from predictions based on previous drought studies. We review available studies on both extreme precipitation (redistribution within seasons) and seasonal changes in precipitation (redistribution across seasons) on grasslands and forests. Extreme precipitation differentially affected Aboveground Net Primary Productivity (ANPP), depending on whether extreme precipitation led to increased or decreased soil water content (SWC), which differed based on the current precipitation at the site. Specifically, studies to date reported that extreme precipitation decreased ANPP in mesic sites, but, conversely, increased ANPP in xeric sites, suggesting that plant available water is a key factor driving responses to extreme precipitation. Similarly, the effects of seasonal changes in precipitation on ANPP, phenology, and leaf and fruit development varied with the effect on SWC. Reductions in spring or summer generally had negative effects on plants, associated with reduced SWC, while subsequent reductions in autumn or winter had little effect on SWC or plants. Similarly, increased summer precipitation had a more dramatic impact on plants than winter increases in precipitation. The patterns of response suggest xeric biomes may respond positively to extreme precipitation, while comparatively mesic biomes may be more likely to be negatively affected. And, seasonal changes in precipitation during warm or dry seasons may have larger effects than changes during cool or wet seasons. Accordingly, responses to redistributed precipitation will involve a complex interplay between plant available water, plant functional type, soil type and resultant influences on plant phenology, growth and water relations. These results highlight the need for experiments across a range of plant functional types, critical for predicting future vegetation responses to future climates. [ABSTRACT FROM AUTHOR]

Spatial information on inundation dynamics is expected to improve greenhouse gas estimates in climate models. Satellite data can provide land cover information from local to global scale. The detection capability for dynamics is however limited. Cloud cover and daylight independent methods are required for frequent updates. Suitable are therefore sensors which make use of microwaves. The purpose of the present study is to assess such data for determination of wetland dynamics from the viewpoint of use in climate models of the boreal and tundra environments. The focus is on synthetic aperture radar (SAR) operating in C-band due to, among microwave systems, comparably good spatial resolution and data availability. Continuity is also expected for such systems. Simple classification algorithms can be applied to detect open water in an automatised way allowing the processing of time series. Such approaches are robust when the water surface is smooth. C-band data from ENVISAT ASAR (Advanced SAR) operating in wide swath mode (150m resolution) have been investigated for implementation of an automated detection procedure of open water fraction. More than 4000 samples (single acquisitions tiled into 0.5 degree grid cells) have been analysed for July/August 2007 and 2008. Modification of input parameters results in differences below 1% open water fraction. The actual challenge is the frequent occurrence of waves due to wind and precipitation. This reduces the separability of the water class from other land cover. The possible update intervals for surface water extent are therefore decreased considerably. Statistical measures of the backscatter distribution can be applied in order to retrieve the for classification suitable data. The Pearson correlation between each sample dataset and a location specific representation of the bimodal distribution has been used for assessment. On average only 40% of acquisitions allow a separation of the open water class. Satellite data are available every 2-3 days over the Western Siberian study region. With respect to the irregular acquisition intervals and varying length of unsuitable weather periods a minimum update interval of 10 days is suggested for the Northern Eurasian test case. Although SAR data availability is currently constraint future satellite missions which aim for operational services such as Sentinel-1 with its C-band SAR instrument may provide the basis for inundation monitoring in support of climate modelling. [ABSTRACT FROM AUTHOR]

The paper explores the occurrence of minimal precipitation extremes at specific meteorological stations in the southeastern region of Serbia. With climate change leading to increased instances of droughts, these natural phenomena have garnered heightened interest due to their negative impacts on society, environment, and the economy. Employing the SPI-12 index in the southeastern part of Serbia from 1946 to 2021, the study sheds light on the vulnerability of this natural phenomenon in the observed stations. Understanding historical manifestation of these events helps water resource managers, farmers and policymakers manage these risks in the southeastern region of Serbia. [ABSTRACT FROM AUTHOR]

Precipitation and temperature drive many aspects of terrestrial ecosystem function. Climate change scenarios predict increasing precipitation variability and temperature, and long term experiments are required to evaluate the ecosystem consequences of interannual climate variation, increased growing season (intra-annual) rainfall variability, and warming. We present results from an experiment applying increased growing season rainfall variability and year round warming in native perennial grassland. During ten years of study, total growing season rainfall varied 2-fold, and we found ~50-200% interannual variability in plant growth and aboveground net primary productivity, leaf carbon assimilation (ACO2), and soil CO2 efflux (JCO2) despite only ~40% variation in mean volumetric soil water content (0-15 cm, Θ15). Interannual variation in soil moisture was thus amplified in most measures of ecosystem response. Differences between years in Θ15 explained the greatest portion (14-52%) of the variation in these processes. Experimentally increased intra-annual rainfall variability doubled the amplitude of intra-annual soil moisture variation and reduced Θ15 by 15%, causing most ecosystem processes to decrease 8-40% in some or all years with increased rainfall variability compared to ambient rainfall timing, suggesting reduced ecosystem rainfall use efficiency. Warming treatments increased 5 cm soil temperature, particularly during spring, fall, and winter. Warming advanced canopy green up in spring, increased winter JCO2, and reduced summer JCO2, and forb ANPP , suggesting that the effects of warming differed in cooler versus warmer parts of the year. We conclude that (1) major ecosystem processes in this grassland may be substantially altered by predicted changes in interannual climate variability, intra-annual rainfall variability, and temperature, (2) interannual climate variation was a larger source of variation in ecosystem function than intra-annual rainfall variability and warming, and (3) effects of increased growing season rainfall variability and warming were small, but ecologically important. The relative effects of these climate drivers are likely to vary for different ecosystem processes and in wetter or drier ecosystems. [ABSTRACT FROM AUTHOR]

The high variability of the sub-desert climate, especially in the south-eastern region of Morocco, has severe socioeconomic impacts on the inhabitant's way of life, as is the case in the Daoura watershed, where this variability is associated with droughts or exceptional rainfall. The data collected from the Guir-Ziz-Rheriss hydraulic agency were processed, corrected and analyzed using the Climatol package (version 4.0.0) developed in R software to homogenize rainfall data. Through this work, the significance and amplitudes of annual and monthly rainfall trends were defined using the Mann-Kendall test and Sens's slope estimator, while comparing the results of raw and homogenized data. The Daoura watershed has a sub-desert climate, and the homogenization process revealed a few rainfall stations with significant positive trends at confidence levels ranging from 90% to 95%. According to the raw and homogenized data, the majority of these stations are located in the High Atlas (CR1) and Anti-Atlasic (CR2) zones, where there is considerable spatiotemporal variability in rainfall from one year to the next. The essential objective of this scientific paper was to analyze the spatiotemporal variability of monthly and annual precipitation and to study their trends through rainfall data homogenized by the climatol package (version 4.0.0) from 13 stations over a period (1957-2018). The contribution of this study to science is the rainfall data it offers, which is useful for managing natural resources in sub-desert areas. [ABSTRACT FROM AUTHOR]

It is well known that rivers connect upstream and downstream ecosystems within watersheds. Here we describe the concept of precipitationsheds to show how upwind terrestrial evaporation source areas contribute moisture for precipitation in downwind sink regions. We illustrate the importance of upwind land cover in precipitationsheds to sustain precipitation in critically water stressed downwind areas, i.e. dryland agricultural areas. We first identify seven regions where rainfed agriculture is particularly vulnerable to reductions in precipitation, and then map their precipitationsheds. We further develop a framework for qualitatively assessing the vulnerability of precipitation for these seven agricultural regions. We illustrate that the sink regions have varying degrees of vulnerability to changes in upwind evaporation rates depending on the extent of the precipitationshed, source region land use intensity and expected land cover changes in the source region. [ABSTRACT FROM AUTHOR]

Impacts of low-latitude, explosive volcanic eruptions on climate and the carbon cycle are quantified by forcing a comprehensive, fully coupled carbon cycle-climate model with pulse-like stratospheric sulfur release. The model represents the radiative and dynamical response of the climate system to volcanic eruptions and simulates a decrease of global and regional atmospheric surface temperature, regionally distinct changes in precipitation, a positive phase of the North Atlantic Oscillation, and a decrease in atmospheric CO2 after volcanic eruptions. The volcanic-induced cooling reduces overturning rates in tropical soils, which dominates over reduced litter input due to soil moisture decrease, resulting in higher land carbon inventories for several decades. The perturbation in the ocean carbon inventory changes sign from an initially weak carbon sink to a carbon source. Positive carbon and negative temperature anomalies in subsurface waters last up to several decades. The multi-decadal decrease in atmospheric CO2 yields an additional radiative forcing that amplifies the cooling and perturbs the Earth System on much longer time scales than the atmospheric residence time of volcanic aerosols. In addition, century-scale global warming simulations with and without volcanic eruptions over the historical period show that the ocean integrates volcanic radiative cooling and responds for different physical and biogeochemical parameters such as steric sea level or dissolved oxygen. Results from a suite of sensitivity simulations with different amounts of sulfur released and from global warming simulations show that the carbon cycle-climate sensitivity, expressed as change in atmospheric CO2 per unit change in global mean surface temperature, depends on the perturbation. On decadal time scales, modeled is several times larger for a Pinatubo-like eruption than for the industrial period and for a high emission, 21st century scenario. [ABSTRACT FROM AUTHOR]

Tropical tree height-diameter (H:D) relationships may vary by forest type and region making large-scale estimates of above-ground biomass subject to bias if they ignore these differences in stem allometry. We have therefore developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical countries. Utilising this database, our objectives were: 1. to determine if H:D relationships differ by geographic region and forest type (wet to dry forests, including zones of tension where forest and savanna overlap). 2. to ascertain if the H:D relationship is modulated by climate and/or forest structural characteristics (e.g. stand-level basal area, A). 3. to develop H:D allometric equations and evaluate biases to reduce error in future local-to-global estimates of tropical forest biomass. Annual precipitation coefficient of variation (PV), dry season length (SD), and mean annual air temperature (TA) emerged as key drivers of variation in H:D relationships at the pantropical and region scales. Vegetation structure also played a role with trees in forests of a high A being, on average, taller at any given D. After the effects of environment and forest structure are taken into account, two main regional groups can be identified. Forests in Asia, Africa and the Guyana Shield all have, on average, similar H:D relationships, but with trees in the forests of much of the Amazon Basin and tropical Australia typically being shorter at any given D than their counterparts elsewhere. The region-environment-structure model with the lowest Akaike's information criterion and lowest deviation estimated stand-level H across all plots to within a median -2.7 to 0.9% of the true value. Some of the plot-to-plot variability in H:D relationships not accounted for by this model could be attributed to variations in soil physical conditions. Other things being equal, trees tend to be more slender in the absence of soil physical constraints, especially at smaller D. Pantropical and continental-level models provided only poor estimates of H, especially when the roles of climate and stand structure in modulating H:D allometry were not simultaneously taken into account. [ABSTRACT FROM AUTHOR]

This study investigates how the climate is changing at individual weather stations around the world by measuring means and extremes. Extensive python code was written to read in the daily data from thousands of stations and compute average yearly temperature, precipitation, and extremes such as heat waves, cold spells, very wet and dry periods. A best-fit line and goodness-of-fit statistic were computed for each statistic at each station. All these linear trends were collected into histograms and geographic distribution plots. It was found that the earth is undergoing significant changes: 97% of all stations are increasing in temperature since 1950, averaging 4° F per century. All measures of extreme heat are increasing, and all measures of extreme cold are decreasing. Almost all stations are recording significant increases in the number of warm days (days above a reference 90th percentile) and heat waves (three consecutive warm days) and the warmest day of the year is getting hotter. There are fewer cold nights and cold spells. The number of frost nights is significantly decreasing, averaging 25 fewer frost nights per year over a century. Changes in precipitation vary by geography: some regions are drier while others are wetter. For example, precipitation changes are strongly varied in both the U.S. and Australia. This study confirms that the earth's climate is rapidly changing in both means and extremes. To help the public better understand climate change, this data is presented in an online map for interactive exploration at http://lillianpetersen.github.io. [ABSTRACT FROM AUTHOR]

The impact of climate change on forest ecosystems may manifest itself by a shift in forest vegetation zones in the landscape northward and into higher elevations. Studies of climate change-induced vegetation zone shifts in forest ecosystems have been relatively rare in the context of European temperate zone (apart from Alpine regions). The presented paper outlines the results of a biogeographic model of climatic conditions in forest vegetation zones applied in the Central European landscape. The objective of the study is a prediction of future silvicultural conditions for the Norway spruce (Picea abies L. Karst.), which is one of the principal tree species within European forests. The model is based on a general environmental dependence of forest vegetation zones on the long-term effect of altitudinal and exposure climates defined by the mean and extreme air temperatures and the amount and distribution of atmospheric precipitation. The climatological data for the model were provided by a validated regional climate database for 2010 – 2090 according to the SRES A1B scenario, bound to specific geo-referenced points in the landscape. The geobiocoenological data in the model were provided by the Biogeography Register database which contains ecological data on the landscape bound to individual cadastres of the entire Czech Republic. The biogeographic model applies special programs (the FORTRAN programming language) in the environment of geographic information systems. The model outputs can be clearly graphically visualized as scenarios of predicted future climatic conditions of landscape vegetation zones. Modelling of the regional scenario of changes in the climatic conditions of forest vegetation zones reveals that in the prediction period of 2070 and beyond, good and very good climatic conditions for the cultivation of forests with dominant Norway spruce will be found only in some parts of its today's native range in forest vegetation zones 5 – 8. Based on the results provided by the regional scenario, the authors of this paper recommend fundamental reassessment of the national strategy of sustainable forest management in the Czech Republic, stipulating that the current practice of spruce cultivation be reduced only to areas specifically defined by the biogeographic model. The paper shows that biogeographic models based on the concept of vegetation zoning can be applied not only in regional scenarios of climate change in the landscape but also as support tools for the creation of strategies of sustainable forest management. [ABSTRACT FROM AUTHOR]

This paper presents a research study of expected precipitation extremes across the Gandaki Province, Nepal. The study used five indices to assess extreme precipitation under climate change. Precipitation output of two Global Climate Models (GCMs) of Coupled Model Intercomparison Project Phase Six (CMIP6) were used to characterize the future precipitation extremes during the rainfall season from June to September (JJAS) and overall days of the year. To characterize extreme precipitation events, we used daily precipitation under the SSP2–4.5 and SSP5–8.5 scenarios from the Beijing Climate Center and China Meteorological Administration, China; and Meteorological Research Institute (MRI), Japan. Considering large uncertainties with GCM outputs and different downscaling (including bias correction) methods, direct use of GCM outputs were made to find change in precipitation pattern for future climate. For 5-, 10-, 20-, 50-, and 100-year return periods, observed and projected 24 h and 72 h annual maximum time series were used to calculate the return level. The result showed an increase in simple daily intensity index (SDII) in the near future (2021–2040) and far future (2081–2100), with respect to the base-year (1995–2014). Similarly, heavy precipitation days (R50 mm), very heavy precipitation days (R100 mm), annual daily maximum precipitation (RX1day), and annual three-day maximum precipitation (RX3day) indices demonstrated an increase in extreme precipitation toward the end of the 21st century. A comparison of R50 mm and R100 mm values showed an extensive (22.6% and 63.8%) increase in extreme precipitation days in the near future and far future. Excessive precipitation was forecasted over Kaski, Nawalparasi East, Syangja, and the western half of the Tanahun region. The expected increase in extreme precipitation may pose a severe threat to the long-term viability of social infrastructure, as well as environmental health. The findings of these studies will provide an opportunity to better understand the origins of severe events and the ability of CMIP6 model outputs to estimate anticipated changes. More research into the underlying physical factors that modulate the occurrence of extreme incidences expected for relevant policies is suggested. [ABSTRACT FROM AUTHOR]

As a result of climate change, rainfall regimes became more extreme over the course of the 20th century, characterised by fewer and larger rainfall events. Such changes are expected to continue throughout the current century. The effect of changes in the temporal distribution of rainfall on ecosystem carbon fluxes is poorly understood, with most available information coming from experimental studies of grassland ecosystems. Here, continuous measurements of ecosystem carbon fluxes and precipitation from the worldwide FLUXNET network of eddy-covariance sites are exploited to investigate the effects of differences in rainfall distribution on the carbon balance of seasonally water-limited shrubland and forest sites. Once the strong dependence of ecosystem fluxes on total annual rainfall amount is accounted for, results show that sites with more extreme rainfall distributions have significantly lower gross productivity, slightly lower ecosystem respiration and consequently a smaller net ecosystem productivity. [ABSTRACT FROM AUTHOR]

Precipitation is a key link in the global water cycle and a proxy for changing climate; therefore, proper assessment of the urban environment’s impact on precipitation (land use, aerosols, thermal properties) will be increasingly important in ongoing climate diagnostics and prediction, Global Water and Energy Cycle (GWEC) analysis and modeling, weather forecasting, freshwater resource management, urban planning–design, and land–atmosphere–ocean interface processes. These facts are particularly critical if current projections for global urban growth are accurate. The goal of this paper is to provide a concise review of recent (1990–present) studies related to how the urban environment affects precipitation. In addition to providing a synopsis of current work, recent findings are placed in context with historical investigations such as Metropolitan Meteorological Experiment (METROMEX) studies. Both observational and modeling studies of urban-induced rainfall are discussed. Additionally, a discussion of the relative roles of urban dynamic and microphysical (e.g., aerosol) processes is presented. The paper closes with a set of recommendations for what observations and capabilities are needed in the future to advance our understanding of the processes. [ABSTRACT FROM AUTHOR]

The aim of this paper is to identify the trends of changes in atmospheric precipitation percolation under the changing climate conditions of Lithuania (the East Baltic region) based on long-term lysimeter studies. Data from 1987–2022 research (n = 1296) was used to determine trends in precipitation infiltration changes. Two 10-year periods, 1989–1998 and 2011–2020, were selected from the whole observation period (1987–2022) to assess changes in precipitation infiltration due to climate change. The air temperature has increased significantly in November (+3.4 °C) and December (+3.3 °C), with a +2.2 °C increase in the standard climate normal. The distribution of yearly precipitation has changed, with the annual amount decreasing from 686 to 652 mm. Precipitation increased the most in July and August (10.9 and 22.9 mm). In autumn, the amount of precipitation decreased by 7.9–31.1 mm. The number of rainy days did not change during the year, but the frequency of heavy precipitation increased significantly in August. The annual percolation increased by 14.2% over 2011–2020 compared to 1989–1998. Percolation increased by 19.0, 22.3, and 20.1% during the spring, autumn, and winter, respectively, and decreased by 35.0% in summer. The increase in annual percolation is mostly related to the increase in temperature during the cold season: November and December. During these months, the likelihood of early freeze formation, which interrupts gravitational water percolation in soil, is significantly reduced. In the spring, the increase in average air temperatures in March leads to faster melting of the winter snow in a shorter period, which significantly increases percolation processes. In Lithuania, higher percolation in autumn and winter, when part of the agricultural land is not covered by vegetation, may lead to higher leaching of chemical elements. [ABSTRACT FROM AUTHOR]

This paper presents the results of a trend analysis of three climate elements: precipitation, cloudiness and humidity. Almost the entire period of instrumental measurements (precipitation and humidity) and visual observations (cloudiness) are covered. In the observed 68-year period (1951-2018), the trend of annual and seasonal precipitation amounts is insignificant. Though, there is a significant decrease in the number of days with precipitation = 1 mm, which implies a movement towards more arid conditions. On the other hand, the number of days with extreme rainfall = 40 and 50 mm is increasing. In Podgorica, the annual statistics of days with snow cover decreases as well. There is also a decrease in the relative humidity and cloudiness, and with both elements the trend is insignificant only in the autumn season. The results of the trend calculation show that the number of gloomy days is more intensively reduced than the number of increasing bright days. In general, the results of the research show that the climate of Podgorica tends to be more arid with more extreme weather events. The climate variations happening in this city are, to small amount, caused by the urbanization process. Podgorica has the character of an urban heat island in a cooler environment, with an average annual intensity of about 0.7°C and the highest in winter (about 0.8°C). The most symptomatic indicator of urbanization is temperature, but anthropogenic heat production in the city (asphalt, constructions, increase of aerosols, etc.) also affects other climate elements. Compared to the non-urban environment, Podgorica has a higher annual rainfall of 100 mm and a lower humidity of 3%, while this difference is not noticeable in the overall cloudiness. [ABSTRACT FROM AUTHOR]

The main atmospheric climate parameters are important for the daily and seasonal variation of the parameters of the Comana Puddle aquariums. The anomalous variation of temperatures, precipitation and evaporation induces a fluctuation in the volume of water from the pond and the river Neajlov. Atmospheric temperature and precipitation directly affect winter phenomena and breakdown processes during the summer period, with significant effects on the agriculture, the most vulnerable domain on climate changes. In the hilly or hill area, the amount of rainfall decreases, thus influencing the water intake in these aquariums. The high warming time of the heat season leads to an increase in evaporation values, so that a water deficit is recorded in the hillside, hillside and plain areas, which also entails a loss in the volume of water in the lagoons. These seasonal fluctuations directly affect the limbic or aquatic fauna, but also the agriculture. In the cold season winter phenomena (ice bridge, ice on the shore, slopes, snowballs) and blocking water as snow, creates a deficiency in the water supply of lakes, ponds, puddles and swamps. This paper analysed the impact of climatic changes but also the possibilities of the recovery a part of the gloss of water, a gloss that existed years ago and which was greatly diminished after the work done downstream changed the hydrological balance of the area. This effect adds to the fact that climate change has made it possible for the volume of evaporation to be increased and sometimes to exceed the volume of precipitation. [ABSTRACT FROM AUTHOR]

Assessing climate change risk to municipal water supplies is often conducted by hydrologic modeling specific to local watersheds and infrastructure to ensure that outputs are compatible with existing planning frameworks and processes. This study leverages the modeling capacity of an operational National Weather Service River Forecast Center to explore the potential impacts of future climate-driven hydrologic changes on factors important to planning at the Salt Lake City Department of Public Utilities (SLC). Hydrologic modeling results for the study area align with prior research in showing that temperature changes alone will lead to earlier runoff and reduced runoff volume. The sensitivity of average annual flow to temperature varies significantly between watersheds, averaging -3.8% °F-1 and ranging from 21.8% to 26.5% flow reduction per degree Fahrenheit of warming. The largest flow reductions occur during the high water demand months of May-September. Precipitation drives hydrologic response more strongly than temperature, with each 1% precipitation change producing an average 1.9% runoff change of the same sign. This paper explores the consequences of climate change for the reliability of SLC's water supply system using scenarios that include hydrologic changes in average conditions, severe drought scenarios, and future water demand test cases. The most significant water management impacts will be earlier and reduced runoff volume, which threaten the system's ability to maintain adequate streamflow and storage to meet late-summer water demands. [ABSTRACT FROM AUTHOR]

In this paper, we have analyzed the time series of daily values for three meteorological elements, two continuous and a discontinuous one, i.e., the maximum and minimum air temperature and the precipitation. The analysis was done based on the observations from seven stations in Serbia from the period 1951-2010. The main aim of this paper was to quantify the complexity of the annual values for the mentioned time series and to calculate the rate of its change. For that purpose, we have used the sample entropy and the Kolmogorov complexity as the measures which can indicate the variability and irregularity of a given time series. Results obtained show that the maximum temperature has increasing trends in the given period which points out a warming, ranged in the interval 1-2 °C. The increasing temperature indicates the higher internal energy of the atmosphere, changing the weather patterns, manifested in the time series. The Kolmogorov complexity of the maximum temperature time series has statistically significant increasing trends, while the sample entropy has increasing but statistically insignificant trend. The trends of complexity measures for the minimum temperature depend on the location. Both complexity measures for the precipitation time series have decreasing trends. [ABSTRACT FROM AUTHOR]

Physical-natural, economic, social, and spatial factors constitute processes that, when associated, form and give meaning to the spatial complexity of the Metropolitan Region of Rio de Janeiro, configuring it as a susceptible and vulnerable space to the occurrence of climate exceptionalities. Thus, this paper aims to analyze the spatial and temporal variability of extreme precipitation events in the Metropolitan Region of Rio de Janeiro. Daily data regarding 48 rainfall stations were used: 40 stations in a series from 2008 to 2019 and 8 stations concerning the period between 1970 and 2019. The percentile technique was used to establish standard years (1, 10, 90, and 99 percentile) and to define the extremes (99th percentile). The R software was used to perform autocorrelation tests, to extract the RX1Day and RX5Day indices, and to perform the Mann-Kendall, Pettitt, and Sen's Slope tests. The influence of altitude, slope orientation, and sea level was verified on the spatial distribution of precipitation and extreme events. The years with the highest occurrence of extremes, as well as concentrated and persistent events of greater magnitude, are identified as rainy and extremely rainy, namely 1988 e 2009. 90% of extremes occur in the rainy season, especially during December, January, and March. However, April manifests extremes of a greater magnitude. Four stations with negative and two with positive trends were identified. [ABSTRACT FROM AUTHOR]

This paper presents the first study to identity, in historical records, regional changes in the mechanisms of extreme water available for runoff (W). We used a quality‐controlled Snowpack Telemetry data set (1979–2017) combined with the nonparametric regional Kendall test to examine changes in annual maximum W under four hydrometeorological conditions (melt only/rain‐on‐snow/all melt/all melt plus rainfall) over the mountainous regions of the western United States. Under a warming climate, our analyses indicated significant declining trends in annual maximum W at regional scale under all four conditions. The annual maximum of all melt plus rainfall decreased significantly by 15% in the southwestern United States, while the frequency of rain‐on‐snow events increased significantly by 32% in the northwestern United States. The annual maximum snowmelt only decreased significantly by 21% across the entire western United States. Our results confirmed that interaction between regional humidity and solar radiation with warming temperature helps drive these changes. Plain Language Summary: In the western United States, mountain snowmelt generates about 50% of the region's streamflow and plays a critical role in sustaining water resources. It is important to understand how snowpack are changing under warming, as risks related to these changes involve trillions of dollars. This paper presents the first study to identify, in historical records, large‐scale changes in the mechanisms of extreme water available for runoff (W). We used a regional trend analysis to examine spatiotemporal changes in rain‐on‐snow (ROS) frequency and the mechanisms of extreme W from 1979 to 2017, based on our newly developed quality‐controlled observed snow and precipitation data set. We found that, under a significant warming trend, annual maximum W from snowmelt only (not including ROS) has been decreasing by 21% across the western United States. The northwestern United States showed significant increasing trends in ROS frequency by 32%, but the rate of annual maximum ROS showed nonsignificant trends (i.e., more frequent but similar in magnitude). The annual maximum W from all conditions (melt plus rain) has been decreasing significantly by 15% in the southwestern United States. Decreasing trends in the mechanisms of extreme W may have significant ramifications for water management relative to flood risk and public safety. Key Points: Annual maximum snowmelt (not including rain‐on‐snow) decreased significantly by 21% averaged across the snowy regions of the western United StatesThe frequency of rain‐on‐snow events increased significantly by 32% averaged in the higher humidity snowy regions of the northwestern United StatesAnnual maximum water available for runoff (melt + rain) decreased significantly by 15% in the snowy regions of the southwestern United States [ABSTRACT FROM AUTHOR]

This study was driven by a need to clarify how variations in climate might affect intense rainfall and the potential for flooding. Sub-daily durations are of particular interest for urban applications. Worldwide, few such observation-based studies exist, which is mainly due to limitations in data. While there are still large discrepancies between precipitation data sets from observations and models, both show that there is a tendency for moist regions to become wetter and for dry regions to become drier. However, changes in extreme conditions may show the opposite sign to those in average conditions. Where changes in observed intense precipitation have been studied, this has typically been for daily durations or longer. The purpose of this two-part study is to examine daily and sub-daily rainfall extremes for evidence of non-stationarity. Here the problem was addressed by supplementing one long record (Part 1) by a set of shorter records for a 30-yr concurrent period (Part 2). Variations in frequency and magnitude of rainfall extremes across durations from 6 min to 72 h were assessed using data from sites in the south-east of Australia. For the analyses presented in this paper, a peaks-over-threshold approach was chosen since it allows investigating changes in frequency as well as magnitude. Non-parametric approaches were used to assess changes in frequency, magnitude, and quantile estimates as well as the statistical significance of changes for one station (Sydney Observatory Hill) for the period 1921 to 2005. Deviations from the long-term average vary with season, duration, and threshold. The effects of climate variations are most readily detected for the highest thresholds. Deviations from the long-term average tend to be larger for frequencies than for magnitudes, and changes in frequency and magnitude may have opposite signs. Investigations presented in this paper show that variations in frequency and magnitude of events at daily durations are a poor indicator of changes at sub-daily durations. Studies like the one presented here should be undertaken for other regions to allow the identification of regions with significant increase/decrease in intense rainfall, whether there are common features with regards to duration and season exhibiting most significant changes (which in turn could lead to establishing a theoretical framework), and assist in validation of projections of rainfall extremes. [ABSTRACT FROM AUTHOR]

Biogenic aerosols are relevant for the Earth system, climate, and public health on local, regional, and global scales. Up to now, however, little is known about the diversity and biogeography of airborne microorganisms. We present the first DNA-based analysis of airborne fungi on global scales, showing pronounced geographic patterns and boundaries. In particular we found that the ratio of species richness between Basidiomycota and Ascomycota is much higher in continental air than in marine air. This may be an important difference between the "blue ocean" and "green ocean" regimes in the formation of clouds and precipitation, for which fungal spores can act as nuclei. Our findings also suggest that air flow patterns and the global atmospheric circulation are important for the evolution of microbial ecology and for the understanding of global changes in biodiversity. [ABSTRACT FROM AUTHOR]

Crop yields are threatened by global climate change. Maize has high water requirements, and precipitation fluctuations can impact its yield. In this study, we used the Environmental Policy Integrated Climate (EPIC) model to simulate maize yields in eight northeastern U.S. states. We used precipitation fluctuations and the coefficient of variation (CV) of yield as indicators to construct a vulnerability curve for the CV of yield and precipitation fluctuations. We then evaluated the vulnerability of maize yields under precipitation fluctuations in the region. We obtained the following results: (1) the fitted vulnerability curves were classified into three categories (positive slope, negative slope, and insignificant fit), of which the first category accounted for about 92.7%, indicating that the CV of maize yield was positively correlated with precipitation fluctuations in most parts of the study area; and (2) the CV of maize yield under 11 precipitation fluctuation scenarios was mapped to express the CV at the spatial level, and the maize yield in Connecticut and Maryland proved to be the most sensitive to precipitation fluctuations. This study provided a theoretical and experimental basis for the prevention of maize yield risk under fluctuating precipitation conditions. [ABSTRACT FROM AUTHOR]

This paper shows that joint temperature-precipitation information over a global domain provides a more accurate estimate of aerosol forced responses in climate models than does any other combination of temperature, precipitation, or sea level pressure. This fact is demonstrated using a new quantity called potential detectability, which measures the extent to which a forced response can be detected in a model. In particular, this measure can be evaluated independently of observations and therefore permits efficient exploration of a large number of variable combinations before performing optimal fingerprinting on observations. This paper also shows that the response to anthropogenic aerosol forcing can be separated from that of other forcings using only spatial structure alone, leaving the time variation of the response to be inferred from data, thereby demonstrating that temporal information is not necessary for detection. The spatial structure of the forced response is derived by maximizing the signal-to-noise ratio. For single variables, the north-south hemispheric gradient and equator-to-pole latitudinal gradient are important spatial structures for detecting anthropogenic aerosols in some models but not all. Sea level pressure is not an independent detection variable because it is derived partly from surface temperature. In no case does sea level pressure significantly enhance potential detectability beyond that already possible using surface temperature. Including seasonal or land-sea contrast information does not significantly enhance detectability of anthropogenic aerosol responses relative to annual means over global domains. [ABSTRACT FROM AUTHOR]

The study of climate changes is most often based on the analysis of time series of temperature and precipitation in urban areas and the increase in the emission of gases having a greenhouse effect. On the other hand, the selection of representative and relevant stations and comprehensive analysis of climate indicators lead to better and more exact assessments on climate changes at the regional level. In order to connect climate changes with agricultural, biological, socio-economic, and tourism databases, the paper deals with the dynamic analysis of changes in thermal component expressed through the values of regional climate indices in four climatological stations with different geographical positions in Serbia. There are significant differences between the two time series data (1961-1990 and 1991-2013) on temperature and humidity, precipitation, insolation, and wind speed. However, after using the climatic indices as a tool for assessing climate changes, the results of the study suggest the relative influence of the thermal component on the change of climate indices, with a slight increase in the index of significance for human activities. Relying on the results of this alternative approach to the study of climate changes, the fact remains that the climate is not fixed but highly variable factor that should be taken into consideration in terms of monitoring, evaluation, and management of the area. [ABSTRACT FROM AUTHOR]

The objective of this paper is to identify better performing Coupled Model Intercomparison Project phase 3 (CMIP3) global climate models (GCMs) that reproduce grid-scale climatological statistics of observed precipitation and temperature for input to hydrologic simulation over global land regions. Current assessments are aimed mainly at examining the performance of GCMs from a climatology perspective and not from a hydrology standpoint. The performance of each GCM in reproducing the precipitation and temperature statistics was ranked and better performing GCMs identified for later analyses. Observed global land surface precipitation and temperature data were drawn from the Climatic Research Unit (CRU) 3.10 gridded data set and re-sampled to the resolution of each GCM for comparison. Observed and GCM-based estimates of mean and standard deviation of annual precipitation, mean annual temperature, mean monthly precipitation and temperature and Köppen-Geiger climate type were compared. The main metrics for assessing GCM performance were the Nash-Sutcliffe efficiency (NSE) index and root mean square error (RMSE) between modelled and observed long-term statistics. This information combined with a literature review of the performance of the CMIP3 models identified the following better performing GCMs from a hydrologic perspective: HadCM3 (Hadley Centre for Climate Prediction and Research), MIROCm (Model for Interdisciplinary Research on Climate) (Center for Climate System Research (The University of Tokyo), National Institute for Environmental Studies, and Frontier Research Center for Global Change), MIUB (Meteorological Institute of the University of Bonn, Meteorological Research Institute of KMA, and Model and Data group), MPI (Max Planck Institute for Meteorology) and MRI (Japan Meteorological Research Institute). The future response of these GCMs was found to be representative of the 44 GCM ensemble members which confirms that the selected GCMs are reasonably representative of the range of future GCM projections. [ABSTRACT FROM AUTHOR]

Drought (similarly as flooding) is considerably the gravest agrometeorological extreme connected with climate change and bringing the highest losses in an agricultural production. The objective of this paper is to study the spatial and temporal variability of the Aridity Index (AI) in the Czech Republic, per decade, during the 55-year period (1961 - 2015). AI is a climatic index, which is important for recording of the drought phenomenon evolution. The climatic data used, include monthly precipitation totals and air temperature from 120 meteorological stations operated by the Czech Hydrometeorological Institute. The potential evapotranspiration was calculated based on the modified algorithm Penman-Monteith. The data processing was done by the statistical tools of Microsoft Excel and the Geographical Information Systems (Clidata GIS, ArcGIS 10). The results of the analysis showed, that during the decade 1961 - 1970, almost the whole area of the Czech Republic is classified as "wet" with AI values ranging above 0.60, but over the next years (1971 - 2015), areas of the south Moravia (e.g. Dyjsko-svratecký ravine, Valticko-lednický area, surroundings of Brno city), and also Prague city and Poohří river basin shifted gradually to "sub-humid" climate zone with AI < = 0.60. Especially, during the pre-last decade of the study period 1991 - 2000. [ABSTRACT FROM AUTHOR]

Future projections of precipitation at regional scales are vital to inform climate change adaptation activities. Therefore, is it important to quantify projected changes and associated uncertainty, and understand model processes responsible. This paper addresses these challenges for southern Africa and the adjacent Indian Ocean focusing on the local wet season. Precipitation projections for the end of the twenty-first century indicate a pronounced dipole pattern in the CMIP5 multimodel mean. The dipole indicates future wetting (drying) to the north (south) of the climatological axis of maximum rainfall, implying a northward shift of the ITCZ and south Indian Ocean convergence zone that is not consistent with a simple "wet get wetter" pattern. This pattern is most pronounced in early austral summer, suggesting a later and shorter wet season over much of southern Africa. Using a decomposition method we determine physical mechanisms underlying this dipole pattern of projected change, and the associated intermodel uncertainty. The projected dipole pattern is largely associated with the dynamical component of change indicative of shifts in the location of convection. Over the Indian Ocean, this apparent northward shift in the ITCZ may reflect the response to changes in the north-south SST gradient over the Indian Ocean, consistent with a "warmest get wetter" mechanism. Over land subtropical drying is relatively robust, particularly in the early wet season. This has contributions from dynamical shifts in the location of convection, which may be related to regional SST structures in the southern Indian Ocean, and the thermodynamic decline in relative humidity. Implications for understanding and potentially constraining uncertainty in projections are discussed. [ABSTRACT FROM AUTHOR]

Reanalysis data show an increasing trend in Arctic precipitation over the 20th century, but changes are not homogenous across seasons or space. The observed hydroclimate changes are expected to continue and possibly accelerate in the coming century, not only affecting pan-Arctic natural ecosystems and human activities, but also lower latitudes through the atmospheric and ocean circulations. However, a lack of spatiotemporal observational data makes reliable quantification of Arctic hydroclimate change difficult, especially in a long-term context. To understand Arctic hydroclimate and its variability prior to the instrumental record, climate proxy records are needed. The purpose of this review is to summarise the current understanding of Arctic hydroclimate during the past 2000 years. First, the paper reviews the main natural archives and proxies used to infer past hydroclimate variations in this remote region and outlines the difficulty of disentangling the moisture from the temperature signal in these records. Second, a comparison of two sets of hydroclimate records covering the Common Era from two data-rich regions, North America and Fennoscan-dia, reveals inter- and intra-regional differences. Third, building on earlier work, this paper shows the potential for providing a high-resolution hydroclimate reconstruction for the Arctic and a comparison with last-millennium simulations from fully coupled climate models. In general, hydroclimate proxies and simulations indicate that the Medieval Climate Anomaly tends to have been wetter than the Little Ice Age (LIA), but there are large regional differences. However, the regional coverage of the proxy data is inadequate, with distinct data gaps in most of Eurasia and parts of North America, making robust assessments for the whole Arctic impossible at present. To fully assess pan-Arctic hydroclimate variability for the last 2 millennia, additional proxy records are required. [ABSTRACT FROM AUTHOR]