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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.

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]

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]

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]

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]

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]

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]

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 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]

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]

The seasonal variability of surface layer salinity (SLS), evaporation (E), precipitation (P ) and E -P over the global ocean is examined using in situ salinity data and the National Center for Environmental Prediction's Climate System Forecast Reanalysis. Sea- 5 sonal amplitudes and phases are calculated using harmonic analysis and presented in all areas of the open ocean between 60° S and 60° N. Areas with large amplitude SLS seasonal variations include: the intertropical convergence zone in the Atlantic, Pacific and Indian Oceans; western marginal seas of the Pacific; and the Arabian Sea. The median value in areas that have statistically significant seasonal cycles of SLS 10 is 0.19. Between about 60° S and 60° N, 37% of the ocean surface has a significant seasonal cycle of SLS and 75% a seasonal cycle of E -P . Phases of SLS have a bimodal distribution, with most areas of the ocean peaking in SLS in either March/April or September/October. The same calculation is done with surface freshwater flux using a mixed-layer depth 15 climatology. With the exception of an area near the western boundaries of the North Atlantic and North Pacific, seasonal variability is dominated by precipitation. Surface freshwater fluxes also have a bimodal distribution, with peaks in January and July, 1-2 months before the peaks of SLS. The amplitudes and phases of SLS and surface fluxes compare well in a qualitative 20 sense, suggesting that much of the variability in SLS is due to E -P forcing. However, the amplitudes of SLS are somewhat larger than would be expected and the peak of SLS comes typically about one month earlier than expected. The differences of the amplitudes of the two quantities is largest in such areas as the Amazon River plume, the Arabian Sea, the ITCZ and the eastern equatorial Pacific and Atlantic, indicating 25 that other processes such as ocean mixing and lateral transport must be important, especially in the tropics. [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 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]

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]

Purpose: The purpose of this paper is to examine the role of high intensity precipitation events in increasing the vulnerability to floods in Mediterranean Spain. Precipitation intensity in this area appears to have augmented in the last two decades in association with warming trends of the Mediterranean Sea. At the same time, intense urbanization processes, occupying and transforming flood prone land, have produced an important increase in exposure. The main objective is to assess whether higher intensity precipitation and changing patterns in exposure aggravate vulnerability to floods. Design/methodology/approach: In this paper, vulnerability is understood as the result of the interrelationships between exposure, sensitivity, impacts and adaptive capacity. Consequently, methods used involved the compilation and analysis of published and unpublished precipitation data, population and land use data, data on insurance claims, and media sources related to those variables. Findings: Changes toward episodes of more intense precipitation in the expanding urban areas of Mediterranean Spain increase exposure but not necessarily vulnerability, at least in terms of human deaths. However, adaptative capacity needs to be formulated. Actions that attempt to absorb and eventually reuse flood flows (as the flood park in Alicante) appear to be more effective than traditional hydraulic solutions (as in Majorca). Originality/value: The paper provides a systematic and coherent approach to vulnerability analysis taking into account the changing dynamics of its components. Especially, it signals the limits of current adaptive approaches to flooding and advocates for changes toward a more circular and less linear approach to urban drainage. [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]

This paper presents a precipitation reconstruction that is based on the continuous observations by Louis Morin in Paris from 1665–1713. Morin usually recorded precipitation intensity and duration, when it snowed/rained, three times each day (sometimes up to six times). The consistency of his observations can be calculated from his other measurements and observations (e.g. temperature, cloud cover), where at least one entry of his different measurements and observations for 98.7 % of all days is noted. To 5 convert these observations to common units, we calibrated them with a multiplicative interacting model using Philippe and Gabriele-Philippe de la Hire's instrumental measurements from Paris. The two series of measurements by de la Hire (father and son) and observations by Morin overlap from 1688–1713. To test the quality of the reconstruction, we analyzed it with the de la Hire's measurements, proxy data, an internal analysis of Morin's measurements of different climate variables, and modern data. Thus, we assess the reliability of the precipitation reconstructions based on Morin's data as follows. We have moderate confidence regarding the exact quantities of daily, seasonal, and annual precipitation totals. We have low confidence regarding exceptionally high precipitation amounts, but we have high confidence in the indices of an impact analysis (i.e., dry days, wet days, consecutive dry days, consecutive wet days), in monthly frequencies of rainfall, and in interannual, interseasonal, and interdecadal variability. Rainy seasons with precipitation totals greater than 250 mm occurred in MAM 1682, JJA 1682, SON 1687, JJA 1697 and JJA 1703. Furthermore, compared to other DJF seasons, the winter of 1666/67 stands out with a precipitation total of 248 mm. Dry seasons with precipitation totals less than 60 mm occurred in SON 1669, DJF 1690/91 and DJF 1693/94. An impact analysis shows no abnormalities regarding consecutive dry days or wet days in MAM. In JJA a longer dry period of 31 days appeared in 1686 and a dry period of 69 days appeared in DJF 1671/72. [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]

Any hydro-meteorology variable includes different components, in general, such as periodicity, trend, possibly jump, and uncertain stochastic parts. Among these, the trend analysis gained importance in the last three decades due to global warming and climate change effects. The literature is full of monotonic trend applications by taking into consideration trend analysis methodologies such as Mann–Kendall trend identification, Sen trend slope calculation, and Şen innovative trend analysis (ITA). It is more important in practical studies to deal with less than one-year durations to assess the possible trend pieces for better practical uses such as agricultural productivity purposes. In this paper, a new concept is applied, known as the innovative polygon trend analysis (IPTA), to assess the trend component transitions between two successive months. The application of the methodology is presented for the coastal region of northeast Algerian precipitation records. The emanated results from this study provided information that El Taref station has the most unstable precipitation behavior among all the meteorology stations in the study area, moving from a month to another rather very unsystematically; whereas other meteorology stations have systematic movement from a month to the subsequent one. [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]

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 an investigation of the role of climatic variability on interannual groundwater and streamflow variability in the southeast United States. For this purpose, streamflow and associated groundwater levels are analyzed for 20 basins that are minimally affected by reservoirs and groundwater pumping. Using the spatially averaged monthly precipitation time series obtained from the Precipitation-elevation Regressions on Independent Slopes Model (PRISM), this paper identifies the recharge and discharge periods that influence the groundwater levels during the winter [January, February, March (JFM)] and summer [July, August, September (JAS)] seasons. Recharge-discharge dependency analyses indicate that precipitation during the previous 3 months influences the groundwater level in a given month. Streamflow in any given month depends on the groundwater level during the previous 3 months. Principal component analysis (PCA) on the precipitation, temperature, streamflow, and groundwater data indicates that groundwater levels and streamflow are the two dominant variables influencing the basin hydroclimatology. Furthermore, relating the percentage variance explained from the PCA to baseflow index (BFI) clearly shows that basins with high BFI have higher eigenvalues, indicating that groundwater is a spatial integrator of hydroclimatic processes. Relating the groundwater levels with El Niño/ Southern Oscillation (ENSO) index, NINO3.4, shows that interannual variability in JFM groundwater levels could be partially explained by the ENSO conditions, but the relationship between JAS groundwater levels and JAS NINO3.4 is not statistically significant. Precipitation forecasts from the ECHAM4.5 general circulation model indicate that it is possible to quantify groundwater availability during the winter season on the basis of the forecasted precipitation and ENSO conditions. [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]

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]

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]

Climate change is likely to increase the future risk of weather-related damage to buildings worldwide. This challenge is faced by society in general, but the insurance industry is particularly important in the management of the anticipated increase in future risk. In addition to adjusting premiums appropriately and gradually, they can play an important role in prevention. It is crucial to know which areas are vulnerable and to what extent. In this paper, a spatial regression model for linking weather-related insurance losses for residential buildings to meteorological and hydrological covariates is coupled with three plausible scenarios for the future climate in order to project the future number of weather-related residential building insurance losses in Norway. The model is trained on observed daily insurance loss and weather data at the municipality level. Our results indicate a dramatic increase in the projected future weather-related insurance risk in many parts of Norway. The procedure can be extended and applied to other areas globally. [ABSTRACT FROM AUTHOR]