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Lignin is a by-product of the pulp and paper industry that can be precipitated by acidification from black liquor as a potential feedstock for valuable green materials. Precipitation and quantification of lignin from softwood black liquors have been documented and commercialized with well-established methods; however, applying those methods to the precipitation of lignin from hardwood black liquors has produced low lignin yields. A need to understand the main differences between hardwood and softwood lignin precipitation prompted the current investigation. Multiple black liquor samples from sweetgum and pine pulping were obtained at different times of standard kraft cooks. Two lignin fractions were precipitated from each of these black liquors, one at pH 9.5 and one at pH 2.5. Detailed lignin and carbohydrate material balances were performed around each of the sample sets, starting with the wood and ending with precipitated lignin fractions. For all conditions tested, the amount and purity of pine lignin precipitated were superior to sweetgum lignin. The maximum recovery for sweetgum lignin was 69.7%, while for pine lignin, it was 90.9%. [ABSTRACT FROM AUTHOR]

Estimating precipitation is of critical importance to climate systems and decision-making processes. This paper presents Espresso, a deep learning model designed for estimating precipitation from satellite observations on a global scale. Conventional methods, like ground-based radars, are limited in terms of spatial coverage. Satellite observations, on the other hand, allow global coverage. Combined with deep learning methods, these observations offer the opportunity to address the challenge of estimating precipitation on a global scale. This research paper presents the development of a deep learning model using geostationary satellite data as input and generating instantaneous rainfall rates, calibrated using data from the Global Precipitation Measurement Core Observatory (GPMCO). The performance impact of various input data configurations on Espresso was investigated. These configurations include a sequence of four images from geostationary satellites and the optimal selection of channels. Additional descriptive features were explored to enhance the model's robustness for global applications. When evaluated against the GPMCO test set, Espresso demonstrated highly accurate precipitation estimation, especially within equatorial regions. A comparison against six other operational products using multiple metrics indicated its competitive performance. The model's superior storm localization and intensity estimation were further confirmed through visual comparisons in case studies. Espresso has been incorporated as an operational product at Météo-France, delivering high-quality, real-time global precipitation estimates every 30 min. [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]

Karst spring water dynamic characteristics and its response to atmospheric precipitation are of great significance for water resources utilization under the background of climate change. This paper selects Longzici spring area, North China, as the study area. Based on a long series of spring water flow and precipitation data, the dynamic characteristics of spring flow were analyzed and the numerical simulation of the groundwater flow model was established. The results show that the groundwater kept the sustained decline over the past decades which is in a negative equilibrium state, with a storage variable of − 2.26 million m3/year. The sensitivity of spring flow to precipitation under different precipitation scenarios shows that the water level changes in the recharge and drainage areas are similar about (3–5 cm) and slightly larger than that in the runoff area(1.5 cm) when minimum rainfall (287.24 mm) happens. When the precipitation is at its maximum (867.66 mm), the water level change in the runoff area can reach 95 cm which is much larger than those in the recharge and discharge areas. The results indicate that Longzici karst spring has a relatively good regulation water resource capacity and the runoff area is more sensitive which plays an important role in response to climate change. [ABSTRACT FROM AUTHOR]

Prediction of drought, a dangerous hydrometeorological phenomenon, is based on meteorological data (temperature, precipitation, air pressure, dew point, evaporation), combined into a single formula – an index describing the qualitative state of aridity depending on the quantitative value of the index in a given climatic region. Due to the lack of a universal definition of drought, different aridity indices provide an effective assessment of aridity in different climatic regions of the world in different ways. In order to adapt methods for assessing aridity in a specific climatic region accounting for both the physical mechanism of the occurrence and evolution of drought and the influence of geographical and climatic features of the region under study, it is necessary to investigate the informativeness of a particular aridity index in relation to that region. This paper provides a solution for prediction of drought for the Central Asian region. [ABSTRACT FROM AUTHOR]

It is important to investigate the hydrological consequences of current climate change. Hydrological responses to climate warming and wetter conditions include changes in discharge (frequency, amplitude, and volume). This paper describes current climate change and its impact on hydrological flow within the Horyn River basin. Daily air temperature and precipitation data obtained from the 17 meteorological stations located in and nearby the Horyn River basin, in combination with hydrological data (such as daily water discharges obtained from 9 water gauges), were used for the analysis of climate variability and its hydrological consequences. Analyses of meteorological variables and water discharges are crucial for the assessment of long-term changes in the river regime. Thiessen polygons were used to determine the area of influence of assigned specific meteorological stations, which affect the river's catchments within the Horyn River basin. As a result of the trend analysis, it was observed that discharge within the Horyn River basin decreased over time. These results were congruent with the trends of precipitation data and air temperature data of the stations determined by the Thiessen polygons and basin boundaries. To understand current changes in the daily flow in the basin, changes in air temperature and precipitation for the period 1991-2020 were compared with the period of the climatic norm (1961-1990). A similar analysis was done for daily water discharges. Increasing air temperature and decreasing precipitation in the current period led to a significant decrease in discharges in the Horyn River basin, especially during the spring flood period. [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]

Continuously raising awareness of the issue of climate change helps to better understand it, but there is very little or no implementation of activities to mitigate the effects in practice. Therefore, it is important to collect data, perform analyses and studies in order to improve the existing situation. The paper provides an overview of the current condition caused by climate change with a focus on water resources in Bosnia and Herzegovina, possible consequences in the future and measures recommended to be applied as a means to minimize the negative effects. [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]

The present paper presents the influence of the main factors that generate the maximum flow in the upper basin of the Crisul Negru river. Starting from the three types of flow in the basin (maximum, average and minimum) and selecting among them the most representative from the hydrological point of view - the maximum characteristic leak, data from meteorological and hydrological observations have been used since the 1950s. Characteristic and important, for this type of flow in the basin, are the data collected from the main gauging stations in the catchment area of the upper reception basin of Crişul Negru. Within the paper are presented and analyzed the main elements of the maximum leak as well as the meteorological data recorded in the receiving basin taken into consideration. The characteristic elements of the flow in the riverbeds - flows, levels, hydrological parameters, as well as the determining elements in the formation of the flow - air temperatures and precipitation are taken into account. On the basis of the data processed, analyzed and graphically represented in various forms, the close connection between all these generating elements was emphasized and in some cases they maintain the maximum flow type in the reception area of the upper Crisul Negru basin. [ABSTRACT FROM AUTHOR]

Gridded data products, for example interpolated daily measurements of precipitation from weather stations, are commonly used as a convenient substitute for direct observations because these products provide a spatially and temporally continuous and complete source of data. However, when the goal is to characterize climatological features of extreme precipitation over a spatial domain (e.g., a map of return values) at the native spatial scales of these phenomena, then gridded products may lead to incorrect conclusions because daily precipitation is a fractal field and hence any smoothing technique will dampen local extremes. To address this issue, we create a new "probabilistic" gridded product specifically designed to characterize the climatological properties of extreme precipitation by applying spatial statistical analysis to daily measurements of precipitation from the Global Historical Climatology Network over the contiguous United States. The essence of our method is to first estimate the climatology of extreme precipitation based on station data and then use a data-driven statistical approach to interpolate these estimates to a fine grid. We argue that our method yields an improved characterization of the climatology within a grid cell because the probabilistic behavior of extreme precipitation is much better behaved (i.e., smoother) than daily weather. Furthermore, the spatial smoothing innate to our approach significantly increases the signal-to-noise ratio in the estimated extreme statistics relative to an analysis without smoothing. Finally, by deriving a data-driven approach for translating extreme statistics to a spatially complete grid, the methodology outlined in this paper resolves the issue of how to properly compare station data with output from earth system models. We conclude the paper by comparing our probabilistic gridded product with a standard extreme value analysis of the Livneh gridded daily precipitation product. Our new data product is freely available on the Harvard Dataverse (https://bit.ly/2CXdnuj). [ABSTRACT FROM AUTHOR]

Quantitatively evaluation of satellite precipitation and potential evapotranspiration products with the high resolution, wide coverage and dynamic continuity is an important foundation for drought monitoring over mainland China. This paper examined the accuracy of products and the utility of drought monitoring using the newly released long-term (more than 30 years) satellite precipitation products (climate hazards group infrared precipitation with station, CHIRPS) data version 2.0 and potential evapotranspiration products (global land-surface evaporation: the Amsterdam methodology, GLEAM) dataset. We selected standardized precipitation evapotranspiration index (SPEI) and six statistical and classification measures indexes to evaluate accuracy and the utility of CHIRPS and GLEAM-Ep (potential evapotranspiration derived from GLEAM), with China Gauge-based Precipitation Daily Analysis dataset (CGDPA) and potential evapotranspiration calculated by Penman-Monteith (PM-Ep) as evaluation reference data sets. The results showed that CHIRPS and GLEAM-Ep performed well in eastern and southwest of China. However, their performance in western China was uncertain due to the sparsity of meteorological stations. SPEIs (SPEI value calculated by the CHIRPS and GLEAM-Ep) had a good performance on drought monitoring in eastern and southwestern China. Values of correlation coefficient (CC) between SPEIs and SPEIm (SPEI value calculated by the CGDPA and PM-Ep) were more than 0.6 in southeastern China, southwestern China, the middle and lower reaches of the Yangtze River region and northern China, especially in relatively humid areas, which the correlation coefficient values were more than 0.7 and the root mean-squared error (RMSE) values were less than 0.8. In order to further evaluate the performance of SPEIs in drought monitoring at spatial and temporal scales, the SPEIs3 (SPEIs at three-month scale) and SPEIm3 (SPEIm at three-month scale) in southeastern China, southwestern China, the middle and lower reaches of the Yangtze River region and northern China were compared. SPEIs3 had a better simulation effect on the evolution process of the ratio of drought area in those regions during1981-2016. And the success ratio of simulating drought duration was about 0.93, 0.57, 0.71 and 0.81, respectively. Moreover, SPEIs3 displayed a high accuracy over the four regions in capturing drought, which was the spatial distribution of typical drought events on specific month. In conclusion, SPEI based on long-term CHIRPS and GLEAM-Ep could be applied to monitor and evaluate drought in eastern and southwestern China. This paper can provide reliable reference for monitoring and warning of drought events and water resources management in those regions. [ABSTRACT FROM AUTHOR]

This paper presents adjustment routines for Geonor totalizing precipitation gauge data collected from the headwaters of the Oldman River, within the southwestern Alberta Canadian Rockies. The gauges are situated at mountain valley and alpine ridge locations with varying degrees of canopy cover. These data are prone to sensor noise and environment-induced measurement errors requiring an ordered set of quality control (QC) corrections using nearby weather station data. Sensor noise at valley sites with single-vibrating wire gauges accounted for the removal of 5% to 8% (49-76 mm) of annual precipitation. This was compensated for by an increase of 6% to 8% (50-76 mm) from under-catch. A three-wire ridge gauge did not experience significant sensor noise; however, the under-catch of snow resulted in 42% to 52% (784-1342 mm) increased precipitation. When all QC corrections were applied, the annual cumulative precipitation at the ridge demonstrated increases of 39% to 49% (731-1269 mm), while the valley gauge adjustments were 􀀀4% to 1% (􀀀39 mm to 13 mm). Public sector totalizing precipitation gauge records often undergo minimal QC. Care must be exercised to check the corrections applied to such records when used to estimate watershed water balance or precipitation orographic enhancement. Systematic errors at open high-elevation sites may exceed nearby valley or forest sites. [ABSTRACT FROM AUTHOR]

Highlights • Synthesis of 2D REEs (i.e., Nd, Pr and Dy) oxide nano-sheets from end-of-life Nd-Fe-B permanent magnets. • 2D REEs (i.e., Nd, Pr and Dy) oxide in dimension of ∼1 μm × 0.5 μm × 17 nm made from nano-particles. • Synthesis of crystallized RE 2 (i.e., Nd, Pr and Dy) [C 2 O 4 ] 3.10H 2 O nano-sheets from Nd-Fe-B magnets. Abstract With rising global demand for rare earth elements (REEs) in a range of emerging clean energy technologies such as hybrid electric vehicles, and the uncertainty in their supply, REEs are now under severe risk. The development of new technologies for the recovery of REEs from waste and also replacing the conventional resources with the alternative renewable sources is urgently needed. Currently, Nd-Fe-B magnets are known as one of the most extensively used types of REE magnets which can be used as a potentially valuable and rich source of REEs (i.e., Nd, Pr and Dy). In the present paper, using REEs (i.e., Nd, Pr and Dy) recovered from the end-of-life Nd-Fe-B magnets, we applied homogeneous precipitation technique at low temperature and synthesised REEs (i.e., Nd, Pr and Dy) hydrate oxalate which was then utilised as a precursor for the synthesis of REO nano-sheets. FE-SEM and TEM images showed that the synthesised REO nano-sheets were in the dimension of ∼1μm×0.5μm×17 nm made from nano-particles. From X-ray diffraction spectrum, several strong peaks assigning to the cubic phase of Nd 2 O 3 and small peaks corresponding to cubic phases of NdPrO 3 and Pr 2 O 3 were detected. This paper confirms the feasibility of transforming waste materials such as end-of-life Nd-Fe-B magnets into valuable nano-structured products through a simple pathway. [ABSTRACT FROM AUTHOR]

This paper used data on land use, normalized difference vegetation index, digital elevation model, temperature and precipitation, and urban distribution to analyse the impacts of climate change, urban expansion and the Grain for Green project implementation on land use and land cover change in the Loess Plateau between 1980 and 2015 based on a single factor and comprehensive factor analysis. The aim of this paper is to explore the spatial expression of human activities under the influence of urban expansion, climate change, and the implementation of the Grain for Green project. The results indicated that climate change dominated among the influencing factors of land use and land cover change in the Loess Plateau, accounting for 93.65% of the total, with a surface-like distribution. It was followed by urban expansion, accounting for 5.46% of the total, with a point-like distribution. The impact of the Grain for Green project implementation accounted for 0.64%, with a patchy distribution. However, due to the low resolution, the quantitative assessment results regarding the role of the Grain for Green project implementation was lower, while for climate change and urban expansion, results were higher. [ABSTRACT FROM AUTHOR]

The major task of multi-purpose reservoir „Modrac" operation is to decide how much water should be released now and how much should be retained for future use given some available and/or forecasted information at the beginning of the current time period. In practice, reservoir operators usually follow rule curves, which stipulate the actions that should be taken conditioned on the current state of the system. Through construction of the dam Modrac in 1964, the reservoir of the same name was formed. Its primary objectives were the provision of technological water for industries in the Tuzla region and mitigation of downstream floods as well as recreation and other purposes. The multi-purpose reservoir Modrac is currently a drinking water source for the municipality Tuzla. In order to better manage of the multi-purpose reservoir „Modrac", certain analyzes are presented in this paper. This paper presents an analysis of annual precipitation, mean annual inflows in the catchment area of the multi-purpose reservoir „Modrac" for the period 1967 - 2016. In this paper there are presented statistical datas on the maximum amount of precipitation for the dry season period (May to October) for different return periods, for different distribution curves, as well as the maximum amount of precipitation for the wet season (November to April) for different return periods for different curves distribution. This paper provides information on the movement of precipitation changes in the catchment area of multi-purpose reservoir "Modrac" for the period from 1967. - 2016. [ABSTRACT FROM AUTHOR]

Changing climate and precipitation patterns make the estimation of precipitation, which exhibits two-dimensional and sometimes chaotic behavior, more challenging. In recent decades, numerous data-driven methods have been developed and applied to estimate precipitation; however, these methods suffer from the use of one-dimensional approaches, lack generality, require the use of neighboring stations and have low sensitivity. This paper aims to implement the first generally applicable, highly sensitive two-dimensional data-driven model of precipitation. This model, named frequency based imputation (FBI), relies on non-continuous monthly precipitation time series data. It requires no determination of input parameters and no data preprocessing, and it provides multiple estimations (from the most to the least probable) of each missing data unit utilizing the series itself. A total of 34,330 monthly total precipitation observations from 70 stations in 21 basins within Turkey were used to assess the success of the method by removing and estimating observation series in annual increments. Comparisons with the expectation maximization and multiple linear regression models illustrate that the FBI method is superior in its estimation of monthly precipitation. This paper also provides a link to the software code for the FBI method. [ABSTRACT FROM AUTHOR]

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The Brazilian savannah-like Cerrado is classified as a fire-dependent biome. Human activities have altered the fire regimes in the region, and as a result, not all fires have ecological benefits. The indigenous lands (ILs) of the Brazilian Cerrado have registered the recurrence of forest fires. Thus, the diagnosis of these events is fundamental to understanding the burning regimes and their consequences. The main objective of this paper is to evaluate the fire regimes in Cerrado's indigenous lands from 2008 to 2017. We used the Landsat time series, at 30 m spatial resolution, available in the Google Earth Engine platform to delineate the burned areas. We used precipitation data from a meteorological station to define the rainy season (RS), early dry season (EDS), middle dry season (MDS), and late dry season (LDS) periods. During 2008-2017, our results show that the total burned area in the indigenous lands and surrounding area was 2,289,562 hectares, distributed in 14,653 scars. Most fires took place between June and November, and the annual burned area was quite different in the years studied. It was also possible to identify areas with high fire recurrence. The fire regime patterns described here are the first step towards understanding the fire regimes in the region and establishing directions to improve management strategies and guide public policies. [ABSTRACT FROM AUTHOR]

This paper estimates rainfall totals at 17 Greenland meteorological stations, subjecting data from in situ precipitation gauge measurements to seven different precipitation phase schemes to separate rainfall and snowfall amounts. To correct the resulting snow/rain fractions for undercatch, we subsequently use a dynamic correction model (DCM) for automatic weather stations (AWS, Pluvio gauges) and a regression analysis correction method for staffed stations (Hellmann gauges). With observations ranging from 5% to 57% for cumulative totals, rainfall accounts for a considerable fraction of total annual precipitation over Greenland’s coastal regions, with the highest rain fraction in the south (Narsarsuaq). Monthly precipitation and rainfall totals are used to evaluate the regional climate model RACMO2.3. The model realistically captures monthly rainfall and total precipitation (R = 0.3–0.9), with generally higher correlations for rainfall for which the undercatch correction factors (1.02–1.40) are smaller than those for snowfall (1.27–2.80), and hence the observations are more robust. With a horizontal resolution of 5.5 km and simulation period from 1958 to the present, RACMO2.3 therefore is a useful tool to study spatial and temporal variability of rainfall in Greenland, although further statistical downscaling may be required to resolve the steep rainfall gradients. [ABSTRACT FROM AUTHOR]

This paper contributes to the predictive understanding of satellite precipitation estimation errors over complex terrain, which is fundamental to the development of error models for improving hydrological applications. This paper focuses on the Trentino-Alto Adige region of the eastern Italian Alps. Rainfall observations over a 10-year period (2000–2009) from a dense rain gauge network in the region are used as reference precipitation. A number of satellite precipitation error properties (probability of detection, false alarm rates, missed events, spatial correlation of the error, and hit biases) are investigated in terms of seasonality, satellite algorithm, rainfall intensity, gauge density, and temporal resolution dependencies. These error parameters are typically used in error models (e.g., SREM2D) and provide the basis for enhancing error scheme development. Three widely used satellite-based precipitation products are employed: 1) the Climate Prediction Center morphing product; 2) the precipitation estimation from remotely sensed imagery using artificial neural networks; and 3) the Tropical Rainfall Measuring Mission multisatellite precipitation analysis 3B42 near-real-time product. The three products show similar performances, with larger errors during the warm season, characterized by convective storms, and less variability in the cold season, characterized by more organized stratiform systems. Lower biases are depicted at the daily scale with respect to the 3-hourly resolution. The SREM2D error model has the ability to correct the satellite precipitation products, even though attention is needed for potential systematic errors when applying the calibrated model to independent periods or regions. [ABSTRACT FROM PUBLISHER]

Compared to traditional single-polarization radar, dual-polarization radar has a number of advantages for quantitative precipitation estimation because more information about the drop size distribution and hydrometeor type can be gleaned. In this paper, an improved dual-polarization rainfall methodology is proposed, which is driven by a region-based hydrometeor classification mechanism. The objective of this study is to incorporate the spatial coherence and self-aggregation of dual-polarization observables in hydrometeor classification and to produce robust rainfall estimates for operational applications. The S-band dual-polarization data collected from the NASA Polarimetric (NPOL) radar during the GPM Iowa Flood Studies (IFloodS) ground validation field campaign are used to demonstrate and evaluate the proposed rainfall algorithm. Results show that the improved rainfall method provides better performance than a few single- and dual-polarization algorithms in previous studies. This paper also investigates the impact of radar beam broadening on various rainfall algorithms. It is found that the radar-based rainfall products are less correlated with ground disdrometer measurements as the distance from the radar increases. [ABSTRACT FROM AUTHOR]

Copyright of Ochrona Srodowiska i Zasobów Naturalnych is the property of Sciendo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ochrona Srodowiska i Zasobów Naturalnych is the property of Sciendo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of this paper is to elucidate a potential use of the large samples of seasonal means that hindcasts provide for investigating different aspects of climate variability. This use of hindcasts complements their traditional uses in bias correction, real-time forecast calibration, and prediction skill assessment. For seasonal hindcast data from NCEP CFSv2 we show that a sample size 5208 for each target season is achievable. To demonstrate the utility of the proposed concept, we use this large sample dataset to illustrate how it could be used in documenting spatial variability in various moments of seasonal mean precipitation PDF over the US, and further, quantify nuances in the variations in precipitation PDF at different geographical locations with the amplitude of ENSO SSTs. It is our hope that analysis presented in this paper will accelerate utilization of seasonal hindcast datasets in furthering our understanding of different aspects of climate variability. With the advantage of the large sample size, we demonstrated that the precipitation PDF at the each grid of the CONUS can be represented by gamma distribution for a more concise and effective way to summarize precipitation variability. The availability of the large sample dataset also allowed us to analyze the statistical characteristic of the precipitation responses to the different amplitudes of ENSO SSTs. The results show that for strong warm events, enhancement in precipitation has larger amplitude than decrease in precipitation for cold events in the regions of Southern California and southeastern US. The variation of the precipitation signal over the other sub-regions including the southwestern US, mid-northwest, and mid-east shows more linear relationship with the ENSO SSTs. In response to anomalous ENSO SSTs, although the PDF of December-January-February seasonal mean precipitation anomaly is shifted from its climatological PDF, there is still a large overlap between precipitation PDFs for ENSO and its climatological counterpart. This uncertainty in seasonal mean outcomes of precipitation, therefore, limits the seasonal prediction skill. [ABSTRACT FROM AUTHOR]

The use of radar measurements for the space time estimation of precipitation has for many decades been a central topic in hydro-meteorology. In this paper we are interested specifically in daily and sub-daily extreme values of precipitation at gauged or ungauged locations which are important for design. The purpose of the paper is to develop a methodology to combine daily precipitation observations and radar measurements to estimate sub-daily extremes at point locations. Radar data corrected using precipitation-reflectivity relationships lead to biased estimations of extremes. Different possibilities of correcting systematic errors using the daily observations are investigated. Observed gauged daily amounts are interpolated to unsampled points and subsequently disaggregated using the sub-daily values obtained by the radar. Different corrections based on the spatial variability and the subdaily entropy of scaled rainfall distributions are used to provide unbiased corrections of short duration extremes. Additionally a statistical procedure not based on a matching day by day correction is tested. In this last procedure as we are only interested in rare extremes, low to medium values of rainfall depth were neglected leaving a small number of L days of ranked daily maxima in each set per year, whose sum typically comprises about 50% of each annual rainfall total. The sum of these L day maxima is first iterpolated using a Kriging procedure. Subsequently this sum is disaggregated to daily values using a nearest neighbour procedure. The daily sums are then disaggregated by using the relative values of the biggest L radar based days. Of course, the timings of radar and gauge maxima can be different, so the method presented here uses radar for disaggregating daily gauge totals down to 15 min intervals in order to extract the maxima of sub-hourly through to daily rainfall. The methodologies were tested in South Africa, where an S-band radar operated relatively continuously at Bethlehem from 1998 to 2003, whose scan at 1.5 km above ground [CAPPI] overlapped a dense (10 km spacing) set of 45 pluviometers recording in the same 6-year period. This valuable set of data was obtained from each of 37 selected radar pixels [1 km square in plan] which contained a pluviometer not masked out by the radar foot-print. The pluviometer data were also aggregated to daily totals, for the same purpose. The extremes obtained using disaggregation methods were compared to the observed extremes in a cross validation procedure. The unusual and novel goal was not to obtain the reproduction of the precipitation matching in space and time, but to obtain frequency distributions of the point extremes, which we found to be stable. [ABSTRACT FROM AUTHOR]

Important hydrological changes are observed in Serbia, as well as in many parts of the world. Many national and international projects and studies address climate change and its impact on water resources. Some focus solely on the impact of climate change, while others also assess the impact of land use changes and/or changes in human use of water. Due to differences in climate change and human activities, the different climate and hydrological trends are obtained for the different regions in Serbia. This paper presents the past longterm temperature, precipitation and river discharge trends across Serbia. Second, more important aim of the research, is to assess and forecast average relationships between an increase in air temperature and changes in river discharges and precipitation. This relation could help us to find appropriate regional climate and hydrological models. Even within a single catchment, depending on the regional models used, the initial and other assumptions made, and the impacts assessed, the differences between the results can be small but often significant, too. The reliability of the projections receives little or no consideration. This paper also discusses this topic and attempts to provide some guidelines. [ABSTRACT FROM AUTHOR]

This paper analyzes the potential of a nu-support vector regression (nu-SVR) model for the reconstruction of missing data of hydrological time series from a sensor network. Sensor networks are currently experiencing rapid growth of applications in experimental research and monitoring and provide an opportunity to study the dynamics of hydrological processes in previously ungauged or remote areas. Due to physical vulnerability or limited maintenance, networks are prone to data outages, which can devaluate the unique data sources. This paper analyzes the potential of a nu-SVR model to simulate water levels in a network of sensors in four nested experimental catchments in a mid-latitude montane environment. The model was applied to a range of typical runoff situations, including a single event storm, multi-peak flood event, snowmelt, rain on snow and a low flow period. The simulations based on daily values proved the high efficiency of the nu-SVR modeling approach to simulate the hydrological processes in a network of monitoring stations. The model proved its ability to reliably reconstruct and simulate typical runoff situations, including complex events, such as rain on snow or flooding from recurrent regional rain. The worst model performance was observed at low flow periods and for single peak flows, especially in the high-altitude catchments. [ABSTRACT FROM AUTHOR]

Non‐catching type gauges are the emerging class of in situ precipitation measurement instruments. For these instruments, rigorous testing and calibration are more challenging than for traditional gauges. Hydrometeors characteristics like particle size, shape, fall velocity and density must be reproduced in a controlled environment to provide the reference precipitation, instead of the equivalent water flow used for catching‐type gauges. They are generally calibrated by the manufacturers using internal procedures developed for the specific technology employed. No agreed methodology exists, and the adopted procedures are rarely traceable to internationally recognized standards. The EURAMET project 18NRM03 'INCIPIT' on 'Calibration and accuracy of non‐catching instruments to measure liquid/solid atmospheric precipitation', funded by the European Metrology Programme for Innovation and Research (EMPIR), was initiated in 2019 to investigate calibration and accuracy issues of non‐catching measuring instruments used for liquid/solid atmospheric precipitation measurement. A survey of the existing models of non‐catching type instruments was initially performed and this paper provides an overview and a description of their working principles and the adopted calibration procedures. Both literature works and technical manuals disclosed by manufacturers are summarized and discussed, while current limitations and metrological requirements are identified. [ABSTRACT FROM AUTHOR]

The paper aims to provide an overview of the most important parameters (the occurrence, frequency and magnitude) in Vojvodina Region (North Serbia). Monthly and annual mean precipitation values in the period 1946-2014, for the 12 selected meteorological stations were used. Relevant parameters (precipitation amounts, Angot precipitation index) were used as indicators of rainfall erosivity. Rainfall erosivity index was calculated and classified throughout precipitation susceptibility classes liable of triggering soil erosion. Precipitation trends were obtained and analysed by three different statistical approaches. Results indicate that various susceptibility classes are identified within the observed period, with a higher presence of very severe rainfall erosion in June and July. This study could have implications for mitigation strategies oriented towards reduction of soil erosion by water. [ABSTRACT FROM AUTHOR]

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Recent field observations suggest that cloud-top precipitation generating cells (GCs) are ubiquitous in the warm-frontal and comma-head regions of midlatitude winter cyclones. The presence of fallstreaks emanating from the GCs and their persistence either to the surface or until merging into precipitation bands suggests that GCs are a critical component of the precipitation process in these cyclones. This paper is the second part of a three-part series that investigates the dynamics of GCs through very-high-resolution idealized Weather Research and Forecasting (WRF) Model simulations. This paper assesses the role of cloud-top instability paired with nighttime, daytime, or no radiative forcing on the development and maintenance (or lack) of GCs. Under initially unstable conditions at cloud top, GCs develop regardless of radiative forcing but only persist clearly with radiative forcing. Cloud-top destabilization due to longwave cooling leads to development of GCs even under initially neutral and stable conditions, providing a physical explanation for the observed ubiquity of GCs atop winter cyclones. GCs do not develop in initially stable simulations with no radiation. Decreased range in vertical velocity spectra under daytime radiative forcing is consistent with offset of the destabilizing influence of longwave cooling by shortwave heating. [ABSTRACT FROM AUTHOR]

For any quantitative applications that use reflectivity and/or differential reflectivity, radar observations need to be compensated for attenuation effects due to precipitation. This paper presents a robust attenuation correction system (ACS) for dual-polarization radars correcting the reflectivity factor as well as differential reflectivity profiles. The major advantage of the algorithm described in this paper is that the procedures are immune to the bias effect of reflectivity and differential reflectivity. In addition, this method is not very sensitive to the variation of temperature. The proposed ACS has been evaluated with X-band radar observations simulated from drop size distribution derived from high-resolution S-band measurements observed by the CSU-CHILL radar. The evaluation of the proposed retrieval algorithm shows that the retrieved reflectivity and differential reflectivity provide an improvement over the conventional self-consistent attenuation correction technique with the differential phase constraint. [ABSTRACT FROM PUBLISHER]

Precipitation displays a remarkable variability in space and time. An important yet poorly documented aspect of this variability is intermittency. In this paper, a new way of quantifying intermittency based on the burstiness B and memory M of interamount times is proposed. The method is applied to a unique dataset of 325 high-resolution rain gauges in the United States and Europe. Results show that the M- B diagram provides useful insight into local precipitation patterns and can be used to study intermittency over a wide range of temporal scales. It is found that precipitation tends to be more intermittent in warm and dry climates with the largest observed values in the southwest of the United States (i.e., California, Nevada, Arizona, and Texas). Low-to-moderate values are reported for the northeastern United States, the United Kingdom, the Netherlands, and Germany. In the second half of the paper, the new metrics are applied to daily rainfall data for 1954-2013 to investigate regional trends in intermittency due to climate variability and global warming. No evidence is found of a global shift in intermittency but a weak trend toward burstier precipitation patterns and longer dry spells in the south of Europe (i.e., Portugal, Spain, and Italy) and an opposite trend toward steadier and more correlated precipitation patterns in Norway, Sweden, and Finland is observed. [ABSTRACT FROM AUTHOR]

Drying and salt precipitation in geological formations can have serious consequences for upstream operations in terms of injectivity and productivity. Here we investigate the consequences of supercritical CO 2 injection in sandstones. The reported findings are directly relevant for CO 2 sequestration and acid–gas injection operations, but might also be of interest to a broader community dealing with drying and capillary phenomena. By injecting dry supercritical CO 2 into brine-saturated sandstone, we investigate the drying process and the associated precipitation of salts in a capillary-pressure-dominated flow regime. Precipitation patterns were recorded during the drying process by means of μCT scanning. The experimental results and numerical simulations show that under a critical flow rate salt precipitates with an inhomogeneous spatial distribution because of brine and solutes being transported in counter-current flow upstream where salt eventually precipitates. A substantial impairment of the absolute permeability has been found, but despite high local salt accumulation, the effective CO 2 permeability increased during all experiments. This phenomenon is a result of the observed microscopic precipitation pattern and eventually the resulting K ( ϕ ) relationship. The findings in this paper are related to unimodal sandstone. In a companion paper ( Ott et al., 2014 ) we present data on the distinctly different consequences of salt precipitation in dual- or multi-porosity rocks. [ABSTRACT FROM AUTHOR]

Precipitation is a very important input variable for numerous models in many scientific fields such as hydrology, agriculture, ecology, and environmental sciences. However, precipitation often exhibits considerable spatial variability and cannot be adequately modeled by commonly used geostatistical techniques, particularly in terms of the prediction uncertainty accuracy, which is of great significance to determine the effects on various models’ prediction uncertainty. In this paper, a moving-window copula-based geostatistical method was proposed to assess the local spatial uncertainty of precipitation. By incorporating non-stationary, non-Gaussian, and distance-weighted spatial statistics, many geostatistical techniques can be regarded as a special case of the proposed method. Especially, in this paper, the marginal distribution in each window was fitted using Legendre polynomials. Although the proposed method has the potential to improve both prediction accuracy and the prediction uncertainty accuracy, the case study showed that the prediction accuracy of the proposed method was not better than commonly used geostatistical techniques (i.e., ordinary kriging, moving window kriging, and the global copula-based method). However, the prediction uncertainty accuracy was the best of all. The moving-window copula-based geostatistical method allows the estimation of the full conditional distribution of the precipitation at any ungauged site. With the full conditional distributions, various analyses and decisions can be conducted and made. Moreover, in the sense of statistics, more accurate results could be expected. [ABSTRACT FROM AUTHOR]

This review paper presents the methods that have been used to date for the purification of crude biodiesel obtained by heterogeneous production processes. At first, a typical biodiesel production process using heterogeneous catalysts is shortly described, paying attention to the main processing steps. Then, possible impurities and their effects on the biodiesel quality are pointed out. The main part of this review paper deals with the traditional (wet and dry washing) and novel (membrane extraction, precipitation, complexation, simultaneous ion-exchange and precipitation as well as simultaneous biodiesel synthesis and purification) purification methods. These purification methods are compared with respect of their refining efficiency. A special attention is paid to their comparison regarding the type of raw materials used in biodiesel production. Furthermore, advantages and disadvantages of the crude biodiesel purification methods are emphasized. Finally, environmental aspects of crude biodiesel purification are highlighted. [ABSTRACT FROM AUTHOR]

In the context of climate change, scientists discuss the relevant reference periods for the assessment of changes in climate. Recently, many studies have been published comparing recent conditions with the last reference period 1961-1990. In this paper, the trends of annual, seasonal and monthly average air temperature, as well as annual, seasonal and monthly precipitation totals in Slovakia, are presented to point out changes which will probably show up in the next reference period 1991-2020. In the second part of paper, changes in the climate regions in Slovakia are analysed, comparing spatial distributions in the period 1961-1990 and in the period 1961-2010. [ABSTRACT FROM AUTHOR]

This paper presents the study of the impact of precipitation changes on alluvial aquifer systems in Xanthi Prefecture plain region, Greece. Two study areas were investigated, taking into account several hydrological and hydrogeological data for a time period of 23 years (1989-2011) measured and elaborated in the framework of the hydrogeological conceptual model assessment of the aquifer systems. It is considered that the evaluation and presentation of this kind of material is informative and quite necessary enforcing the reliability of the approach of the research presented in this paper. Graphs are designed showing precipitation monthly values and groundwater level fluctuation values recorded by three groundwater level loggers installed at the study areas. The conjunctive and synthetic assessment of the impact of precipitation on groundwater level fluctuation is carried out at three levels regarding precipitation moving average values fluctuation classified into thee time periods, high groundwater level values distinguished in three time periods, and correlation between precipitation moving average values and groundwater level values with temporal discrimination within specific hydrological years. It is concluded that the influence of precipitation on groundwater level fluctuation in the study area can almost responsibly be indicated based on original and reliable data contributing to better understanding and managing the functioning of the investigated aquifer system under several climate changes. [ABSTRACT FROM AUTHOR]

This paper compares the spatial distribution datasets on monthly precipitation totals derived from the Famine Early Warning System Network FEWS NET service (CHIRPS 2.0 product) and the International Mission of the Global Precipitation Measurement GPM (IMERG v06 product) with ground-based observations of a stationary weather stations located in the steppe region of the Crimean Peninsula in order to assess the representativeness of the precipitation spatial distribution and the applicability of the datasets for water balance calculations and agricultural crop dynamics modeling. A close convergence was observed between the estimated monthly precipitation totals and the precipitation gauge data during the study period (January 2017 - July 2020), with mean correlation coefficients of 0.75 and 0.73 for the GPM IMERG and CHIRPS, respectively. Both products generally overestimated the precipitation values compared to the measured data, with GPM IMERG (final run) exhibiting the greatest overestimations (1.3-2.1 times the weather station values). Our results demonstrate the requirement of GPM-derived precipitation estimations (particularly those from the GPM_3IMERDL v06 daily accumulated late run dataset) to be additionally verified and calibrated based on data from regional weather stations or the CHIRPS 2.0 product (if available). [ABSTRACT FROM AUTHOR]

In a series of two papers, rain-rate retrievals based on specific attenuation A at radar X-band wavelength using the R( A) method presented by Ryzhkov et al. are thoroughly investigated. Continuous time series of overlapping measurements from two polarimetric X-band weather radars in Germany during the summers of 2011-13 are used to analyze various aspects of the method, like miscalibration correction, ground clutter contamination, partial beam blockage (PBB), sensitivity to precipitation characteristics, and sensitivity to temperature assumptions in the retrievals. In Part I of the series, the relations inherent to the R( A) method were used to calculate radar reflectivity Z from specific attenuation and it was compared with measured reflectivity to estimate PBB and calibration errors for both radars. In this paper, R( A) rain estimates are compared to R( Z) and R( KDP) retrievals using specific phase shift KDP. PBB and calibration corrections derived in Part I made the R( Z) rainfall estimates almost perfectly consistent. Accumulated over five summer months, rainfall maps showed strong effects of clutter contamination if R( KDP) is used and weaker impact on R( A). These effects could be reduced by processing the phase shift measurements with more resilience toward ground clutter contamination and by substituting problematic R( KDP) or R( A) estimates with R( Z). Hourly and daily accumulations from rain estimators are compared with rain gauge measurements; the results show that R( A) complemented by R( Z) in segments with low total differential phase shift correlates best with gauges and has the lowest bias and RMSE, followed by R( KDP) substituted with R( Z) at rain rates below 8 mm h−1. [ABSTRACT FROM AUTHOR]

The release of seasonal (and longer) predictions of various climatological quantities is now routine. While undoubtedly devastating to lives and livelihoods, it is unclear whether seasonal extremes in precipitation-for example, extreme dry spells leading to droughts or heavy precipitation events leading to flooding-represent a feasible target for these predictions, that is, whether they are potentially predictable or are instead inherently unpredictable more than a few days to weeks in advance. This paper assesses the potential for predicting seasonal extremes in observed precipitation as a function of region and time of year by decomposing the station-based variance into that attributable to short-memory behavior of typical meteorological events-as generated from station-specific, seasonally varying, daily time-scale stationary stochastic weather models (SSWMs)-and that attributable to longer-time-scale, potentially predictable changes in precipitation-producing processes. Findings suggest the potential for making skillful predictions of seasonal precipitation extremes over the United States is enhanced (reduced) during the cool (warm) season, particularly for heavy precipitation event accumulations. Further, this potential is accentuated along the West Coast, around the Great Lakes, and over the central plains and Ohio River valley but is diminished over the Northeast and northern Great Plains. However, findings also suggest the potential for producing seasonal (and longer) predictions of seasonal precipitation extremes is spatially and seasonally dependent. As such, this paper includes supplemental material for the potentially predictable variance of seasonal extreme dry spell lengths, heavy event accumulations, and total accumulations at 774 stations across all 365 days so readers can evaluate the potential predictability for the location, timing, and metric of most relevance to them. [ABSTRACT FROM AUTHOR]

In a two-part paper, radar rain-rate retrievals using specific attenuation A suggested by Ryzhkov et al. are thoroughly investigated. Continuous time series of overlapping measurements from two twin polarimetric X-band weather radars in Germany during the summers of 2011-13 are used to analyze various aspects of rain-rate retrieval, including miscalibration correction, mitigation of ground clutter contamination and partial beam blockage (PBB), sensitivity to precipitation characteristics, and the temperature assumptions of the R( A) technique. In this paper, the relations inherent to the R( A) method are used to estimate radar reflectivity Z from A and compare it to the measured Z in order to estimate PBB and calibration offsets for both radars. The fields of Z estimated from A for both radars are consistent, and the differences between Z( A) and measured Z are in good agreement with the ones calculated using either consistency relations between reflectivity at horizontal polarization Z H, differential reflectivity ZDR, and specific differential phase KDP in rain or a digital elevation model in the presence of PBB. In the analysis, the dependence of A on temperature appears to have minimal effects on the overall performance of the method. As expected, the difference between Z( A) and attenuation-corrected measured Z observations varies with rain type and exhibits a weak systematic dependency on rainfall intensity; thus, averaging over several rain events is required to obtain reliable estimates of the Z biases caused by radar miscalibration and PBB. [ABSTRACT FROM AUTHOR]

The oceanic influence on winter precipitation in the Iberian Peninsula has been evidenced in numerous scientific papers. Large-scale forecasting models generally use variables such as Sea Surface Temperature (SST), soil moisture and ice cover, but they are not very accurate yet. Using observational data, this paper analyzes the influence of North Atlantic and Mediterranean SST on winter precipitation in the Iberian Peninsula between October 1951 and September 2011. First, trends of both data sets have been calculated to study their behavior during the past six decades, showing an overall increase of SST and a substantial decrease in winter precipitation in the Iberian Peninsula, except in eastern and south-eastern regions. Then, connection patterns between autumn Sea Surface Temperature Anomalies and winter precipitation have been studied to identify ocean regions that may be used as potential predictors of winter precipitation. After applying a Principal Component Analysis to cluster the information provided by the 1431 measuring points of a SST grid with a small number of variables, the Principal Components extracted were introduced into a Multiple Linear Regression algorithm in order to obtain an estimation of winter precipitation in each river basin. The validation process has shown that the algorithm explains nearly 50% of inter-annual variability of winter precipitation in the basins of the Iberian Peninsula with a strongly oceanic influence; this percentage is somewhat lower in the Mediterranean regions. [ABSTRACT FROM AUTHOR]

This paper describes the structural and photocatalytic studies of TiO 2 nanoparticles prepared by two different precipitation methods using titanium tetrachloride (TiCl 4) and titanium oxalate [Ti(C 2 O 4) 2 as raw materials for the first time. The samples were characterized by TG-DSC, XRD, TEM, EDS, SAED, UV–Vis, Raman, N 2 adsorption-desorption isotherms, and XPS to investigate the effects of salt type and calcination temperature on the crystal structure, morphology, composition, energy band gap and photocatalytic activity of TiO 2 nanoparticles. Results indicated that when TiCl 4 was used as Ti source, the crystallization temperature of amorphous TiO 2 to anatase TiO 2 was as low as 250 °C, but it increased to ~450 °C when Ti(C 2 O 4) 2 was selected. Besides, TiCl 4 was able to dynamically modify the crystalline structure of TiO 2 nanoparticles from anatase into rutile after calcination at ~450 °C, however this temperature was increased to ~850 °C for Ti(C 2 O 4) 2. The optimal photocatalytic property of methyl orange (MO) degradation in two TiO 2 systems was 99.08% and 38.6% with corresponding calcination temperatures of 450 °C and 550 °C, respectively, which was mainly correlated with the different crystal structure and crystallite size. [ABSTRACT FROM AUTHOR]

In this paper, a nonlinear mathematical model is proposed and analyzed to study the removal of two gaseous pollutants and the mixture of particulate matters formed separately by these two gases from the atmosphere of a city by rain. It is assumed that particulate matters are formed in the atmosphere by chemical transformations of two gaseous pollutants emitting in the atmosphere in presence of rain. The atmosphere, during rain, is assumed to consist of six interacting phases namely, the raindrops phase, the two phases of gaseous pollutants, their absorbed phases and the phase of the mixture of particulate matters. It is also assumed that gaseous pollutants are removed from the atmosphere by the process of absorption while the particulate matters are removed only by the process of impaction with different removal rates. By analyzing the model, it is shown that under appropriate conditions, these gaseous pollutants and particulate matters are removed from the atmosphere and their equilibrium levels, remaining in the atmosphere, would depend mainly upon the rates of emission of pollutants, growth rate of raindrops and the rate of raindrops falling on the ground, etc. It is found that if the rates of transformations of gaseous pollutants into particulate matters and the rainfall are very large, then these pollutants may be removed completely from the atmosphere. The numerical simulations performed support the analytical findings. [ABSTRACT FROM AUTHOR]

This paper simulates the responses of water budget components to doubled CO2 (2 × 378 ppm) concentration in the atmosphere with atmospheric and oceanic surface warming of 2°C. Simulations employed version 4.7 of the Regional Climate Model of the International Centre for Theoretical Physics (ICTP). Two six-year experiments were each repeated twice with the same model physics and parameterizations. The control experiment held the CO2 concentration at 378 ppm (no warming), while the other experiment specified doubled CO2 concentration and warming. The results showed a positive response (60-100% increase) to doubled CO2 for precipitation, runoff, and storage terms in Sierra Leone, Burkina Faso, Guinea Bissau, and the ocean area between 3 and 13°N. However, there was a negative response (up to 60%) for northern Senegal, southern Mali, and northern Nigeria. The reductions in water fluxes were observed mostly on the leeward side of the highlands. Evapotranspiration showed a negative response (1-20%) to doubled CO2 on the land north of 20°N. Burkina Faso and southern Mali responded oppositely to doubled CO2, despite their spatial proximity. [ABSTRACT FROM AUTHOR]

• Mixing effects on barium sulfate precipitation test process course were investigated. • Comparison of several literature barium sulfate precipitation kinetics is presented. • Two reactor types of three different sizes each are considered. • Mixing in jet reactors was generally found to be faster than precipitation. • Both large eddy simulations and k-ε model can be used for precipitation modeling in jet reactors. The paper presents an application of large eddy simulations (LES) to predict the course of barium sulfate precipitation carried out in jet reactors and basic guidelines for a reactor design. The reactors in question were of different geometries and made in different sizes in order to achieve high mixing intensities and low residence times in a mixing chamber, thus enabling to reflect and understand the effects of process conditions and influence of mixing on the course of precipitation better. The system's behavior is explained using experimental and simulation results. Simulations were validated by comparing LES model predictions with experimental data, as well as the k-ε model supplemented with the multiple-time-scale mixing model. The BaSO 4 precipitation results obtained with a CFD based precipitation model are in a very good agreement with experiments and are used to distinguish the jet reactors that allow obtaining a product with favorable characteristics, i.e., the smallest mean particle size. In general, the smallest studied reactors are found to best meet this criterion. A special attention is given to precipitation kinetics models, the choice of which can significantly affect predictions' accuracy. Several literature precipitation kinetics models were tested and the ones working best in jet reactors were identified. Finally, a time-scale analysis of process controlling mechanisms is highlighted and the assumption of negligibility of the subgrid closure for precipitation in LES is validated. [ABSTRACT FROM AUTHOR]