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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]

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]

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]

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]

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]

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]

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]

• 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]

Beijing and its surrounding areas experienced a torrential rainstorm from July 21 to 22, 2012. Previous studies have shown that melting was the main rainwater source in this process. In this paper, melting conversion processes were set to zero (NPMLT test) to analyze the effect of microphysical processes on the structure and precipitation of the convective system. The results showed that without the melting processes, the wind shear at the 700 hPa level decreased, and the wind field in Beijing and its surrounding areas changed. The cold front system moved faster, and the rainfall amount only reached the low rain level, much lower than that during the actual rainstorm. The hydrometeors sources had apparently changed. Though the latent heat release was large and little latent heat absorption occurred in the NPMLT test, the net latent heat did not affect the development of the convective system, and the precipitation was low. Therefore, microphysical processes greatly influence precipitation and convective system. [ABSTRACT FROM AUTHOR]

The Bay Area of California and surrounding region receives much of its annual precipitation during the October–March wet season, when atmospheric river events bring periods of heavy rain that challenge water managers and may exceed the capacity of storm sewer systems. The complex terrain of this region further complicates the situation, with terrain interactions that are not currently captured in most operational forecast models and inadequate precipitation measurements to capture the large variability throughout the area. To improve monitoring and prediction of these events at spatial and temporal resolutions of interest to area water managers, the Bay Area Advanced Quantitative Precipitation Information project was developed. To quantify improvements in forecast precipitation, model validation studies require a reference dataset to compare against. In this paper we examine 10 gridded, high-resolution (≤10 km, hourly) precipitation estimates to assess the uncertainty of high-resolution quantitative precipitation estimates (QPE) in areas of complex terrain. The products were linearly interpolated to 3-km grid spacing, which is the resolution of the operational forecast model to be validated. Substantial differences exist between the various products at accumulation periods ranging from hourly to annual, with standard deviations among the products exceeding 100% of the mean. While the products seem to agree fairly well on the timing of precipitation, intensity estimates differ, sometimes by an order of magnitude. The results highlight both the need for additional observations and the need to account for uncertainty in the reference dataset when validating forecasts in this area. [ABSTRACT FROM AUTHOR]

The paper is focused on the problem of weather radar precipitation compositing and aims to produce the data for the whole measurement domain in a way that ensures the quality of the composite is as high as possible. This is achieved by employing information about the data quality in the form of a quality index (QI) map. Different techniques that take the QI values as the compositing criterion are investigated; they apply the maximum or the weighted mean from particular radars. The proposed method employs a combination of the QI value and the distance from the radar site as a criterion in a weighted mean approach. Different versions of the quality‐based techniques are compared with standard techniques that are based on the maximum of estimated precipitation and distance from the nearest radar site. Verification of the techniques was performed employing statistical metrics by comparison against rain gauge observations. Moreover qualitative verification with assessment of seamlessness and the presence of contamination was carried out on long‐term accumulations of the composites generated by means of different methods. The proposed method based on QI value and distance from the radar site was found to be the most suitable for radar precipitation compositing. [ABSTRACT FROM AUTHOR]

The measurement of rainfall has a long history, but despite its apparent simplicity it is difficult to quantify accurately. The common installation of raingauges with rims above the ground surface results in a difference between the rainfall caught and the amount reaching ground level, termed undercatch. The UK standard installation of raingauges is for their rim to be sited at 0.305 m above the ground; however, the use of weighing gauges installed at a minimum rim height of 1 m has increased in recent years. The installation of these weighing raingauges raises complex questions of homogeneity in rainfall data across space and time. Here, we investigate the impact of these changes using field trials of commonly deployed UK raingauges at a site in south-east England. This paper discusses the results of the trial, exploring the variation in and potential drivers of undercatch with differing gauge sitings. With varying standards for gauge heights around the world and new rainfall measurement technologies coming to the market all the time, improved understanding of undercatch is needed to inform evolving operational practices and explore the possibility of developing catch correction algorithms to remove arising inhomogeneity in precipitation datasets. [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]

This paper highlights detailed projected changes in rainfall over Thailand for the early (2011–2040), middle (2041–2070) and late (2071–2099) periods of the 21st century under the representative concentration pathways (RCP) 4.5 and RCP 8.5 using the high‐resolution multi‐model simulations of the Coordinated Regional Climate Downscaling Experiment (CORDEX) Southeast Asia. The ensemble mean is calculated based on seven members consisting of six general circulation models (GCMs) and three regional climate models (RCMs). Generally, the ensemble mean precipitation agrees reasonably well with observations, best represented by the Global Precipitation Climatology Center (GPCC) data, over Thailand during the historical period (1976–2005). However, inter‐model variations can be large among ensemble members especially during dry months (December to March) for northern‐central‐eastern parts, and throughout the year for the southern parts of Thailand. Similarly for future projection periods, inter‐model variations in the sign and magnitude of changes exist. The ensemble means of projected changes in rainfall for both RCPs during dry months show distinct contrast between the northern‐central‐eastern parts and the southern parts of Thailand with generally wetter and drier conditions, respectively. The magnitude of change can be as high as 15% of the historical period, which varies depending on the sub‐region, season, projection period, and RCP scenario. In contrast, generally drier conditions are projected during the wet season (June to September) throughout the country for both RCPs where the rainfall reduction can be as high as 10% in some areas. However, the magnitude of projected rainfall changes of some individual models can be much larger than the ensemble means, exceeding 40% in some cases. These projected changes are related to the changes in regional circulations associated with the winter and summer monsoons, which are projected to weaken. The drier (wetter) condition is associated with the enhanced subsidence (rising motion). [ABSTRACT FROM AUTHOR]

We have investigated the predictability of precipitation using a new configuration of the superparameterized Community Atmosphere Model (SP‐CAM). The new configuration, called the multiple‐instance SP‐CAM, or MP‐CAM, uses the average heating and drying rates from 10 independent two‐dimensional cloud‐permitting models (CPMs) in each grid column of the global model, instead of a single CPM. The 10 CPMs start from slightly different initial conditions and simulate alternative realizations of the convective cloud systems. By analyzing the ensemble of possible realizations, we can study the predictability of the cloud systems and identify the weather regimes and physical mechanisms associated with chaotic convection. We explore alternative methods for quantifying the predictability of precipitation. Our results show that unpredictable precipitation occurs when the simulated atmospheric state is close to critical points as defined by Peters and Neelin (2006, https://doi.org/10.1038/nphys314). The predictability of precipitation is also influenced by the convective available potential energy and the degree of mesoscale organization. It is strongly controlled by the large‐scale circulation. A companion paper compares the global atmospheric circulations simulated by SP‐CAM and MP‐CAM. Key Points: Multiple‐instance superparameterization is described, and its small‐scale ensemble is used to explore precipitation predictabilityA measure of spread, called proportional variability, is found to reliably characterize predictabilityUnpredictable precipitation is related to the CAPE magnitude, degree of mesoscale organization, and proximity to atmospheric critical points [ABSTRACT FROM AUTHOR]

The paper studies the connection between the precipitation regime over the northern Baikal mountain region during the warm season (April–October) and atmospheric macrocirculation processes, the results are presented. Based on the data of ten weather stations, spatiotemporal heterogeneities in the precipitation regime are revealed for the period of 2000–2018. The long-term (since the middle of the 1960s) trends in total precipitation are evaluated. According to the analysis of HYSPLIT five-day backward trajectories (for days with precipitation), the main directions of moisture transport to the study area are identified, and the trajectories are typed for each month. Three groups of atmotpheric macroprocesses which induce precipttation are identified, and the contribution of each group to total precipitation is estimated. The spatial distinction between different parts of the study area in the precipitation regime and predominant moisture sources is found. [ABSTRACT FROM AUTHOR]

The intensity of interannual variation of spring precipitation over southern China during 1979–2014 and possible reasons for it are investigated in this paper. There is a significant interdecadal change in the intensity of interannual variation of spring precipitation over southern China around 1995/96. The intensity of interannual variation of spring rainfall over South China is stronger during 1979–95 than that during 1996–2014. The possible reason may be the larger amplitude of the sea surface temperature anomaly (SSTA) in the western Pacific Ocean (WP) before 1995/96. The cooler (warmer) SSTA in WP may trigger an abnormal local anticyclone (cyclone) at lower levels. The anomalous southwesterly (northeasterly) flow at the northwestern flank of the WP anticyclone (cyclone) covers South China, transporting more (less) moisture to South China. Meanwhile, the anomalous winds converge (diverge) in South China at lower levels and diverge (converge) at upper levels, which causes the anomalous ascent (descent) to enhance (reduce) the precipitation over there. However, during 1996–2014, the intensity of interannual variation of spring rainfall over the middle and lower reaches of the Yangtze River valley becomes much stronger than that during 1979–95, which is related to the intensified interannual variation of the atmospheric circulation in the middle and high latitudes over Eurasia. The weak (strong) Siberian high and East Asian trough may reduce (enhance) the northerly wind from the middle and high latitudes. As a result, the middle and lower reaches of the Yangtze River valley are subjected to the anomalous southerly wind, favoring more (less) precipitation over there. [ABSTRACT FROM AUTHOR]

Global mean precipitation changes due to climate change were previously shown to be relatively small and well constrained by the energy budget. However, local precipitation changes can be much more significant. In this paper we propose that for large enough scales, for which the water budget is closed (precipitation [P] roughly equals evaporation [E]), changes in P approach the small global mean value. However, for smaller scales, for which P and E are not necessarily equal and convergence of water vapor still plays a role, changes in P could be much larger due to dynamical contributions. Using 40 years of two reanalysis data sets, 39 Coupled Model Intercomparison Project Phase 5 (CMIP5) models and additional numerical simulations, we identify the scale of transition in the importance of the different terms in the water budget to precipitation to be ~3,500–4,000 km and demonstrate its relation to the spatial scale of precipitation changes under climate change. Plain Language Summary: Predicting precipitation changes due to climate change is of great importance for society. We propose that the present‐day characteristic scale of the hydrological cycle (for which precipitation roughly equals evaporation) predicts the spatial scale of future precipitation changes under global warming. For smaller scales than the characteristic scale of the hydrological cycle, changes in precipitation could be much larger than the global mean change due to water vapor convergence contributions. However, above this scale the precipitation changes approach the relatively small global mean change. Using reanalysis data sets, Coupled Model Intercomparison Project Phase 5 (CMIP5) models, and additional numerical simulations, we identify the characteristic scale of the hydrological cycle to be ~3,500–4,000 km and demonstrate its relation to the spatial scale of precipitation changes under climate change. These results suggest that changes in precipitation on the regional‐continental scale could be much larger than the global mean change. Key Points: The present‐day characteristic scale of the hydrological cycle predicts the spatial scale of precipitation changes under climate changeUsing reanalysis data sets and CMIP5 models, we identify the characteristic scale of the hydrological cycle to be ~3,500–4,000 kmThese results suggest that changes in precipitation on the continental scale could be much larger than the global mean change [ABSTRACT FROM AUTHOR]

Numerous circulation indices have been applied in practical climate services focused on regional precipitation. It is beneficial to identify the most influential or decisive indices, but this is difficult with conventional correlation analyses because of the underlying nonlinear mechanisms for precipitation. This paper demonstrates a set of the most influential indices for July–August precipitation in North China, based on the recursive random forest (RRF) method. These decisive circulation indices include the Polar–Eurasia teleconnection, North African subtropical high ridge position, India–Burma trough, Antarctic Oscillation, Northern Hemisphere polar vortex central latitude, North Atlantic Oscillation, and western Pacific subtropical high northern boundary position. Some of these factors have been recognized as directly influential to the regional precipitation, for example, those of the northwestern Pacific subtropical high; however, some are not easily understood. Decision tree (DT) models using these indices were developed to facilitate composite analyses to explain the RRF results. Taking one of the most interesting DT rules as an example, when the North African subtropical high ridge position is sufficiently far south, an anomalous anticyclone occurs in the upstream and an anomalous cyclone in the downstream of North China. This is unfavorable for northward moisture transport in eastern China and hence causes less precipitation in North China than climatology. The present results are not only helpful for improving diagnostic models of regional precipitation, but also enlightening for exploring how global climate change could impact a region by modulating large-scale circulation patterns. [ABSTRACT FROM AUTHOR]

There have been numerous statistical and dynamical downscaling model comparisons. However, differences in model skill can be distorted by inconsistencies in experimental set-up, inputs and output format. This paper harmonizes such factors when evaluating daily precipitation downscaled over the Iberian Peninsula by the Statistical DownScaling Model (SDSM) and two configurations of the dynamical Weather Research and Forecasting Model (WRF) (one with data assimilation (D) and one without (N)). The ERA-Interim reanalysis at 0. 75 ∘ resolution provides common inputs for spinning-up and driving the WRF model and calibrating SDSM. WRF runs and SDSM output were evaluated against ECA&D stations, TRMM, GPCP and EOBS gridded precipitation for 2010–2014 using the same suite of diagnostics. Differences between WRF and SDSM are comparable to observational uncertainty, but the relative skill of the downscaling techniques varies with diagnostic. The SDSM ensemble mean, WRF-D and ERAI have similar correlation scores ( r = 0.45 –0.7), but there were large variations amongst SDSM ensemble members ( r = 0.3 –0.6). The best Linear Error in Probability Space ( LEPS = 0.001 –0.007) and simulations of precipitation amount were achieved by individual members of the SDSM ensemble. However, the Brier Skill Score shows these members do not improve the prediction by ERA-Interim, whereas precipitation occurrence is reproduced best by WRF-D. Similar skill was achieved by SDSM when applied to station or gridded precipitation data. Given the greater computational demands of WRF compared with SDSM, clear statements of expected value-added are needed when applying the former to climate impacts and adaptation research. [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]

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]

Precipitation plays a crucial role in the Earth's energy balance, the water cycle, and the global atmospheric circulation. Aerosols, by direct interaction with radiation and by serving as cloud condensation nuclei, may affect clouds and rain formation. This effect can be examined in terms of energetic constraints, that is, any aerosol‐driven diabatic heating/cooling of the atmosphere will have to be balanced by changes in precipitation, radiative fluxes, or divergence of dry static energy. Using an aqua‐planet general circulation model (GCM), we show that tropical and extratropical precipitation have contrasting responses to aerosol perturbations. This behavior can be explained by contrasting ability of the atmosphere to diverge excess dry static energy in the two different regions. It is shown that atmospheric heating in the tropics leads to large‐scale thermally driven circulation and a large increase in precipitation, while the excess energy from heating in the extratropics is constrained due to the effect of the Coriolis force, causing the precipitation to decrease. Plain Language Summary: Precipitation, as the Earth's only natural source of fresh water, is of great importance for society. Climate change, besides changing the mean surface temperature and its distribution, is expected to change the precipitation's temporal and spatial distribution and, to a lesser extent, the global mean precipitation. One important agent in precipitation changes is anthropogenic aerosols. In this paper we study the response of precipitation to aerosol perturbations at different latitudes. Previously, it was proposed that aerosols drive a slowdown of the hydrological cycle. In addition, it was shown that, due to energy budget conservation, absorbing aerosols leads to a reduction in the global mean precipitation. Here we show that the response in the tropics is the opposite of the global mean response and of the extratropical response. Specifically, we show that the same aerosol perturbation generally increases precipitation in the tropics and decreases precipitation in the extratropics. This behavior can be explained by the contrasting ability of the atmosphere to diverge excess dry static energy in the tropics and extratropics. We also show that local aerosol perturbations could affect precipitation in remote regions due to a formation of large‐scale circulation. Key Points: Aerosol effect on precipitation is examined in terms of energetic constraintsAerosol perturbation generally increases precipitation in the tropics and decreases precipitation in the extratropicsThis behavior can be explained by contrasting ability of the atmosphere to diverge excess dry static energy in the two different regions [ABSTRACT FROM AUTHOR]

Asphaltene precipitation and deposition in different parts of petroleum industry increase considerably cost and problems in oil production. Due to these facts controlling asphaltene precipitation becomes one of valuable topics for research in petroleum engineering. Utilization of Asphaltene inhibitors is known as one of the dominant methods for controlling asphaltene precipitation so in this paper Adaptive neuro-fuzzy inference system (ANFIS) is joint with Genetic Algorithm (GA) to study effectiveness of asphaltene inhibitors on precipitation in terms of oil and inhibitors properties. In order to prepare and evaluate the ANFIS-GA algorithm, some reliable experimental data were gathered. The obtained results from the comparison shows the coefficient of determination (R2) for training and testing phases are 0.98804 and 0.9916 respectively. The determined indexes and graphical comparisons expresses that ANFIS-GA has enough accuracy and potential to estimate effectiveness of inhibitors on asphaltene precipitation reductions. [ABSTRACT FROM AUTHOR]

This paper points out two procedures for verifying the statistical independence between the historical and actual data series. They are based respectively on the computation of an empirical distance correlation coefficient, and the use of Hamming distance between binary encoded phase signals corresponding to Log-Gabor filtered time-series. Both procedures are applied to the monthly precipitation series recorded during 480 successive months at 49 meteorological stations in Dobrogea region (Romania) and on 4 and 5-valued fuzzified versions of the initial data represented using linguistic labels. The results show that the crisp data and their fuzzified versions cannot support the hypothesis of history-based predictability from their history. Hence, the two statistical independence tests are robust with respect to the k-means fuzzification of data and cross-validate each other, being applicable to any long-term analysis of precipitation series, to any other signals in general, and to their fuzzified versions, as well. [ABSTRACT FROM AUTHOR]

Translating changes in land surface conditions and climate into changes in precipitation, runoff and flood frequencies over a range of catchment scales is a pressing challenge for hydrologic design and flood risk management today. In this paper, we describe a novel approach for modeling areal runoff frequency from heavy-to-extreme precipitation in large urban areas using a simple but general stochastic model for runoff at point scale and bi- and univariate parametric probability distributions for positive point precipitation and areal runoff, respectively. We apply the approach to the Dallas–Fort Worth area using a 22-year historical multisensor precipitation dataset from the National Weather Service to characterize how the different factors that specify the second-order statistics of precipitation, imperviousness and soil water holding capacity at point scale may shape areal runoff frequency, and to assess how changes in precipitation climatology and land surface conditions may change areal runoff frequency as a function of catchment scale and magnitude of precipitation. The results indicate that areal runoff frequency is impacted most significantly by changes in climatological mean and coefficient of variation of positive point precipitation, water holding capacity of soil, imperviousness, and spatial correlation scale of positive point precipitation given the probability of occurrence of heavy-to-extreme precipitation, and that a very small number of low-order statistics of point precipitation may describe areal runoff frequency given the conditional probability distribution models for point precipitation and areal runoff. The approach presented hence offers a parsimonious physically-based alternative to purely numerical approaches based on integrated modeling, or empirical approaches based solely on statistical modeling toward predictive modeling of areal precipitation and runoff frequencies under changing hydroclimatological conditions. [ABSTRACT FROM AUTHOR]

This study presents the precipitation changes of the Heihe River Basin (HRB), Northwest China, using a long-term (1980–2014) and highly resolved modeling (up to 3 km by 3 km) with the Regional Integrated Environment Modeling System (RIEMS) forced by ERA-Interim reanalysis data. Firstly, the added value of high-resolution RIEMS simulation nested with ERA-Interim reanalysis was presented by comparisons among the RIEMS simulation results, site-based ground measurements, satellite-retrieved precipitation from TRMM 3B43 (V7), and the EAR-interim reanalysis data. The bias of the ERA-Interim reanalysis was largely corrected by the RIEMS simulation, although a little bias existed in the RIEMS simulation. RIEMS simulation showed that there was an increasing trend in the precipitation of the HRB from 1980 to 2014 with a rate of increase of approximately 3%/year for summer and 5%/year for autumn in the southeast part of the HRB. The increased precipitation mainly resulted from more precipitation days and the strengthening of daily precipitation. Upward motion from strengthened convergence over the eastern part of the HRB was the common reason for increased precipitation in summer and autumn, which was partly offset by decreased water vapor supply in summer while it was strengthened by increased water vapor supply in autumn. This paper presents precipitation changes for the HRB associated with global warming since 1980 and provides a higher-resolution climatological data set useful for reference climate impact studies. [ABSTRACT FROM AUTHOR]

The paper investigates the spatial distribution of the seasonal and annual precipitation in Bosnia and Herzegovina. The mean monthly precipitation data from 40 meteorological stations covering the standard climatological thirty-year period (1961-1990) were used for the analysis. Seven precipitation-based parameters were used to regionalize climate in Bosnia and Herzegovina by using the Principal Component Analysis and clustering techniques. The spatial patterns of precipitation were determined by using the R-mode principal component analysis with varimax rotation. The first two principal components, which describe 97.60% of the total variance, were taken into consideration. The varimax rotated scores were subjected to the Cluster Analysis in order to identify homogeneous precipitation regions over the territory of Bosnia and Herzegovina. The agglomerative hierarchical clustering identified three sub-regions with different precipitation regimes. The complex orography, i.e., the influence of the Pannonian Basin, the Dinaric Alps, and the Adriatic Sea, is one of the most decisive factors that affect spatial patterns of precipitation in Bosnia and Herzegovina. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate a 48‐member multiphysics ensemble using the Weather Research and Forecasting (WRF) model for the JJA extreme precipitation and temperature in 2003 over the CORDEX‐EA‐II domain. The simulated precipitation and temperature are reasonable in the subregions controlled by a large‐scale circulation, yet the biases for both precipitation and temperature are evident over the subregions where the effects of mesoscale processes are important. The performance of various combinations of WRF physical schemes for simulating the JJA precipitation is dependent on the region. Meanwhile, the cumulus and microphysical schemes have substantial influences on the simulation of precipitation, and the land surface models and cumulus schemes play crucial roles in the surface temperature. Our analysis shows that the combination of Noah for the land surface process, Lin for the microphysics, G3D for the cumulus parameterization, and CAM for the radiation scheme can provide the most reliable reproduction of both precipitation and temperature extremes over China. Ensemble analysis shows that the simulated climate extremes are usually accompanied by a large ensemble spread, implying sensitivities to the model physical processes in some subregions. The simulated wind fields at low‐to‐middle atmospheric levels display responses to the options of the land surface models and cumulus schemes. The essential impact of the land–atmospheric interaction on simulating the extremes can be largely attributed to the active convective processes. WRF has difficulties in reproducing the observed temporal evolution of the rainfall process, which consists of continuous large rainfall episodes in the observation data set during the simulation period. [ABSTRACT FROM AUTHOR]

precipitation and evaporation are two vital components of water cycle, and Hydrogen and oxygen stable isotopes are important tracers in water, which are very sensitive to changes in the climate and the water cycle. Rayleigh Fractionation equation is usually applied to calculate isotope distributions in order to quantify the precipitation and evaporation processes. It is reasonable to explain the evaporation process using the Rayleigh fractionation equation. However, the composition of hydrogen and oxygen stable isotopes in the precipitation will change due to the effects of dynamic fractionation and dilution during raindrop fall. In this case, it is not feasible to rely entirely on the Rayleigh fractionation equation. In this paper, atmospheric precipitation isotopes data recorded during 1996–2016 in Hong Kong from the Global Network of Isotopes in Precipitation (GNIP) are analyzed, including local meteoric water line (LMWL), deuterium-excess (d), temperature effect and rainfall amount effect. The results indicate that precipitation is affected by secondary evaporation and dilution effects. In addition, the stable isotope composition in precipitation is the result of temperature and precipitation. Due to the effects of these two effects, changes of isotope composition in precipitation are not always consistent. When the rainfall density is very large, the temperature effect is covered up and the temperature is inversely related to the isotope composition of precipitation. In contrast, when the rainfall density is small, the temperature is positively related to the isotope composition of precipitation. Therefore, it is suggested to consider the rainfall density while studying the relationship between the isotope composition of precipitation and the local climate. These finds can provide some enlightenments and references on how to investigate the changing pattern of isotope composition in precipitation. [ABSTRACT FROM AUTHOR]

A physically based Bayesian passive microwave precipitation retrieval requires an accurate forward radiative transfer model along with realistic database representation of hydrometeors, atmospheric properties, and surface emission. NASA’s Global Precipitation Measurement (GPM) Mission provides an unprecedented opportunity for the development of such databases, matching a well-calibrated radiometer with dual-frequency radar. Early versions of passive microwave products from GPM utilized a physically constructed database in a Bayesian retrieval scheme, assumed ice particles to be spheres, and used Mie radiative transfer. A large body of recent work demonstrates that this is insufficient for retrieval at the GPM radiometer frequencies. In this paper, the retrieval is updated to use nonspherical particles. Simulated brightness temperature (Tb) agreement with observations is shown to be significantly improved across the high frequencies, decreasing biases significantly and increasing correlations to observed Tb. This is compared with a second identical retrieval performed with the assumption of spherical ice particles, and retrieval results are compared globally, seasonally, and instantaneously for a case study at the rain rate level. While not at the high level of improvement shown in Tb space, the precipitation retrieval is improved as compared to one using observed Tb in correlation, bias, and root-mean-square error. Reported improvements, while modest in magnitude, advance the retrieval to more physical consistency which allows for deeper insight into ice particle properties associated with precipitation. [ABSTRACT FROM AUTHOR]

This paper evaluates several daily precipitation products over western and central Europe, identifies and documents their respective strengths and shortcomings, and relates these to uncertainties associated with each of the products. We analyze one gauge-based, three satellite-based, and two reanalysis-based products using high-density rain gauge observations as reference. First, we assess spatial patterns and frequency distributions using aggregated statistics. Then, we determine the skill of precipitation event detection from these products with a focus on extremes, using temporally and spatially matched pairs of precipitation estimates. The results show that the quality of the datasets largely depends on the region, season, and precipitation characteristic addressed. The satellite and the reanalysis precipitation products are found to have difficulties in accurately representing precipitation frequency with local overestimations of more than 40%, which occur mostly in dry regions (all products) as well as along coastlines and over cold/frozen surfaces (satellite-based products). The frequency distributions of wet-day intensities are generally well reproduced by all products. Concerning the frequency distributions of wet-spell durations, the satellite-based products are found to have clear deficiencies for maritime-influenced precipitation regimes. Moreover, the analysis of the detection of extreme precipitation events reveals that none of the non-station-based datasets shows skill at the shortest temporal and spatial scales (1 day, 0.25°), but at and above the 3-day and 1.25° scale the products start to exhibit skill over large parts of the domain. Added value compared to coarser-resolution global benchmark products is found both for reanalysis and satellite-based products. [ABSTRACT FROM AUTHOR]

Abstract Precipitation complexity measurement is often overlooked in precipitation time series research. Entropy, as a measure of system complexity, can be used to diagnose the complexity of precipitation. However, it is difficult to judge the applicability of different theoretical entropy models for solving precipitation uncertainty problems. This paper introduces the distinction degree theory and the serial number sum theory to screen the optimal entropy model for precipitation complexity measurement. The optimal entropy model was used to analyze the spatiotemporal differences of monthly precipitation complexity in Heilongjiang Province, China. Possible influencing factors of precipitation complexity were also examined. The results indicated that in the complexity measurement of precipitation based on entropy theory, the stability and reliability of sample entropy was higher than those of fuzzy entropy, wavelet entropy and permutation entropy. The complexity of monthly precipitation in the selected study area significantly increased with time. The average complexity of monthly maximum precipitation, monthly average precipitation and monthly minimum precipitation were 0.665, 0.622 and 0.545, respectively, and their tendency change rates were 0.070/decade, 0.055/decade and 0.038/decade, respectively. The areas with high monthly precipitation complexity were concentrated in the central, eastern and northwest parts of the study area, and the precipitation was less predictable. Monthly precipitation in the southwest was less complex and more predictable. The highest monthly precipitation complexity was 1.012, at Hulin station, and the lowest was 0.510, at Mingshui station. The increasing complexity of monthly precipitation in the province was strongly related to local industrial and agricultural production. The superposition effects of altitude, topographic relief, change in grassland area and agricultural production formed the basic pattern of spatial differences in monthly precipitation complexity. The results may provide a scientific guidance for regional precipitation predictability measurement, effective assessment of droughts and floods, and water resources management. Highlights • The optimal entropy model was selected to diagnose complexity in precipitation time series. • Complex monthly precipitation was concentrated in the central eastern and northwest parts of the study area. • Monthly precipitation complexity had a strong relationship with local industrial and agricultural production. • This study may provide a scientific guidance for regional water resources management. [ABSTRACT FROM AUTHOR]

Noting a strong imperative to understand precipitation extremes, and that considerable uncertainty affects observational data sets, this paper compares the representation of extremes in a number of widely used daily gridded products, derived from rain gauge data, satellite retrieval and reanalysis for the conterminous United States. Analysis is based upon the concept of "tail dependence" arising in multivariate extreme value theory, and we infer the level of temporal dependence in the joint tail of the precipitation probability distribution for pairwise comparisons of products. In this way, we consider the range of products more like an ensemble and examine the relationships between members, and do not attempt to define, or compare products to, some ground truth. Linear correlation between products is also computed. Considerable discrepancy between groups of products, both annually and seasonally, is linked to source data and complex terrain. In particular, products based on rain gauge data showed remarkable similarity, but differed considerably, showing almost total loss of extremal dependence during DJF in mountainous regions, when compared with satellite products. Additionally, simulated re-forecasts revealed reasonable temporal agreement with large scale generated extremes. The diversity and extent of discrepancies identified across all products raises important questions about their use, and we urge caution, particularly for products derived from satellite data. [ABSTRACT FROM AUTHOR]

This paper reports a consistent seesaw relationship between interdecadal precipitation variability over North China and the Southwest United States, which can be found in observations and simulations with several models. Idealized model simulations suggest the seesaw could be mainly driven by the interdecadal Pacific oscillation (IPO), through a large-scale circulation anomaly occupying the entire northern North Pacific, while the Atlantic multidecadal oscillation (AMO) contributes oppositely and less. Modulation of precipitation by the IPO tends to be intensified when the AMO is in the opposite phase, but weakened when the AMO is in the same phase. The warm IPO phase is associated with an anomalous cyclone over the northern North Pacific; consequently, anomalous southwesterly winds bring more moisture and rainfall to the Southwest United States, while northwesterly wind anomalies prevail over North China with negative rainfall anomalies. The east–west seesaw of rainfall anomalies reverses sign when the circulation anomaly becomes anticyclonic during the cold IPO phase. The IPO-related tropical SST anomalies affect the meridional temperature gradient over the North Pacific and adjacent regions and the mean meridional circulation. In the northern North Pacific, the atmospheric response to IPO forcing imposes an equivalent barotropic structure throughout the troposphere. An important implication from this study is the potential predictability of drought-related water stresses over these arid and semiarid regions, with the progress of our understanding and prediction of the IPO and AMO. [ABSTRACT FROM AUTHOR]

This paper scrutinizes the zonal oscillation of the western North Pacific subtropical high (WNPSH) via diagnosing its two extreme phases, which are defined by the top 10% strongest (positive phase) and the weakest (negative phase) WNPSH index (WNPSHI) days during summers in 1979–2016. Key findings include the following: a tripole pattern consisting of intensified (weakened) precipitation over the Maritime Continent and the East Asian summer monsoon regions, and suppressed (strengthened) precipitation over the western North Pacific summer monsoon region during positive (negative) WNPSH phases; a westward movement of WNPSH-induced precipitation anomalies that subsequently affects eastern China, Japan, and the Korean Peninsula at different time lags; an OLR–vorticity pattern explained by atmospheric responses to thermal sources is suggested to drive the oscillation; and the competitive interaction of local air–sea feedbacks, especially during the positive phase. In addition, moderate-to-strong positive correlations between the WNPSHI and the Niño-3.4 index are found on 1–2-, 2–3-, and 3–6-yr time scales; both exhibit decadal shifts to a higher-frequency mode, suggesting the intensification of both the zonal WNPSH oscillation and the ENSO under the changing climate and their close interdecadal association. A nonlinear quasi-biennial WNPSH–ENSO relationship is identified: the positive (negative) WNPSH phase sometimes occurs during 1) a decaying El Niño (La Niña) in the preceding summer/autumn, and/or 2) a developing La Niña (El Niño) in the current summer/autumn. A full ENSO transition from moderate-to-strong El Niño to La Niña is often seen during the positive phase, offering potential in predicting ENSO events and extreme WNPSH phases and thereby the summer monsoon rainfall in East Asia. [ABSTRACT FROM AUTHOR]