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Mediterranean regions are prone to heavy rainfall, flash floods, and erosion issues. Drop size distribution (DSD) is a key element for studying these phenomena through the hydrological variables which can be derived from it (rainfall rates and totals, kinetic energy fluxes). This paper proposes a five-year (2012-2016) DSD climatology, summarized by scaling parameters for concentration, size, and shape. The DSD network is composed of two longitudinal transects of three OTT Parsivel optical disdrometers each, across the Mediterranean Cevennes-Vivarais region. The influence of several factors are analysed: location (distance from the sea, orographic environment), season, daily synoptic weather situation (derived from geopotential heights, at 700 and 1000 hPa), rainfall type (analysed from 5 min radar data), as well as some combinations of these factors. It was found and/or confirmed that the orographic environment, season, weather patterns associated with the exposure to low level atmospheric flows, and rainfall types influenced the microphysical processes, leading to rainfall, measured at the ground. Consequently, the DSD characteristics, as well as the relationships between the rainfall rate and reflectivity factor, are influenced by these factors. [ABSTRACT FROM AUTHOR]

The results of metrological, hydrological, and environmental data analyses are mainly dependent on the reliable estimation of missing data. In this study, 21 classical methods were evaluated to determine the best method for infilling the missing precipitation data in Ethiopia. The monthly data collected from 15 different stations over 34 years from 1980 to 2013 were considered. Homogeneity and trend tests were performed to check the data. The results of the different methods were compared using the mean absolute error (MAE), root-mean-square error (RMSE), coefficient of efficiency (CE), similarity index (S-index), skill score (SS), and Pearson correlation coefficient (rPearson). The results of this paper confirmed that the normal ratio (NR), multiple linear regression (MLR), inverse distance weighting (IDW), correlation coefficient weighting (CCW), and arithmetic average (AA) methods are the most reliable methods of those studied. The NR method provides the most accurate estimations with rPearson of 0.945, mean absolute error of 22.90 mm, RMSE of 33.695 mm, similarity index of 0.999, CE index of 0.998, and skill score of 0.998. When comparing the observed results and the estimated results from the NR, MLR, IDW, CCW, and AA methods, the MAE and RMSE were found to be low, and high values of CE, S-index, SS, and rPearson were achieved. On the other hand, using the closet station (CS), UK traditional, linear regression (LR), expectation maximization (EM), and multiple imputations (MI) methods gave the lowest accuracy, with MAE and RMSE values varying from 30.424 to 47.641 mm and from 49.564 to 58.765 mm, respectively. The results of this study suggest that the recommended methods are applicable for different types of climatic data in Ethiopia and arid regions in other countries around the world. [ABSTRACT FROM AUTHOR]

The influence of urbanization on regional precipitation is one of the most important issues in hydrology. This paper selected the North Haihe Basin as the study area and explored the connection between summer precipitation and urbanization index (URBI) based on satellite precipitation and nighttime lights datasets. A moving spatial percentage anomaly method (MSP) was used to signify the local induced enhancement of precipitation (LIEP). Local indicators of spatial association (LISA) clustering for LIEP and URBI based on Bivariate Moran's I coupled with digital elevation model (DEM) segmentation was used to separate the impacts caused by urbanization and terrain uplifting, and thus, the regions of interest (ROI) where the urban induced enhancement of precipitation (UIEP) plays a dominant role were located. A geographically weighted regression (GWR) model was used to reveal the spatial variation of the sensitivity of UIEP to URBI within the ROI. Pearson correlation and cross-wavelet analyses (XWT) were adopted to investigate the teleconnection between UIEP and climate anomalies, using Niño3.4 and SOI as indices. The results indicated that: (1) Urbanization effects on precipitation spatial variation in the upstream mountainous area would be hidden away by topographic factors. (2) From the perspective of the basin, the highest urbanization level areas have the Lowest LIEP, while the suburban areas have the highest LIEP, and the rural areas are in the middle. (3) The UIEP and the URBI are generally negatively correlated within ROI. (4) UIEP versus Niño3.4 and SOI both show a significant common high-power period at a time scale of 2 years. This work can help comprehensively understand the hydrological response to urbanization. [ABSTRACT FROM AUTHOR]

This paper characterizes the influence of synoptic-scale air mass conditions on the spatial and temporal patterns of precipitation in North Carolina over a 16-year period (2003–2018). National Center for Environmental Prediction Stage IV multi-sensor precipitation estimates were used to describe seasonal variations in precipitation in the context of prevailing air mass conditions classified using the spatial synoptic classification system. Spatial analyses identified significant clustering of high daily precipitation amounts distributed along the east side of the Appalachian Mountains and along the Coastal Plains. Significant and heterogeneous clustering was prevalent in summer months and tended to coincide with land cover boundaries and complex terrain. The summer months were dominated by maritime tropical air mass conditions, whereas dry moderate air mass conditions prevailed in the winter, spring, and fall. Between the three geographic regions of North Carolina, the highest precipitation amounts were received in western North Carolina during the winter and spring, and in eastern North Carolina in the summer and fall. Central North Carolina received the least amount of precipitation; however, there was substantial variability between regions due to prevailing air mass conditions. There was an observed shift toward warmer and more humid air mass conditions in the winter, spring, and fall months throughout the study period (2003–2018), indicating a shift toward air mass conditions conducive to higher daily average rain rates in North Carolina. [ABSTRACT FROM AUTHOR]

Precipitation is a key climatic variable that connects the processes of atmosphere and land surface, and it plays a leading role in the water cycle. However, the vast area of Northwest China, its complex geographical environment, and its scarce observation data make it difficult to deeply understand the temporal and spatial variation of precipitation. This paper establishes a statistical downscaling model to downscale the monthly precipitation in the inland river basin of Northwest China with the Tarim River Basin (TRB) as a typical representation. This method combines polynomial regression and machine learning, and it uses the batch gradient descent (BGD) algorithm to train the regression model. We downscale the monthly precipitation and obtain a dataset from January 2001 to December 2017 with a spatial resolution of 1 km × 1 km. The results show that the downscaling model presents a good performance in precipitation simulation with a high resolution, and it is more effective than ordinary polynomial regression. We also investigate the temporal and spatial variations of precipitation in the TRB based on the downscaling dataset. Analyses illustrate that the annual precipitation in the southern foothills of the Tianshan Mountains and the North Kunlun Mountains showed a significant upward trend during the study periods, while the annual precipitation in the central plains presented a significant downward trend. [ABSTRACT FROM AUTHOR]

In the French Alps the quality of the radar Quantitative Precipitation Estimation (QPE) is limited by the topography and the vertical structure of precipitation. A previous study realized in all the French Alps, has shown a general bias between values of the national radar QPE composite and the rain gauge measurements: a radar QPE over-estimation at low altitude (+20% at 200 m a.s.l.), and an increasing underestimation at high altitudes (until −40% at 2100 m a.s.l.). This trend has been linked to altitudinal gradients of precipitation observed at ground level. This paper analyzes relative altitudinal gradients of precipitation estimated with rain gauges measurements in 2016 for three massifs around Grenoble, and for different temporal accumulations (yearly, seasonal, monthly, daily). Comparisons of radar and rain gauge accumulations confirm the bias previously observed. The parts of the current radar data processing affecting the bias value are pointed out. The analysis shows a coherency between the relative gradient values estimated at the different temporal accumulations. Vertical profiles of precipitation detected by a research radar installed at the bottom of the valley also show how the wide horizontal variability of precipitation inside the valley can affect the gradient estimation. [ABSTRACT FROM AUTHOR]

In this paper, the diurnal variations of various clouds are analyzed using hourly cloud observations at weather stations in China from 1985 to 2011. In combination with merged hourly precipitation data, the relationship between the diurnal variations of clouds and precipitation in the summers from 2008 to 2011 are studied. The results show that the occurrence frequencies of total cloud and various cloud types exhibit significant diurnal variations. The diurnal variations of the occurrence frequencies of altocumulus and stratocumulus show a bimodal pattern, with peaks appearing in the early morning and late afternoon. The early morning peaks of altocumulus and stratocumulus appear earlier in the summer than in the other seasons, while the late afternoon maxima show an opposite trend. The occurrence frequency of nimbostratus peaks in the morning between 07 and 12 LST (local solar time), and the peak value lags 2 to 3 h from west to east along the Yangtze River valley; meanwhile, the diurnal variation shows no clear differences caused by changes in the latitude or seasons. Cumulus shows an afternoon (14 LST) maximum, while cumulonimbus peaks in the late afternoon during 16–20 LST, and both of them present a great diurnal range. Cirrus usually reaches its peak at 17–18 LST, and it differs by 1 to 2 h with a change in the latitude. The results of the study first show that the diurnal variations of precipitation among different regions are dominated by different clouds. The upper reaches of the Yangtze River valley present a midnight precipitation maximum that is mainly dominated by cumulonimbus. For the middle reaches of the Yangtze River valley impacted by nimbostratus, the precipitation peaks in the early morning. In South and Northeast China, the precipitation peaks in the afternoon and is determined by the diurnal variations of convective clouds. In the region between the Yangtze River valley and Yellow River valley, the precipitation peaks in the early morning and afternoon; the early morning peak is mainly determined by stratiform clouds, while the afternoon peak is closely related to convective clouds. [ABSTRACT FROM AUTHOR]

The aim of ensemble precipitation prediction in this paper was to achieve the best performance via artificial intelligence (AI) based modeling. In this way, ensemble AI based modeling was proposed for prediction of monthly precipitation with three different AI models (feed forward neural network-FFNN, adaptive neural fuzzy inference system-ANFIS and least square support vector machine-LSSVM) for the seven stations located in the Turkish Republic of Northern Cyprus (TRNC). Two scenarios were examined each having specific inputs set. The scenario 1 was developed for predicting each station's precipitation through its own data at previous time steps while in scenario 2, the central station's data were imposed into the models, in addition to each station's data, as exogenous input. Afterwards, the ensemble modeling was generated to improve the performance of the precipitation predictions. To end this aim, two linear and one non-linear ensemble techniques were used and then the obtained outcomes were compared. In terms of efficiency measures, the averaging methods employing scenario 2 and non-linear ensemble method revealed higher prediction efficiency. Also, in terms of Skill score, non-linear neural ensemble method could enhance predicting efficiency up to 44% in the verification step. [ABSTRACT FROM AUTHOR]

Flash drought is the result of strong precipitation deficits and/or anomalous increases in atmospheric evaporative demand (AED), which triggers a rapid decline in soil moisture and stresses vegetation over short periods of time. However, little is known about the role of precipitation and AED in the development of flash droughts. For this paper, we compared the standardized precipitation index (SPI) based on precipitation, the evaporative demand drought index (EDDI) based on AED, and the standardized evaporation precipitation index (SPEI) based on the differences between precipitation and AED as flash drought indicators for mainland Spain and the Balearic Islands for 1961–2018. The results show large differences in the spatial and temporal patterns of flash droughts between indices. In general, there was a high degree of consistency between the flash drought patterns identified by the SPI and SPEI, with the exception of southern Spain in the summer. The EDDI showed notable spatial and temporal differences from the SPI in winter and summer, while it exhibited great coherence with the SPEI in summer. We also examined the sensitivity of the SPEI to AED in each month of the year to explain its contribution to the possible development of flash droughts. Our findings showed that precipitation is the main driver of flash droughts in Spain, although AED can play a key role in the development of these during periods of low precipitation, especially in the driest areas and in summer. [ABSTRACT FROM AUTHOR]

This study explored the potential for bias correction of global precipitation datasets (GPD) to support streamflow simulation for water resource management in data limited regions. Two catchments, 580 km² and 2530 km², in the Kilombero Valley of central Tanzania were considered as case studies to explore three GPD bias correction methods: quantile mapping (QM), daily percentages (DP) and a model based (ModB) bias correction. The GPDs considered included two satellite rainfall products, three reanalysis products and three interpolated observed data products. The rainfall-runoff model HBV was used to simulate streamflow in the two catchments using (1) observed rain gauge data; (2) the original GPDs and (3) the bias-corrected GPDs as input. Results showed that applying QM to bias correction based on limited observed data tends to aggravate streamflow simulations relative to not bias correcting GPDs. This is likely due to a potential lack of representativeness of a single rain gauge observation at the scale of a hydrological catchment for these catchments. The results also indicate that there may be potential benefits in combining streamflow and rain gauge data to bias correct GPDs during the model calibration process within a hydrological modeling framework. [ABSTRACT FROM AUTHOR]

Atmospheric ice nucleating particles (INPs) contribute to initiate precipitation. In particular, biological INPs act at warmer temperatures than other types of particles (>-10 °C) therefore potentially defining precipitation distribution. Here, in order to identify potential environmental drivers in the distribution and fate of biological INPs in the atmosphere, we conducted a mid-term study of the freezing characteristics of precipitation. A total of 121 samples were collected during a period of >1.5 years at the rural site of Opme (680ma.s.l. (above sea level), France). INP concentration ranged over two orders of magnitude at a given temperature depending on the sample; there were <1 INPs mL-1 at °-5 °C, ~0.1 to 10 mL-1 between -5 °C and -8 °C, and ~1 to 100 mL-1 at colder temperatures. The data support the existence of an intimate natural link between biological INPs and hydrological cycles. In addition, acidification was strongly correlated with a decrease of the freezing characteristics of the samples, suggesting that human activities impact the role of INPs as triggers of precipitation. Water isotope ratio measurements and statistical comparison with aerosol and cloud water data confirmed some extent of INP partitioning in the atmosphere, with the INPs active at the warmest temperatures tending to be more efficiently precipitated. [ABSTRACT FROM AUTHOR]

This study examines the variability of precipitation in the south-east of Tunisia through the analysis of data about annual and monthly precipitation at five stations in theWatershed of Gabes, from 1977 to 2015. Standardized precipitation ratio, wavelet and coherence wavelet analyses were applied to examine the temporal variability of monthly and annual precipitation and to determine the effect of climatic fluctuations on rainfall variability. Results of wavelet analysis showed varied energy bands at the studied stations at annual and inter-annual scales. The depicted bands spread according to intervals of 1-, 2- to 4-, 4- to 8- and 8- to 12-year cycles, obviously influenced by regional factors including altitude, proximity to the Mediterranean Sea and global fluctuations. Eventually, an analysis of wavelet coherence showed a strong correlation between precipitation and Mediterranean Oscillation (MO) in GabesWatershed at different temporal scales. Contribution of the MO ranged between 51% and 93% of fluctuations (8-12 years) in the different examined rainfall stations. [ABSTRACT FROM AUTHOR]

This study focuses on the impacts of climate change on rainfall erosivity in the Huai Luang watershed, Thailand. The multivariate climate models (IPCC AR5) consisting of CCSM4, CSIRO-MK3.6.0 and MRI-CGCM3 under RCP4.5 and RCP8.5 emission scenarios are analyzed. The Quantile mapping method is used as a downscaling technique to generate future precipitation scenarios which enable the estimation of future rainfall erosivity under possible changes in climatic conditions. The relationship between monthly precipitation and rainfall erosivity is used to estimate monthly rainfall erosivity under future climate scenarios. The assessment compared values of rainfall erosivity during 1982-2005 with future timescales (i.e., the 2030s, 2050s, 2070s and 2090s). The results indicate that the average of each General Circulation Model (GCM) combination shows a rise in the average annual rainfall erosivity for all four future time scales, as compared to the baseline of 8302 MJ mm ha-1 h-1 year-1, by 12% in 2030s, 24% in 2050s, 43% in 2070s and 41% in 2090s. The magnitude of change varies, depending on the GCMs (CCSM4, CSIRO-MK3.6.0, and MRI-CGCM3) and RCPs with the largest change being 82.6% (15,159 MJ mm ha-1 h-1 year-1) occurring under the MRI-CGCM3 RCP8.5 scenario in 2090s. A decrease in rainfall erosivity has been found, in comparison to the baseline by 2.3% (8114 MJ mm ha-1 h-1 year-1) for the CCSM4 RCP4.5 scenario in 2030s and 2.6% (8088 MJ mm ha-1 h-1 year-1) for the 2050s period. However, this could be considered uncertain for future rainfall erosivity estimation due to different GCMs. The results of this study are expected to help development planners and decision makers while planning and implementing suitable soil erosion and deposition control plans to adapt climate change in the Huai Luang watershed. [ABSTRACT FROM AUTHOR]

We conducted global warming projections using the Meteorological Research Institute-Atmospheric General Circulation Model Version 3.2with a 60-kmgrid size (MRI-AGCM3.2H). For the present-day climate of 21 years from 1983 through 2003, the model was forced with observed historical sea surface temperature (SST). For the future climate of 21 years from 2079-2099, the model was forced with future SST projected by conventional couple models. Twelve-member ensemble simulations for three different cumulus convection schemes and four different SST distributions were conducted to evaluate the uncertainty of projection. Annual average precipitation will increase over the equatorial regions and decrease over the subtropical regions. The future precipitation changes are generally sensitive to the cumulus convection scheme, but changes are influenced by the SST over the some regions of the Pacific Ocean. The precipitation efficiency defined as precipitation change per 1° surface air temperature warming is evaluated. The global average of precipitation efficiency for annual average precipitation was less than the maximum value expected by thermodynamical theory, indicating that dynamical atmospheric circulation is acting to reduce the conversion efficiency from water vapor to precipitation. The precipitation efficiency by heavy precipitation is larger than that by moderate and weak precipitation. [ABSTRACT FROM AUTHOR]

Wavelet analysis methods (CWT, XWT, WTC) were employed to evaluate the impact of dominant climatic driving factors on summer precipitation in the Beijing area based on monthly precipitation data of Beijing ranging from 1880 to 2014. The two climatic driving factors, i.e., the East Asian summer monsoon (EASM) and the Northern Limit of Western Pacific Subtropical High (NWPSH) were considered in particular. The relationships between summer precipitation and EASM/NWPSH were also examined. The results revealed similar periods in low-frequency oscillation (76-95 years) and mid-range frequency oscillation (32-60 years) for the summer precipitation in the Beijing area and EASM/NWPSH. The summer precipitation correlated positively with the NWPSH and EASM, especially for periods of 43 years and 33 years, respectively. This indicates that summer precipitation during 1880-1960 and during the years after 1960 was significantly affected by NWPSH and EASM, respectively. Based on the periodic change of 33 years for both summer precipitation and EASM, heavy precipitation can be expected to occur again in Beijing at approximately 2026. Understanding the relationships between summer precipitation and climatic factors is of significant importance for precipitation predictions and water resource variations in the Beijing area. [ABSTRACT FROM AUTHOR]

In this study, we investigate the sources of moisture (and moisture for precipitation) over the Danube River Basin (DRB) by means of a Lagrangian approach using the FLEXPART V9.0 particle dispersion model together with ERA-Interim reanalysis data to track changes in atmospheric moisture over 10-day trajectories. This approach computes the budget of evaporation-minus-precipitation by calculating changes in specific humidity along forward and backward trajectories. We considered a time period of 34 years, from 1980 to 2014, which allowed for the identification of climatological sources and moisture transport towards the basin. Results show that the DRB mainly receives moisture from seven different oceanic, maritime, and terrestrial moisture source regions: North Atlantic Ocean, North Africa, the Mediterranean Sea, Black Sea, Caspian Sea, the Danube River Basin, and Central and Eastern Europe. The contribution of these sources varies by season. During winter (October-March) the main moisture source for the DRB is the Mediterranean Sea, while during summer (April-September) the dominant source of moisture is the DRB itself. Moisture from each source has a different contribution to precipitation in the DRB. Among the sources studied, results show that the moisture from the Mediterranean Sea provides the greatest contribution to precipitation in the basin in both seasons, extending to the whole basin for the winter, but being more confined to the western side during the summer. Moisture from the Caspian and Black Seas contributes to precipitation rather less. [ABSTRACT FROM AUTHOR]

Climate signal maps can be used to identify regions where robust climate changes can be derived from an ensemble of climate change simulations. Here, robustness is defined as a combination of model agreement and the significance of the individual model projections. Climate signal maps do not show all information available from the model ensemble, but give a condensed view in order to be useful for non-climate scientists who have to assess climate change impact during the course of their work. Three different ensembles of regional climate projections have been analyzed regarding changes of seasonal mean and extreme precipitation (defined as the number of days exceeding the 95th percentile threshold of daily precipitation) for Germany, using climate signal maps. Although the models used and the scenario assumptions differ for the three ensembles (representative concentration pathway (RCP) 4.5 vs. RCP8.5 vs. A1B), some similarities in the projections of future seasonal and extreme precipitation can be seen. For the winter season, both mean and extreme precipitation are projected to increase. The strength, robustness and regional pattern of this increase, however, depends on the ensemble. For summer, a robust decrease of mean precipitation can be detected only for small regions in southwestern Germany and only from two of the three ensembles, whereas none of them projects a robust increase of summer extreme precipitation. [ABSTRACT FROM AUTHOR]

The Mediterranean region is characterized by its vulnerability to changes in the water cycle, with the impact of global warming on the water resources being one of the major concerns in social, economical and scientific ambits. Even if precipitation is the best-known term of the Mediterranean water budget, large uncertainties remain due to the lack of suitable offshore observational data. In this study, we use the data provided by the Advanced Microwave Sounding Unit-B (AMSU-B) on board NOAA satellites to detect and analyze precipitating and convective events over the last decade at spatial resolution of 0.2° latitude x 0.2° longitude. AMSU-B observation shows that rain occurrence is widespread over the Mediterranean in wintertime while reduced in the eastern part of the basin in summer. Both precipitation and convection occurrences display a weak diurnal cycle over sea. In addition, convection occurrences, which are essentially located over land during summertime, shift to mostly over the sea during autumn with maxima in the Ionian sub-basin and the Adriatic Sea. Precipitation occurrence is also inferred over the sea from two other widely used climatological datasets, HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis interim (ERA-Interim). There is generally a rather fair agreement between these climatologies for describing the large-scale patterns such as the strong latitudinal gradient of rain and eastward rain signal propagation. Furthermore, the higher spatial resolution of AMSU-B measurements (16 km at nadir) gives access to mesoscale details in the region (e.g., coastal areas). AMSU-B measurements show less rain occurrences than HOAPS during wintertime, thereby suggesting that some of the thresholds used in our method might be too stringent during this season. We also observed that convection occurrences in ERA-Interim are systematically lower than those derived from AMSU-B. These results are potentially valuable to evaluate the rainfall parameterization in weather and climate models and to constrain ocean models. [ABSTRACT FROM AUTHOR]

The diurnal cycle of the North American monsoon is analyzed based on the output from a mesoscale model simulation. Statistically significant diurnal cycle in precipitation is identified, with heavy precipitation--essentially convective--dominating in local afternoons. Temporal evolution of key parameters in relation to precipitation is investigated, based on which a sequence of the dynamic/thermodynamic processes underlying precipitation development is proposed. Particularly, the afternoon peak in precipitation is found preceded by enhanced static instability and low-level convergence. [ABSTRACT FROM AUTHOR]

As atmospheric particle matter (PM) pollution has been proven to be a public health risk, we investigated how PM concentrations of various particle diameters may be impacted by precipitation. Repeated measures over time of urban PM concentrations for particles of 0.2–50 µm in diameter were compared with precipitation data from Météo-France weather stations in Paris, Angers and Palaiseau from 2013 to 2019. A significant negative correlation, using Kendall's rank correlation, was found between the amount of precipitation and concentrations of particles >3 µm. Distribution comparative analysis (Dunn's test) of 154 events of 1 mm or more of rain demonstrated a decrease in concentrations for particles from 10 to 50 µm in diameter. Additionally, granulometric analysis of a typical heavy rain event showed a 10-fold decrease in concentrations of particles 10 to 30 µm in diameter one hour after rain compared with one hour before. We were able to show that measured concentrations of particles between 10 and 50 µm in diameter diminish when it rains, with a lasting effect of approximately 10–15 h. [ABSTRACT FROM AUTHOR]

We analyzed 28-year-long monthly oxygen isotope composition of precipitation (δ18Op) data from Punta Arenas (Chile) on the leeward side of the Andes to understand how different synoptic weather types and moisture transport pathways influence δ18Op variability in this region. Combining weather station 6 h precipitation data and atmospheric back trajectories, we found that in such a region where the atmospheric circulation pattern is dominated by very strong westerlies, an increased monthly proportion of easterly-delivered precipitation—with the air-mass trajectory path evading the influence of Andean "isotopic rain shadow" and having less rainout en route—would increase δ18Op. These synoptic easterlies are a result of quasi-stationary blocking-like flow that are an important but underappreciated part of regional circulation patterns and climate. In addition, synoptic easterlies are more often associated with heavy precipitation events as shown by weather station data and higher deuterium excess that indicates weaker post-condensation raindrop re-evaporation. Therefore, our analysis demonstrated the process link between the frequency of synoptic weather types characterized by blocking-like flow and temporal variations in δ18Op in Southern Patagonia. We conclude that isotope proxy paleo-records in this region could provide unique insights into the behaviors and dynamics of the large-scale Southern Hemisphere Westerly Winds over long timescales. [ABSTRACT FROM AUTHOR]

The island of Corsica in the western Mediterranean is characterized by a pronounced topography in which local breeze systems develop in the diurnal cycle. In interaction with the large-scale synoptic situation, various precipitation events occur, which are classified in this study with regard to their duration and intensity. For this purpose, the island was grouped into five precipitation regimes using a cluster analysis, namely the western coastal area, the central mountainous region, the southern coastal area, the northeast coastal area, and the eastern coastal area. Based on principal component analysis using mean sea level pressure (mslp) obtained from ERA5 reanalysis (the fifth generation of the European Centre for Medium-Range Weather Forecasts, ECMWF), six spatial patterns were identified which explain 98% of the large-scale synoptic situation, while the diurnal breeze systems within the regimes characterize local drivers. It is shown that on radiation days with weak large-scale pressure gradients, pronounced local circulations in mountainous regions are coupled with sea breezes, leading to a higher number of short and intense precipitation events. Meridional circulation patterns lead to more intensive precipitation events on the eastern part of the island (30% intensive events with meridional patterns on the east side compared to 11% on the west side). On the west side of Corsica, however, coastal precipitation events are seldom and less intense than further inland, which can be attributed to the influence of the topography in frontal passages. [ABSTRACT FROM AUTHOR]

This study examines the influence of the Atlantic Multidecadal Oscillation (AMO) on the Choco Low-level Jet (CJ) variations during the 1983–2016 period. Considering the September–November (SON) 925 hPa zonal wind index in the CJ core, a significant breakpoint occurs in 1997 with larger values after 1997. The changes in the CJ and Caribbean Low-Level Jet (CLLJ), and their related ocean-atmospheric patterns and impacts on precipitation over Colombia were analyzed considering separately the 1983–1996 and 1998–2016 periods, which overlap the cold and warm AMO phases, respectively. During the 1998–2016 period, the negative sea surface temperature (SST) anomalies in the tropical Pacific Ocean and the positive ones in the Caribbean Sea and Tropical North Atlantic (TNA) strengthen the CJ and weaken the CLLJ, and moisture is transported into Central and Western Colombia increasing the rainfall there. Our results indicate that part of the CJ strengthening after 1997 was due to a higher percentage of intense CJ events coinciding with La Niña events during the warm AMO and cold Pacific Decadal Oscillation (PDO) background. However, the AMO-related SST and sea level pressure (SLP) variations in the TNA seem to be more crucial in modulating the CJ and CLLJ intensities, such that CJ is weakened (intensified) and CLLJ is intensified (weakened) before (after) 1997. As far as we know, the relations of the CJ and CLLJ intensities to the AMO phases were not examined before and might be useful for modeling studies. [ABSTRACT FROM AUTHOR]

Twenty-five climate indices based on daily maximum and minimum temperature and precipitation at 15 meteorological stations were examined to investigate changes in temperature and precipitation extremes over the Yarlung Tsangpo River Basin (1970–2017). The trend-free prewhitening (TFPW) Mann–Kendall test and Pettitt's test were used to identify trends and abrupt changes in the time series, respectively. The results showed widespread significant changes in extreme temperature indices associated with warming, most of which experienced abrupt changes in the 1990s. Increases in daily minimum and maximum temperature were detected, and the magnitude of daily minimum temperature change was greater than that of the daily maximum temperature, revealing an obvious decrease in the diurnal temperature range. Warm days and nights became more frequent, whereas fewer cold days and nights occurred. The frequency of frost and icing days decreased, while summer days and growing season length increased. Moreover, cold spell length shortened, whereas warm spell length increased. Additionally, changes in the precipitation extreme indices exhibited much less spatial coherence than the temperature indices. Spatially, mixed patterns of stations with positive and negative trends were found, and few trends in the precipitation extreme indices at individual stations were statistically significant. Generally, precipitation extreme indices showed a tendency toward wetter conditions, and the contribution of extreme precipitation to total precipitation has increased. However, no significant regional trends and abrupt changes were detected in total precipitation or in the frequency and duration of precipitation extremes. [ABSTRACT FROM AUTHOR]

Seasonal rainfall in the Caribbean Basin is known to be modulated by sea surface temperature anomalies (SSTAs) in the Atlantic and Pacific Oceans, and particularly those in the Equatorial Pacific and Atlantic and the Tropical North Atlantic. However, little is known about how these major oceans influence the seasonal precipitation of individual small island states within the region as climate variability at the island-scale may differ from the Caribbean as a whole. Correlation and composite analyses were determined using monthly rainfall data for the southernmost island of the Caribbean, Trinidad, and an extended area of global SSTAs. In addition to the subregions that are known to modulate Caribbean rainfall, our analyses show that sea surface temperatures (SSTs) located in the subtropical South Pacific, the South Atlantic, and the Gulf of Mexico also have weak (r2 < 0.5) yet significant influences on the islands' early rainy season (ERS) and late rainy season (LRS) precipitation. Composite maps confirm that the South Pacific, South Atlantic, and the Gulf of Mexico show significant SSTAs in December–January–February (DJF) and March–April–May (MAM) prior to the ERS and the LRS. Statistical models for seasonal forecasting of rainfall at the island scale could be improved by using the SSTAs of the Pacific and Atlantic subregions identified in this study. [ABSTRACT FROM AUTHOR]

The precipitation diurnal cycle (PDC) varies with the season and location. Its link to large-scale weather circulations has been studied in different regions. However, comparable information is lacking for Central Europe. Two decades of hourly precipitation data were combined with records of objective weather patterns over Germany, focusing on the general atmospheric wind directions (WD). The PDC is characterized by the frequency and the average amount of hourly precipitation. The precipitation frequency generally has two peaks: one in the morning and the other in the afternoon. The morning peak of the precipitation amount is small compared to that of the afternoon peak. Remarkably, WD has a prominent influence on the PDC. Days with southwesterly WD have a high afternoon peak and a lower morning peak, while days with northwesterly WD have a high morning peak and a lower afternoon peak. Furthermore, the seasonal variations of PDC are dominated by the seasonal frequency of WD classes. This study presents a general overview of the PDC in Germany with regard to its variation with seasonality, geographical location, elevation, and WD. [ABSTRACT FROM AUTHOR]

The Southeastern Tibetan Plateau (SETP) and the Middle Yangtze River Basin (MYRB) show a large difference in their levels of precipitation, despite the fact that they are located within the same latitude band. The annual precipitation in the MYRB is much higher than in the SETP. Precipitation has decreased in the past three decades in both regions. To clarify the difference in precipitation and its changes between these two regions in recent decades, a quasi-isentropic backward trajectory (QIBT) model is used to track the evaporative source with the ERA-Interim reanalysis as the baseline. The wet seasons (from April to September) over the period of 1982–2011 were analyzed. Evaporative sources were divided into an oceanic portion and a terrestrial portion, in which local recycling was included. Our conclusions are as follows. A terrestrial evaporative source, including a neighboring terrestrial land source and local source, dominates both regions, although the summer monsoon regulates precipitation in the wet season. The local precipitation recycling ratio is 35% in the SETP and 29% in the MYRB. The oceanic evaporative source in the MYRB is five times larger than that in the SETP. The decrease in the oceanic evaporative source in the Indian Ocean is responsible for the decrease in precipitation in the SETP. In the MYRB, decreases in neighboring terrestrial sources dominate the precipitation decline. Regardless of the decreases in the remote oceanic or neighboring terrestrial evaporative sources, the local recycling ratio increased in both regions. [ABSTRACT FROM AUTHOR]

Using composite, regular, and partial regression analyses in the six consecutive seasons from spring of the El Niño–Southern Oscillation (ENSO)-/Indian Ocean Dipole (IOD)-developing year through summer following the ENSO/IOD mature phase, the individual and combined impacts of El Niño and positive Indian Ocean Dipole (pIOD) on the evolution of precipitation in China are diagnosed for the period 1950–2013. It is shown that the seasonal responses of precipitation in China to El Niño and pIOD events, and their relationship with the large-scale atmospheric circulations, differ from one season to another. For the pure El Niño years, there is a seasonal reversal of precipitation over southeastern and northwestern China, with deficient precipitation occurring in these two regions before the onset of anomalous wet conditions in the developing autumn. Meanwhile, North China tends to be drier than normal in the developing seasons, but wetter than normal in the decaying seasons. For the pure pIOD events, southern China suffers a precipitation deficit (surplus) in the developing spring (summer and autumn). Furthermore, both North China and northwestern China experience excessive precipitation in the developing autumn and decaying summer. In addition, there is reduced precipitation in northeastern China during both the developing and decaying summers, whereas increased precipitation occurs in the developing autumn and decaying winter. For the combined years, southern China experiences enhanced moisture supply and suffers from increased precipitation from the developing summer through the subsequent spring, but reduced precipitation in the developing spring and decaying summer. Similar to the pure El Niño, northwestern (North) China becomes wetter than normal after the developing summer (autumn) in the combined years. In general, the ENSO/IOD-related precipitation variability could be explained by the associated anomaly circulations. [ABSTRACT FROM AUTHOR]

The linkage between atmospheric blocking (blocking frequency, BF) and total monthly July precipitation in the Selenga River Basin, the main tributary of Lake Baikal, for the period 1979–2016 was investigated. Based on empirical orthogonal functions (EOF) analysis, two dominant modes of precipitation over the Selenga River Basin were extracted. The first EOF mode (EOF 1) is related to precipitation fluctuations mainly in the Mongolian part of Selenga; the second EOF mode (EOF 2)—in the Russian part of Selenga. Based on two different modes obtained, the total amount of precipitation individually for the Russian and Mongolian part of Selenga was calculated. Correlation analysis has demonstrated that precipitation over the Mongolian part of the Selenga Basin is positively correlated to blocking over Eastern Siberia/Mongolia (80–120° E, ESM-BF). Precipitation over the Russian part of the Selenga Basin is positively correlated to blocking over the Urals-Western Siberia (50–80° E, UWS-BF) and European blocking (0–50° E, E-BF). However, the linkage is not stable, and after the mid-1990s, the obtained positive correlation became insignificant. The analysis has shown that the dominance of E or ESM-blocking in July was the primary driver of the existence of two precipitation modes over the Selenga River Basin. During 1996–2016, the negative trend of time coefficients of EOF 1 and 2 for precipitation in Selenga had been observed, which was characterized by displacement of positive precipitation anomalies outside the basin. At the same time, there was a weakening of the linkage between precipitation in the Selenga Basin and blocking frequency. We have revealed two wave-like modes over Northern Eurasia and the subtropical part of Eurasia corresponding to E, ESM-blocks in 1979–1995 and 1996–2016. The change of the Northern and subtropical wave modes is one of the causes for the weakening of the linkage between atmospheric blocking and precipitation in the Selenga Basin and as a consequence decreased precipitation in the Russian and Mongolian part of Selenga during 1979–2016. [ABSTRACT FROM AUTHOR]

Hubei Province Region (HPR), located in Central China, is a concentrated area of severe convective weather. Three severe convective processes occurred in HPR were selected, namely 14–15 May 2015 (Case 1), 6–7 July 2013 (Case 2), and 11–12 September 2014 (Case 3). In order to investigate the differences between the three cases, the temporal and spatial distribution characteristics of cloud–ground lightning (CG) flashes and precipitation, the distribution of radar parameters, and the evolution of cloud environment characteristics (including water vapor (VD), liquid water content (LWC), relative humidity (RH), and temperature) were compared and analyzed by using the data of lightning locator, S-band Doppler radar, ground-based microwave radiometer (MWR), and automatic weather stations (AWS) in this study. The results showed that 80% of the CG flashes had an inverse correlation with the spatial distribution of heavy rainfall, 28.6% of positive CG (+CG) flashes occurred at the center of precipitation (>30 mm), and the percentage was higher than that of negative CG (−CG) flashes (13%). Moreover, the quantity of thunderstorm cells in Case 1 was more than other cases, the peak time of +CG flashes was prior to that of total CG flashes in Case 2 and Case 3, and the time of +CG flashes' peak in Case 2 was prior to that of precipitation at about 2 h. Based on the analysis of the cloud environment, there are three main reasons for the differences of CG flashes and precipitation. Firstly, the structure of the LWC vertical profile and the height of the LWC peak are different, and high LWC makes it difficult for the collision of ice particles to generate electricity. Secondly, the differences between convective available potential energy (CAPE), precipitation, and CG flashes is caused by the sudden increase of VD from 1.5 km to 3 km, and thirdly, the production of CG flashes is very sensitive to RH at the surface layer and the total CG flashes increase as the RH increasing. [ABSTRACT FROM AUTHOR]

The raindrop size distribution (DSD) is fundamental for quantitative precipitation estimation (QPE) and in numerical modeling of microphysical processes. Conventional disdrometers cannot capture the small drop end, in particular the drizzle mode which controls collisional processes as well as evaporation. To overcome this limitation, the DSD measurements were made using (i) a high-resolution (50 microns) meteorological particle spectrometer to capture the small drop end, and (ii) a 2D video disdrometer for larger drops. Measurements were made in two climatically different regions, namely Greeley, Colorado, and Huntsville, Alabama. To model the DSDs, a formulation based on (a) double-moment normalization and (b) the generalized gamma (GG) model to describe the generic shape with two shape parameters was used. A total of 4550 three-minute DSDs were used to assess the size-resolved fidelity of this model by direct comparison with the measurements demonstrating the suitability of the GG distribution. The shape stability of the normalized DSD was demonstrated across different rain types and intensities. Finally, for a tropical storm case, the co-variabilities of the two main DSD parameters (normalized intercept and mass-weighted mean diameter) were compared with those derived from the dual-frequency precipitation radar onboard the global precipitation mission satellite. [ABSTRACT FROM AUTHOR]

The aim of this study is to assess the sensitivity of convective precipitation modelled by the regional climate model MAR (Modèle Atmosphérique Régional) over 1987–2017 to four newly implemented convective schemes: the Bechtold scheme coming from the MESO-NH regional model and the Betts-Miller-Janjić, Kain-Fritsch and modified Tiedtke schemes coming from the WRF regional model. MAR version 3.9 is used here at a resolution of 10 km over a domain covering Belgium using the ERA-Interim reanalysis as forcing. The simulated precipitation is compared against SYNOP and E-OBS gridded precipitation data. Trends in total and convective precipitation over 1987–2017 are discussed. None of the MAR experiments compares better with observations than the others and they all show the same trends in (extreme) precipitation. Over the period 1987–2017, MAR suggests a significant increase in the mean annual precipitation amount over the North Sea but a significant decrease over High Belgium. [ABSTRACT FROM AUTHOR]

The satellite-derived HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) precipitation estimates have been validated against in-situ precipitation measurements from optical disdrometers, available from OceanRAIN (Ocean Rainfall And Ice-phase precipitation measurement Network) over the open-ocean by applying a statistical analysis for binary estimates. In addition to using directly collocated pairs of data, collocated data were merged within a certain temporal and spatial threshold into single events, according to the observation times. Although binary statistics do not show perfect agreement, simulations of areal estimates from the observations themselves indicate a reasonable performance of HOAPS to detect rain. However, there are deficits at low and mid-latitudes. Weaknesses also occur when analyzing the mean precipitation rates; HOAPS underperforms in the area of the intertropical convergence zone, where OceanRAIN observations show the highest mean precipitation rates. Histograms indicate that this is due to an underestimation of the frequency of moderate to high precipitation rates by HOAPS, which cannot be explained by areal averaging. [ABSTRACT FROM AUTHOR]

This work documents the main features of six subtropical cyclones occurred between the years 2010 and 2016 over the southwestern South Atlantic Ocean, near the Brazilian coast, which received names (with the exception of one) from the Brazilian Navy Hydrographic Center. The fine-resolution ERA5 reanalysis and rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) were used to describe the synoptic environment and the adverse weather conditions during the six events. The support of a small-amplitude trough at mid-levels or a cut-off low, weak vertical wind shear, and moisture flux convergence are the main features contributing to the subtropical cyclogenesis at the surface. On the other hand, sea surface temperature (SST) presents a secondary contribution since the cyclones develop over the ocean with a wide range of SST values (from 22.5 °C to 28.6 °C in the initial phase of cyclones). The six subtropical cyclones are less deep in the atmosphere column than the tropical ones and, unlike the extratropical cyclones, they have little or no westward tilt with an increase in height. The studied subtropical cyclones produced adverse weather conditions such as (a) strong winds (reaching 17 m·s−1 at 10 m high) for a long period occurring east/southeastward of the cyclone center, and (b) high amounts of rainfall along the southeastern coast of Brazil, where the accumulated rainfall varied between 170 to 350 mm, being in most cases higher than the monthly climatology. Over the continent, the Brazilian states of Rio de Janeiro and Espírito Santo were the most affected by the intense rainfall associated with the cyclones. [ABSTRACT FROM AUTHOR]

Projected increase in frequency and severity of extreme events are important threat brought by climate change. Thus, there is a need to understand the dynamics and magnitude of climate extreme at local and regional level. This study examines the patterns of annual trends and changes of extreme daily temperature and precipitation in Myanmar for the period of 1981 to 2015 using the RClimDex 1.1 software. The trends of maximum and minimum temperature show significant warming trends (p < 0.001) across Myanmar. From 2009 to 2015, the maximum temperature anomaly has continuously increased by 0.5 °C for all years except 2011. The larger rise in both maximum and minimum temperature observed after 2000 suggests that, overall, days and nights are becoming hotter for the entirety of Myanmar over this recent period. Furthermore, our works also show that the temperature extreme indices of warm days and warm nights have increased, whereas the frequency of cool days and cool nights have decreased. Our analysis also reveals that increasing trends in precipitation anomaly were not significant during 1981–2015. On the contrary, slight increasing trends towards wetter conditions were observed with a rate of 76.52 mm/decade during the study period. The other precipitation extreme indicators—namely, annual total precipitation (PRCPTOT), heavy precipitation days (R20mm), extreme wet days precipitation (R99p), and consecutive wet days (CWD)—are consistent with warming trends. Additionally, the relationship between inter-annual variability in the climate extremes indices and Oceanic Niño Index (ONI) patterns was also examined with a focus on the influence of the El Niño-Southern Oscillation (ENSO) phenomenon. [ABSTRACT FROM AUTHOR]

The tropical, oceanic mean relationship between column relative humidity and precipitation is highly non-linear. Mean precipitation remains weak until it rapidly picks up and grows at high column humidity. To investigate the origin of this relationship, a Lagrangian cloud tracking code, RAMStracks, is developed, which can follow the evolution of clouds. RAMStracks can record the morphological properties of convective clouds, the meteorological environment of clouds, and their effects. RAMStracks is applied to a large-domain radiative convective equilibrium simulation, which produces a complex population of convective clouds. RAMStracks records the lifecycle of 501 clouds through growth, splits, mergers, and decay. The mean evolution of all these clouds is examined. It is shown that the column humidity evolves non-monotonically, but that lower-level and upper-level contributions to total moisture do evolve monotonically. The precipitation efficiency of tropical storms tends to increase with cloud age. This is confirmed using a prototype testing method. The same method reveals that different tracked clouds with similar initial conditions evolve in very different ways. This makes drawing general conclusions from individual storms difficult. Finally, the causality of the precipitation-column humidity relationship is examined. A Granger Causality test, as well as regressions, suggest that moisture and precipitation are causally linked, but that the direction of causality is ambiguous. Much of this link appears to come from the lower-level moisture's contribution to column humidity. [ABSTRACT FROM AUTHOR]

Understanding long-term changes in precipitation and temperature patterns is important in the detection and characterization of climate change, as is understanding the implications of climate change when performing impact assessments. This study uses a statistically robust methodology to quantify long-, medium- and short-term changes for evaluating the degree to which climate change and urbanization have caused temporal changes in precipitation and temperature in South Korea. We sought to identify a fingerprint of changes in precipitation and temperature based on statistically significant differences at multiple-timescales. This study evaluates historical weather data during a 40-year period (1973–2012) and from 54 weather stations. Our results demonstrate that between 1993–2012, minimum and maximum temperature trends in the vicinity of urban and agricultural areas are significantly different from the two previous decades (1973–1992). The results for precipitation amounts show significant differences in urban areas. These results indicate that the climate in urbanized areas has been affected by both the heat island effect and global warming-caused climate change. The increase in the number of rainfall events in agricultural areas is highly significant, although the temporal trends for precipitation amounts showed no significant differences. Overall, the impacts of climate change and urbanization in South Korea have not been continuous over time and have been expressed locally and regionally in terms of precipitation and temperature changes. [ABSTRACT FROM AUTHOR]

We have produced a global ensemble mean of the four third-generation climate reanalysis models for the years 1981–2010. The reanalysis system models used in this study are National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis Interim (ERA-I), Japan Meteorological Agency (JMA) 55-year Reanalysis (JRA-55), and National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA). Two gridded datasets are used as a baseline, for temperature the Global Historical Climatology Network (GHCN), and for precipitation the Global Precipitation Climatology Centre (GPCC). The reanalysis ensemble mean is used here as a comparison tool of the four reanalysis members. Meteorological fields investigated within the reanalysis models include 2-m air temperature, precipitation, and 500-hPa geopotential heights. Comparing the individual reanalysis models to the ensemble mean, we find that each perform similarly over large domains but exhibit significant differences over particular regions. [ABSTRACT FROM AUTHOR]

Plants grown in arable soils mainly use rainwater stored in the soil at matric potential between −10 kPa and −100 kPa, which corresponds to the readily available soil water (RASW). RASW in the 100-cm soil layer of Polish arable soils is relatively low and ranges from about 12 mm in mountain clay soils up to 75 mm in black earths, which, at an average daily evapotranspiration of 3.8 mm·day−1 and spatio—temporal variability of precipitation, determines water scarcity of crop plants. The aim of the study is to estimate the values and the frequency of critical rainfall which ensures that soil water is kept in the range of readily available to plants and prevents water shortages for plants in arable soils. In order to meet this condition, the decade (10-day) sums of this precipitation, included in the ranges 16–27, 22–31, 26–35 and 33–39 mm, occur in 20.8, 13.4, 11.3 and 5.9%, respectively, of the decades of the vegetation period (April to September). Maps of critical rainfall spatial diversity in the background of the actual soil cover in Poland were generated. They may be useful for preliminary, estimated operational planning of irrigation needs. [ABSTRACT FROM AUTHOR]