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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]

Abstract In this paper, we analyzed the effect of SST on the precipitation of coastal areas of the eastern China. The relationship between the precipitation and SST of different seasons based on CMDC's monthly precipitation data and NOAA's SST data from 1979 to 2016 was calculated. Analysis on the links between precipitation and SST has shown a significant correlation in winter and spring, with three positive strong oceanic signals and two negatively correlated sea areas. Meanwhile, the precipitation and SST of highly correlated regions have increased during the past 38 years. Considering the seasonal variation, precipitation presents upward trend in summer and winter with appreciable seasonal variations. For one of the highly related areas, such as the East China Sea (ECS) and the north of Philippine Sea (PS), the SST there has been increased in all four seasons. Spectral analysis also shows that the precipitation and the MEI have the same cycles about 3–5 years. Moreover, lead-lag analysis between precipitation time-series and three climate indexes (Niño 1 + 2 SST index, Niño 3 SST index and SIOD SST index) were applied. The results show that when the SSTs lead 2 to 4 months, they are highly related to the precipitation in the coastal areas of the eastern China. Highlights • Precipitation and SST concentrations in the study area show a significant correlation in winter and spring; • Precipitation and SST experienced different rises from 1979–2016. Precipitation presents an upward trend in summer and winter; • In SST correlated areas, they all had been increasing during the period of 1979–2016 about 1.1 °C on average; • Precipitation and three index (Niño 1 + 2 SST index, Niño 3 SST index, and SIOD SST index) indicated lead-lag relationship; • When Niño 1 + 2 SST index leads precipitation by three months, the two variables are significant positive correlated. [ABSTRACT FROM AUTHOR]

This paper investigates the annual and seasonal precipitation variability at 20 stations over upper Indus River basin (UIRB) by using an innovative trend analysis (ITA) method, Mann-Kendall (MK) and Sen's slope estimator tests. Moreover, the annual precipitation time series is investigated for five precipitation intensities i.e. light, low, moderate, high and heavy; and on a seasonal scale for extreme values i.e. light and heavy precipitation intensities. Annual precipitation showed an increasing trend at four stations in the northeast region and a decreasing trend at two stations in the southeast region of UIRB. On a seasonal scale, the results showed that Garidopatta, Peshawar, Astore and Gupis stations are more sensitive to seasonal precipitation variabilities. Changes in heavy precipitation (> 90th percentile) are found more severe in winter and summer seasons in the northern regions suggesting a probable flooding aggravation. However, a reduction in flooding event observed during the spring season in the southern regions of the UIRB indicating a shift in the precipitation regime from south to north. The results of light precipitation (< 10th percentile) intensity showed that winter and spring seasons are more vulnerable to the occurrence of prolonged drought events. Moreover, ITA method has the advantage of detecting the sub-trends in the precipitation series because of its ability to present the results in graphical format. The results of this study could help to understand seasonal and annual precipitation variability over UIRB and will have imperative insinuations for further studies. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP), being an average of surpassing 4000 m above sea level and around 2.5 × 10 6  km 2 , is the highest and largest plateau in the world and also called as the “Third Pole”. Due to its elevated land surface and complex terrain, the TP is subjected to combined regulations of multiple climate systems and associated large-scale atmospheric circulations. In this paper, we comprehensively review the recent studies of atmospheric moisture transport versus precipitation across the TP, with the attempt to link the two, which did not receive much attention previously. This review focuses on the atmospheric moisture transport and associated circulation patterns in this region, widely adopted approaches to identify the atmospheric moisture transport, qualitative and quantitative analyses for the role of water vapor transport on the precipitation, as well as the internal physical mechanism between atmospheric moisture transport and precipitation over the TP. Moreover, directions of future research are discussed based on the following aspects, which include 1) proposing an integrated statistical-physical framework for demonstrating the influence of atmospheric moisture transport and associated circulation patterns on the precipitation, especially the extremes, in the high-cold mountainous region; 2) quantifying the contribution of atmospheric water vapor from the surrounding sources as well as the local moisture recycling on the TP's precipitation; 3) providing higher quality data for atmospheric water vapor and precipitation; 4) emphasizing on the physical mechanism sustaining the atmospheric moisture transport as well as its potential influence on the extreme precipitation, including amount, frequency, intensity and duration. It is expected that this review will be beneficial for exploring the linkage between atmospheric moisture transport versus precipitation across the TP. [ABSTRACT FROM AUTHOR]

In the first part of this paper, monthly precipitation data from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission 3B42 algorithm Version 7 (TRMM-3B42V7) are evaluated over Iran using the Generalized Three-Cornered Hat (GTCH) method which is self-sufficient of reference data as input. Climate Data Unit (CRU) is added to the GTCH evaluations as an independent gauge-based dataset thus, the minimum requirement of three datasets for the model is satisfied. To ensure consistency of all datasets, the two satellite products were aggregated to 0.5° spatial resolution, which is the minimum resolution of CRU. The results show that the PERSIANN-CDR has higher Signal to Noise Ratio (SNR) than TRMM-3B42V7 for the monthly rainfall estimation, especially in the northern half of the country. All datasets showed low SNR in the mountainous area of southwestern Iran, as well as the arid parts in the southeast region of the country. Additionally, in order to evaluate the efficacy of PERSIANN-CDR and TRMM-3B42V7 in capturing extreme daily-precipitation amounts, an in-situ rain-gauge dataset collected by the Islamic Republic of the Iran Meteorological Organization (IRIMO) was employed. Given the sparsity of the rain gauges, only 0.25° pixels containing three or more gauges were used for this evaluation. There were 228 such pixels where daily and extreme rainfall from PERSIANN-CDR and TRMM-3B42V7 could be compared. However, TRMM-3B42V7 overestimates most of the intensity indices (correlation coefficients; R between 0.7648–0.8311, Root Mean Square Error; RMSE between 3.29mm/day-21.2mm/5day); PERSIANN-CDR underestimates these extremes (R between 0.6349–0.7791 and RMSE between 3.59mm/day-30.56mm/5day). Both satellite products show higher correlation coefficients and lower RMSEs for the annual mean of consecutive dry spells than wet spells. The results show that TRMM-3B42V7 can capture the annual mean of the absolute indices (the number of wet days in which daily precipitation > 10 mm, 20 mm) better than PERSIANN-CDR. The results of daily evaluations show that the similarity of Empirical Cumulative Density Function (ECDF) of satellite products and IRIMO gauges daily precipitation, as well as dry spells with different thresholds in some selected pixels (include at least five gauges), are significant. The results also indicate that ECDFs become more significant when threshold increases. In terms of regional analyses, the higher SNR of the products on monthly (based on the GTCH method) and daily evaluations (significant ECDFs) is mostly consistent. [ABSTRACT FROM AUTHOR]

Abstract: A Local Area Weather Radar (LAWR) is an X-band weather radar developed to meet the needs of high resolution rainfall data for hydrological applications. The LAWR system and data processing methods are reviewed in the first part of this paper, while the second part of the paper focuses on calibration. The data processing for handling the partial beam filling issue was found to be essential to the calibration. LAWR uses a different calibration process compared to conventional weather radars, which use a power-law relationship between reflectivity and rainfall rate. Instead LAWR uses a linear relationship of reflectivity and rainfall rate as result of the log transformation carried out by the logarithmic receiver as opposed to the linear receiver of conventional weather radars. Based on rain gauge data for a five month period from a dense network of nine gauges within a 500×500m area and data from a nearby LAWR, the existing calibration method was tested and two new methods were developed. The three calibration methods were verified with three external gauges placed in different locations. It can be concluded that the LAWR calibration uncertainties can be reduced by 50% in two out of three cases when the calibration is based on a factorized 3 parameter linear model instead of a single parameter linear model. [Copyright &y& Elsevier]

Abstract: This paper presents first exploratory results and analyses performed on a 30-year (1978–2007) homogeneous precipitation database that has been created for the Calabria peninsula, southern Italy. The database consists of complete time series of daily values of precipitation from 88 stations distributed over the region. The database temporal resolution is one day while its spatial resolution is about 10 km. Calabria offers an interesting scenario for mesoclimatic studies in spatial and temporal rainfall variability. The region is located in the Central Mediterranean Basin, which has a strong seasonal variability that mirrors in large precipitation differences among seasons. The complex orography of the region leads to different exposures of the territory to the rain-bearing air masses and large differences in rainfall can occur in few tens of kilometers. Different kinds of Mediterranean storms are important for Calabria: a) storms originating in the lee of the Alps; b) storms that enter the Basin or develop in the western Mediterranean (Gulf of Lyon, Rhone valley, Iberia, Gibraltar); c) storms from northern Africa; d) storms moving over the central Mediterranean from Balkans and eastern Europe. Again, their interaction with local orography determines complex rainfall patterns and variability. In this paper, the maps of average values of precipitation, rain frequency, rain rate, persistence of rainfall and length of dry periods are presented. Precipitation spatial structure shows that the orography and the sea have a major role, while the seasonal dependence of rainfall unequivocally reveals the influence of the synoptic scale conditions. A large number of cast-studies of heavy precipitation events have been investigated in the past and several of them refer to the east side of Calabria. The results shown here confirm this issue in a climatological sense: despite the fact that yearly precipitation is larger on the west side of the peninsula, most intense rainstorms affect mainly the east side, which is favorably exposed to these storms. The current database represents a foundation for further investigations. [Copyright &y& Elsevier]

Abstract: The WMO Field Intercomparison of Rainfall Intensity (RI) Gauges started on October, 1st 2007 at Vigna di Valle (Italy) and was concluded in May 2009. Those catching type instruments, out of the selected rain gauges based on various measuring principles, and the four rain gauges selected as reference instruments to be installed in a pit, were preliminarily calibrated in the laboratory before their final installation at the Field Intercomparison site. The recognized WMO laboratory at the University of Genoa was involved in this task, using the same standard tests adopted for the previously held WMO Laboratory Intercomparison of RI gauges. Further tests were performed to investigate the one-minute performance of the involved instruments. The present paper deals with basically Tipping-Bucket Rain gauges (TBRs) and Weighing Gauges (WGs), using results from tests performed under constant flow rates in laboratory conditions. The objective of this initial phase of the Intercomparison was to single out the counting errors associated with each instrument, so as to help the understanding of the measured differences between instruments in the field during the second phase. Results and comments on the preliminary laboratory calibration exercise are reported in this paper together with their implications for the analysis of the outcome of the Intercomparison in the Field. [Copyright &y& Elsevier]

Abstract: The hydro-meteorological evaluation of a flood event in July 1997 (the Odra flood in Central Europe) demonstrated that new procedures to estimate design floods for the reservoir outflow structures in the Czech Republic (CR) were needed. Therefore, the techniques of the estimation of Probable Maximum Precipitation (PMP) were developed in a national research project (1998–2000), and the activity focused on the improvement of the area related PMP estimates was going on within a present national project. In the frame of the evaluation of the next extreme precipitation event in August 2002 (the Labe flood in the CR and Germany), we compared the catchments related precipitation with the PMP estimates. In this paper, an outline of the PMP estimation techniques is given and the use of data from the Czech gauges is described, the aim being the statistical derivation of the point and area PMP estimates for precipitation duration of 1 to 5 days. The use of radar data in assessing the maximized area reduction factor is discussed and the relationship resulting from the radar measurements over the CR territory is presented. An evaluation of the radar-based area rainfall enabled us to transform the point PMP to the area PMP estimate designed for the river basins in CR. In the last part of the paper, the results obtained by comparing the rainfalls in 1997 and 2002 flood events with the PMP estimates are presented. The comparison showed that the maximum area rainfalls over small Czech catchments (the 3rd order river basins) did not exceed 63% of the corresponding PMP values. [Copyright &y& Elsevier]

A measurement scheme aimed at investigating precipitation properties based on collocated disdrometer and profiling instruments is used in many experimental campaigns. Raindrop size distribution (RSD) estimated by disdrometer is referred to the ground level; the collocated profiling instrument is supposed to provide complementary estimation at different heights of the precipitation column above the instruments. As part of the Special Observation Period 1 of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, conducted between 5 September and 6 November 2012, a K-band vertically pointing micro rain radar (MRR) and a 2D video disdrometer (2DVD) were installed close to each other at a site in the historic center of Rome (Italy). The raindrop size distributions collected by 2D video disdrometer are considered to be fairly accurate within the typical sizes of drops. Vertical profiles of raindrop sizes up to 1085 m are estimated from the Doppler spectra measured by the micro rain radar with a height resolution of 35 m. Several issues related to vertical winds, attenuation correction, Doppler spectra aliasing, and range-Doppler ambiguity limit the performance of MRR in heavy precipitation or in convection, conditions that frequently occur in late summer or in autumn in Mediterranean regions. In this paper, MRR Doppler spectra are reprocessed, exploiting the 2DVD measurements at ground to estimate the effects of vertical winds at 105 m (the most reliable MRR lower height), in order to provide a better estimation of vertical profiles of raindrop size distribution from MRR spectra. Results show that the reprocessing procedure leads to a better agreement between the reflectivity computed at 105 m from the reprocessed MRR spectra and that obtained from the 2DVD data. Finally, vertical profiles of MRR-estimated RSDs and their relevant moments (namely median volume diameter and reflectivity) are presented and discussed in order to investigate the microstructure of rain both in stratiform and convective conditions. [ABSTRACT FROM AUTHOR]

The assessment of future precipitation variations prevailing in an area is essential for the research regarding climate and climate change. The current paper focuses on 3 selected areas in Greece that present different climatic characteristics due to their location and aims to assess and compare the future variation of annual and seasonal precipitation. Future precipitation data from the ENSEMBLES anthropogenic climate-change (ACC) global simulations and the Climate version of the Local Model (CLM) were obtained and analyzed. The climate simulations were performed for the future periods 2021–2050 and 2071–2100 under the A1B and B1 scenarios. Mann–Kendall test was applied to investigate possible trends. Spatial distribution of precipitation was performed using a combination of dynamic and statistical downscaling techniques and Kriging method within ArcGIS 10.2.1. The results indicated that for both scenarios, reference periods and study areas, precipitation is expected to be critically decreased. Additionally, Mann–Kendall test application showed a strong downward trend for every study area. Furthermore, the decrease in precipitation for the Ardas River basin characterized by the continental climate will be tempered, while in the Sperchios River basin it will be smoother due to the influence of some minor climatic variations in the basins' springs in the highlands where milder conditions occur. Precipitation decrease in the Geropotamos River basin which is characterized by Mediterranean climate will be more vigorous. B1 scenario appeared more optimistic for the Ardas and Sperchios River basins, while in the Geropotamos River basin, both applied scenarios brought similar results, in terms of future precipitation response. [ABSTRACT FROM AUTHOR]

Systematic high quality oceanic in-situ precipitation measurements are requested on an international science level and are essential for improved understanding and validation of hydrological processes in satellite, re-analysis and model data. OceanRAIN, the shipboard “Ocean Rainfall And Ice-phase precipitation measurement Network” for surface validation is, to date, the only systematic long-term disdrometer-based oceanic shipboard precipitation data collection effort to establish a comprehensive statistical basis of precipitation for all climate related hotspots over the global oceans. OceanRAIN utilizes automated disdrometer systems (ODM470) capable of measuring precipitation occurrence, intensity and accumulation and discriminates for rain, snow and mixed-phase precipitation through minute-based particle size distributions. The ODM470 was especially designed for shipboard operation under high and frequently varying wind speeds and rough sea states. This paper provides an overview on the OceanRAIN project, the instrumentation, algorithms, methodology, and data products. The procedure of the data processing chain is outlined, including calibration, shipboard operation, data ingest and quality control. The selected research ships do not circumvent high impact weather, allowing for a collection of the full precipitation spectrum including extremes. By October 2014 the fast growing OceanRAIN database comprised more than 3.7 million minutes of precipitation measurements (including true zeros) since its start in 2010. OceanRAIN aims at increasing knowledge about oceanic precipitation, improving error characterization of GPM (Global Precipitation Measurement) era precipitation retrievals, adding to the continual improvement of the satellite retrieval algorithms, as well as benchmarking existing satellite-based climatologies, re-analysis and model data. The accumulating data volume can be utilized for statistical and process study applications on different temporal and spatial scales, microphysical studies of rain and snow formation, and yields insight to the point-to-area problem of precipitation. Information on OceanRAIN including data products is available via http://www.oceanrain.org . [ABSTRACT FROM AUTHOR]

This paper examines differences between Version 6 (V6) and Version 7 (V7) 3-hourly TRMM (Tropical Rainfall Measuring Mission) Multi-Satellite Precipitation Analysis (TMPA 3B42) research products in JJA (June, July and August) and DJF (December, January and February) over a 13-year period from 1998 to 2010 on a global scale. Different surface types and rain regimes are considered in the comparison. The study finds that more rain events are found in V7 than those in V6 in both JJA and DJF, especially over oceans. Overall, both versions show a good agreement in moderate and heavy rain regimes. High Pearson’s correlation coefficients are found in tropical rain band regions. Histograms of both versions are very similar; however higher frequencies of rain events are found in V7 in light rain regime, especially over oceans, than those in V6. For light rain, rainfall estimates in V6 are less than those in V7 over land and oceans in both seasons. For moderate rain, rainfall estimates in V6 are larger than those in V7 over land in most years. Over oceans, it is a mixed situation in which V6 > V7 for some years and V6 < V7 for the other years. For heavy rain, rainfall estimates in V6 are larger than those in V7 throughout all JJA and DJF seasons for both land and oceans, which is also shown in a case study. Large variance in the individual differences is found in light rain and less in heavy rain. No apparent trends are observed. For light rain, all statistics support that there is an uncertainty issue in both versions. [ABSTRACT FROM AUTHOR]

This paper describes the relationships between rainfall in Spain (1961–2010) and four teleconnection patterns on three time scales (monthly, seasonal and annual) using data from 144 meteorological stations. Spearman's test was used to carry out partial correlations, and spatial distribution maps of the correlation coefficients were generated with kriging method. We regionalise the study area into homogeneous areas containing weather stations with a similar precipitation response to the patterns. The links between precipitation and the NAO, AO and EA are generally positive in the east and negative in the west of Spain, whereas WeMO correlates positively in the north and negatively in the rest. As a general result, the winter months and winter season show the highest percentage of weather stations with statistically significant correlations. Spearman coefficients of up to 0.62 were found for the NAO, AO and EA. WeMO strongly correlates (values up to 0.55) from October to April. Five areas have been defined: centre/southwest, northwest, north, northeast, and southeast. The mode which best explains rainfall in the two western areas is the NAO; in the north, the WeMO exerts a notable influence; EA correlates better with precipitation in the two eastern zones, especially in spring, autumn and part of winter. They are better controllers of rainfall in these areas than in the whole of the study area. [ABSTRACT FROM AUTHOR]

As high-resolution climate models become increasingly complex, it should be carefully assessed to what extent the improved physics in such models justifies the large computational cost that the complexity imposes. This paper presents a detailed sensitivity study of convective precipitation characteristics to the number of prognostic moments in bulk microphysics schemes using a high-resolution convection-resolving climate model. It is shown that 1-moment and 2-moment microphysics schemes produce more similar surface precipitation characteristics for a composite of 20 real-case convective simulations in Belgium than for many idealized studies conducted before. In the baseline 2-moment scheme, size sorting of particles is counteracted by collisional drop breakup to produce mean drop sizes that are similar to those in the 1-moment version of the scheme. Hence, fallout, evaporation and surface rain rates are very similar between the two versions of the scheme. Conversely, larger sensitivities of precipitation extremes were found to the treatment of drop breakup and the shape of the particle size distributions. Consistent with previous studies, domain-averaged and peak precipitation increased monotonically with increasing breakup equilibrium diameter Deq. Further, it is shown that a negative exponential size distribution results in excessive radar reflectivities for light rain rates. Surface precipitation and the joint distribution of reflectivity and rain rate are best reproduced by a 2-moment version of the scheme that applies gamma distributions with a diagnostic shape parameter for all particles and a large Deq. However, given the large sensitivities and uncertainties associated with collisional drop breakup and size sorting, it is likely that the full potential of improved physics in a 2-moment scheme will remain underexposed as long as these processes are not better understood. [ABSTRACT FROM AUTHOR]

Abstract: Currently, several satellite missions are employing X-band synthetic aperture radars (SAR) with polarimetric capabilities. In images collected over land by X-band SAR, precipitation results mainly in evident attenuation of the surface returns. Effects of precipitation in polarimetric SAR images and how to exploit them for precipitation studies are emerging topics of interest. This paper investigates polarimetric signatures of precipitation in images collected by the X-band SARs of the Italian Space Agency COSMO SkyMed constellation using the HH-VV alternate polarimetric mode. Analyzed images were collected in 2010 when the constellation was composed of three satellites and operated in the “tandem like” interferometric configuration, which allowed acquisition of the same scene with the same viewing geometry and a minimum decorrelation time of one day. Observations collected in Piedmont (Italy) and Tampa Bay (Florida, US) have been analyzed along with coincident observations collected by operational weather radars, used to reconstruct the component of SAR returns due to precipitation at horizontal and vertical polarization states. Different techniques are used depending on the different characteristics of terrestrial radars. SAR observations reconstructed from terrestrial measurements are in fairly good agreement with actual SAR observations. Results confirm that the attenuation signature in SAR images collected over land is particularly pronounced in the presence of precipitation cells and can be related to the radar reflectivity integrated along the same path. The difference between copolar HH and VV power measurements reveals a differential attenuation due to anisotropy of precipitation, whose range is limited when the SAR incidence angle is low. A specific feature observed in the CosmoSkyMed alternate polarization implementation is the presence of the scalloping effect, a periodic effect along the azimuth direction that cannot always be removed by standard de-scalloping techniques. Amplitude of scalloping between the two polarizations can reach a couple of decibels, close to the maximum range of differential path integrated attenuation. [Copyright &y& Elsevier]

The objective of this paper is to investigate long-term inter-annual, seasonal, and diurnal rainfall characteristics in the Southeastern United States. In order to capture precipitation features at high resolution, we use precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM); the TRMM Precipitation Radar (TPR 2A25: 0.05°×0.05°/daily) and the TRMM Multi-satellite Precipitation Analysis (TMPA 3B42: 0.25°×0.25°/3-h) datasets to create a 13-year rainfall climatology. The higher resolution climatology (2A25) displays a greater ability to capture more localized landform precipitation features when compared with 3B42. On an annual basis, the Southeastern US is characterized by a succession of cold and warm precipitation regimes. The cold season is characterized by higher rain intensity West of 82°W (roughly Atlanta, GA) and the warm season is characterized by higher rain intensity over the coastal areas. The cold/warm rainfall regime duality is modulated by local topographic characteristics that prevail along a W–E direction. During the cold season, the diurnal cycle of precipitation is characterized by a quasi-constant repartition of rain events throughout the day and an absence of land/ocean contrast. On the contrary for summertime there is a strong land/ocean signature with a predominance of late morning/early afternoon (12:00–15:00LST) rainfall over ocean and afternoon/early evening (15:00–18:00LST) precipitation events over land that account for more than 25% of the daily events along the coasts. Differences are observed for the Florida peninsula, where the diurnal cycle displays an afternoon maximum of variable intensity due to sea breeze effects regardless of the season. [ABSTRACT FROM AUTHOR]

Abstract: Microwave radiometers (MWRs) can be useful for the detection of mesoscale phenomena because they provide thermodynamic profiles in a minute time scale. These profiles are mainly used in non-precipitation conditions due to degraded accuracy of the MWR measurements in precipitation. Recently, Radiometrics Corporation used proprietary neural network methods to retrieve temperature, humidity and liquid profiles from off-zenith (15° elevation) radiometer observations to provide higher accuracy during precipitation. In this paper, using the MWR-retrieved temperature and humidity profiles with collocated radiosondes from June 2010 to September 2013 in Wuhan, the impact of precipitation on the MWR measurement accuracy as well as the effect of off-zenith neural network methods on it is investigated. In precipitation, the correlation coefficients of the MWR temperature and vapor density profiles against radiosondes are smaller than those in non-precipitation, and the bias and RMS against radiosondes also increase, especially around 2km heights. For the MWR relative humidity profile, the correlation coefficient in precipitation is obvious smaller than that in non-precipitation below 4.5km, and the bias and RMS against radiosondes are clearly larger above 5.5km. Moreover, the differences between the precipitation and non-precipitation cases mostly are statistically significant. Compared with the results of the zenith observation, the off-zenith observation makes a positive effect on reducing the impact of precipitation on the accuracy of MWR temperature and vapor density retrievals. On the whole, the MWR temperature bias and RMS against radiosondes in precipitation are reduced from 3.6 and 4.2K to 1.3 and 3.1K, respectively, and the MWR vapor density bias is also reduced from 1.10g/m3 to 0.18g/m3 with the RMS decreasing from 2.90g/m3 to 1.91g/m3. The temperature correlation coefficient between the MWR and radiosonde in precipitation is clearly improved above 3km heights, and the temperature bias and RMS are significantly reduced at most heights. For the MWR vapor density retrievals in precipitation, the correlation coefficient, bias and RMS against radiosondes are clearly improved above 2km heights. Additionally, the off-zenith observations during non-precipitation cases are also better compared to zenith observations. Therefore, off-zenith observations generally are better than zenith observations. This could be due to the fact that the off-zenith observations are more representative of the conditions in which radiosonde observations are also taken. [Copyright &y& Elsevier]

Abstract: The Water vapor Strong Lines at 183GHz (183-WSL) algorithm is a method for the retrieval of rain rates and precipitation type classification (convective/stratiform). It exploits the water vapor absorption line observations centered at 183.31GHz of the Advanced Microwave Sounding Unit module B (AMSU-B) and of the Microwave Humidity Sounder (MHS) flying on NOAA-15/-17 and NOAA-18-19/MetOp-A satellite series, respectively. The characteristics of this algorithm were described in Part I of this paper together with comparisons against analogous precipitation products. The focus of Part II is the analysis of the performance of the 183-WSL technique based on surface radar measurements. The “ground truth” dataset consists of 2years and 7months of rainfall intensity fields from the NIMROD radar network, which covers North-Western Europe. The investigation of the 183-WSL retrieval performance is based on a twofold approach: 1) the dichotomous statistic is used to evaluate the capabilities of the method to identify rain and no-rain clouds and 2) the accuracy statistic is applied to quantify the errors in the estimation of rain rates. The results reveal that the 183-WSL technique shows good skills in the detection of rain/no-rain areas and in the quantification of rain rate intensities. The categorical analysis shows annual values of the Probability Of Detection (POD), False Alarm Ratio (FAR) and Hanssen–Kuiper discriminant (HK) indices varying in the range 0.80–0.82, 0.33–0.36 and 0.39–0.46, respectively. The RMSE value is 2.8mmh−1 for the whole period despite an overestimation in the retrieved rain rates. Of note is the distribution of the 183-WSL monthly mean rain rate with respect to radar: the seasonal fluctuations of the average rainfalls measured by radar are reproduced by the 183-WSL. However, the retrieval method appears to suffer during winter seasonal conditions especially when the soil is partially frozen and the surface emissivity drastically changes. This is verified by the discrepancy distribution diagrams where the 183-WSL performs better during the warm months, while during the winter time the discrepancies with radar measurements tend to maximum values. The stable behavior of the 183-WSL algorithm is demonstrated over the whole study period by an overall overestimation for rain rate intensities less than 1mmh−1. This threshold is especially crucial in wintertime when the classification of low-intensity precipitation regimes is difficult. [Copyright &y& Elsevier]

The vertically pointing Micro Rain Radar (MRR) and disdrometer (RD-80) were installed at a coastal station, Thumba (8.5°N, 76.9°E), to study the characteristics of tropical rains. This paper presents the first results from these observations over Thumba and highlights the impact of Mie-scattering corrections to the MRR data for proper estimation of the rainfall intensity. To evaluate the performance of MRR, a total number of 11 Mesoscale Convective Systems events were considered during the period September 2006 to December 2007. The uncorrected MRR shows an overestimation of rain rate and this is larger during the high rain rates. The Mie scattering corrections lead to a decrease in rain rate of the order 2%–31% and resulted in substantial improvement in the rainfall accumulation (368.69mm (before) to 302.16mm (after)). The accumulated rainfall is in good agreement with disdrometer total rainfall of 299.14mm. For the first time, the impact of Mie scattering for different rain categories has been investigated and study shows the rainfall sum significantly improved (about 22%) during the moderate and heavy rain categories whereas, it shows improvement of 11% during the light rain. These studies may be used to estimate the rain attenuation at Ka band over Indian region for different rain categories. [ABSTRACT FROM AUTHOR]

Abstract: The Arctic Oscillation (AO) has been found in previous studies to be a major synoptic factor affecting the climate of many regions in the high and mid-latitudes. This paper demonstrates the physical process by which the AO affects the climate of the Eastern Mediterranean basin, with a focus on precipitation in Israel as a case study. It is shown that a trend of increasing AO is associated with a substantial decrease of winter precipitation from the Iberian Peninsula, though Italy, Greece, Turkey and Cyprus, as well as Lebanon, Syria and also the northern parts of Israel. Winter rain is slightly increased in the southern coast of the eastern half of the Mediterranean Sea. The immediate meteorological causes are shown to be a larger northerly component of the flow over the Mediterranean Sea, associated with a decreasing relative humidity and stability, except over the southern coast, where the air mass has the longest track over the relatively warm water. We suggest here that the observed changes in air flow that drives the precipitation trends can be explained by shifts in the AO that can be partially explained by increasing greenhouses gases. Results from the IPCC multi climate models show that the AO will continue to increase during the 21st century. This increase may lead to a continuation of the trends discussed here. The importance of the analysis provided here is in pointing out the possibility that processes that have been predicted by global warming and changes in global circulation have already started to affect precipitation and major water resources in the Mediterranean basin. [Copyright &y& Elsevier]

Abstract: In this paper, MicroRadarNet, a novel micro radar network for continuous, unattended meteorological monitoring is presented. Key aspects and constraints are introduced. Specific design strategies are highlighted, leading to the technological implementations of this wireless, low-cost, low power consumption sensor network. Raw spatial and temporal datasets are processed on-board in real-time, featuring a consistent evaluation of the signals from the sensors and optimizing the data loads to be transmitted. Network servers perform the final post-elaboration steps on the data streams coming from each unit. Final network products are meteorological mappings of weather events, monitored with high spatial and temporal resolution, and lastly served to the end user through any Web browser. This networked approach is shown to imply a sensible reduction of the overall operational costs, including management and maintenance aspects, if compared to the traditional long range monitoring strategy. Adoption of the TITAN storm identification and nowcasting engine is also here evaluated for in-loop integration within the MicroRadarNet data processing chain. A brief description of the engine workflow is provided, to present preliminary feasibility results and performance estimates. The outcomes were not so predictable, taking into account relevant operational differences between a Western Alps micro radar scenario and the long range radar context in the Denver region of Colorado. Finally, positive results from a set of case studies are discussed, motivating further refinements and integration activities. [Copyright &y& Elsevier]

Abstract: Precipitation is a complex phenomenon which is characterized by a significant variability both in time and space. Conventional measurements, such those of rain gauges, can only provide a limited information of its microphysical properties and dynamical features. In this respect, disdrometer surface measurements can help in exploring the raindrop size distribution. This paper provides an overview of these observation techniques, their physical background and some recent results. Specifically, ground-based techniques to observe precipitation using surface disdrometers, multifrequency microwave radiometers and microwave polarimetric radars will be discussed and illustrated. By exploiting this remote and in-situ instrumentation, estimates of precipitation optical thickness, liquid, ice and melted hydrometeor category, and their size distribution can be obtained. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this paper is to investigate the effects of the growth of the Houston metropolitan area on the characteristics and intensity of convection and precipitation. For this purpose, we implemented the Town Energy Budget (TEB) urban model into Regional Atmospheric Modeling System (RAMS). The Landsat Thematic Mapper National Land Cover Data (NLCD) for the Houston area corresponding to the years 1992, 2001 and 2006 were used for an objective experimental design of land-use sensitivity experiments. We analyzed the impact on two distinct groups of convective cells triggered by the sea breeze circulation on August 24 2000 and compared the model simulated precipitation to RADAR data. The first group of storms occurred southwest of the city and was not influenced by the urban cloud condensation nuclei (CCN), while the second was and occurred north of the city (downwind) a few hours later. The effect of land-use on convection and precipitation was dramatic for the storms SW of the city and it was linked to a monotonic increase in the intensity of the sea breeze. The intensification of the sea-breeze circulation when using the 1992, 2001, and 2006 NLCD land use datasets generated a monotonic increase of the total precipitated volume of 9, 11, and 25%, respectively (over a run with no city). Due to increased exposure to aerosols, the upper levels of the convective cells downwind of the city were invigorated by a greater latent heat release linked to higher amounts of liquid water transported to supercooled levels. However, precipitation did not show a monotonic behavior when we varied the intensity of the urban aerosol sources. With the highest aerosol concentrations, riming growth of ice particles became so inefficient that larger amounts of condensate was transported upwards into the storm anvil, contributing to a reduction in precipitation efficiency. [Copyright &y& Elsevier]

Abstract: This review paper deals with four aspects of precipitation: measurement, remote sensing, climatology and modeling. The measurement of precipitation is summarized in terms of the instruments that count and measure drop sizes (defined as disdrometers) and the instruments that measure an average quantity proportional to the integrated volume of an ensemble of raindrops (these instruments are normally called rain gauges). Remote sensing of precipitation is accomplished with ground based radar and from satellite retrievals and these two approaches are separately discussed. The climatology of precipitation has evolved through the years from the traditional rain gauge data analyses to the more sophisticated data bases that result from a coalescence of data and information on precipitation that is available from several sources into amalgamated products. Recently, rain observations from both ground and space have been assimilated into regional and global numerical weather prediction models aiming at improved moisture analysis and better forecasts of extreme weather events. The current status and the main outstanding issues related to precipitation forecasting are discussed, providing a basic structure for research coordination aimed at the improvement of modeling, observation and data assimilation applicable to global and regional scales. [Copyright &y& Elsevier]

Abstract: The purpose of this paper is to present a rigorous derivation of a model equation system for the mass and energy open precipitating atmosphere. The derivation is based on the treatment of the atmosphere in terms of three open thermodynamic subsystems consisting of cloudy air, rain water and snow, respectively. Each of the three subsystems moves with a different velocity as caused by the different fall velocities of rain and snow in comparison to the cloudy air. A basic assumption of the model consists in the neglect of the inertia terms in the momentum equation of the falling hydrometeors. It will be shown that this simplification yields additional source terms in the budget equations of the total momentum and the total kinetic energy of the system. However, the prognostic equations for the atmospheric wind field and the corresponding kinetic energy equation remain free of these source terms. The model equations strictly conserve the total mass and energy of the system. It is concluded that the combination of the barycentric velocity of the cloudy air and the total density of the system is the best choice to describe the time evolution of the atmospheric wind field. [Copyright &y& Elsevier]

Amino acids in rain samples offer important information on their origin and roles in biogeochemical cycling. This paper describes the development and validation of an alternative analytical procedure for amino acids in atmospheric precipitation using gas chromatography coupled with mass spectrometry (GC–MS). The method detection limits (MDLs) of these amino acids ranged from 1.46 ng L−1 (Proline) to 135 ng L−1 (Arginine), which were much lower than previous methods like high-performance liquid chromatography (HPLC) and comparable to those with liquid chromatography-tandem mass spectrometry (LC-MS/MS). None of the target analytes were detected in blank samples, which was attributed to the optimized pretreatment protocol we adopted. We conclude that the GC–MS based technique developed in this study possesses advantage due to low detection limits. We further demonstrate the applicability of this method by analyzing rain samples from the background atmosphere of the Tibetan Plateau (TP). Similar relative abundances of amino acids were found in the TP rains, marine rains and Arctic ice. The correlations between FAAs and water- soluble ions in the Tibetan Plateau rainwaters showed that the FAAs were most likely originated from biomass burning. Given the similarity of snow and rain samples, our method also provides potential for the future analysis of amino acids in glacier ice cores. • A GC–MS analytical method for amino acids in precipitation was performed and optimized. • The developed method was characterized with high sensitivity and selectivity, while low blank value. • This is the first time that free amino acids were determined in the Tibetan Plateau rain. [ABSTRACT FROM AUTHOR]

The recent intensification of extreme rainfall events has the potential to aggravate the frequency and intensity of floods in urban areas and signals the urgent need for accurate and high spatiotemporal resolution precipitation data for flood monitoring and warning to alleviate the associated damages. In this context, this paper aims to statistically assess the latest Integrated Multisatellite Retrievals from Global Precipitation Measurement (IMERG) multisatellite constellation and radar quantitative precipitation estimation (QPE) products against dense rain gauge network observations under multiple temporal scales (hourly and 3-hourly) and three spatial scales (grid cumulative, regional, and grid) over the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China. The results indicate that (1) at the grid cumulative scale, QPE significantly outperforms IMERG products. The correlation coefficients of QPE (0.83 ≤ CORR ≤ 0.85) are much higher than those of IMERG products (0.35 ≤ CORR ≤ 0.56), the estimation of QPE is generally significantly underestimated (−0.23 ≤ BIAS ≤ -0.16), and the BIAS of IMERG products is larger than that of QPE (−0.24 ≤ BIAS ≤ 0.23). (2) At the regional scale, the accuracy of IMERG products has been significantly improved, with relatively high correlation coefficients (CORR≥0.8) and decreased root mean squared error (RMSE) values (1.18 mm ≤ RMSE ≤ 0.22 mm), and Taylor diagrams visually show that QPE is closer to the gauge observations than are IMERG products. (3) The evaluation results at the grid scale show that both IMERG products and QPE can accurately reflect the spatial distribution of precipitation. Among these results, the spatial distribution of QPE is the most consistent with the actual rainfall, although an obvious underestimation of rainfall occurs in areas with strong rainfall. (4) In terms of detection indicators, the three IMERG products are superior to QPE at capturing rainfall events and have more advantages over QPE in the estimation of instantaneous precipitation, especially for light rain events. However, QPE has better detection effects for rainfall events under rainstorm and heavy rainstorm events, indicating the hydrologic utility of this product. Among the three IMERG products, the IMERG Early Run (ER) product has the advantages of a short lag time and high accuracy, and it has the potential to be applied in flood forecasting. Future studies should improve IMERG algorithms and promote the application of QPE in urban rainstorm and flood research. • The quality of the IMERG products and radar quantitative precipitation estimation (QPE) is compared over the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China. • The dense rain gauge network observations are used for evaluation in the GBA. • The evaluation of multisource precipitation products under different temporal and spatial scales has different results and effects. [ABSTRACT FROM AUTHOR]