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Rationale: Accurate measurement of trace compounds in blood samples is important in clinical diagnosis and life science. Ambient ionization mass spectrometry, however, suffers from the matrix effect when dealing with complex samples such as blood. Therefore, it is important to reduce the matrix effects in blood samples. Methods: A low-cost and disposable Teflon tube was used as a platform to precipitate the protein in blood. The analytes are extracted into organic solvent, and the precipitated protein can be adsorbed by the chromatography paper inserted. Therefore, the Teflon tube after precipitation can be directly subjected to paper spray ionization mass spectrometry, achieving one-step analysis of blood. Results: High sensitivity and satisfactory stability were achieved for pharmaceuticals, acids, and endogenic metabolites in blood. The absolute signal intensities of characteristic product ions of the tested analytes were 8–20 times higher after protein precipitation than those obtained using paper spray. Detection limits and quantitative performance were evaluated for three drugs: carbamazepine, metformin, and tioconazole. In addition, the limits of detection and quantitation were improved 9–14- and 8–12-fold, respectively. Conclusions: Protein precipitation coupled to paper spray with a tube and then to mass spectrometry was successfully achieved and applied in the one-step analysis of trace compounds in blood samples. The experimental results showed that this method was sensitive, stable, convenient, and economic for the direct analysis of blood. [ABSTRACT FROM AUTHOR]

Inorganic fillers are usually used in papermaking industry to reduce production costs and enhance paper optical properties. As an attempt to improve fillers application in papermaking, carboxymethyl cellulose (CMC) and poly aluminum chloride (PAC) were used to encapsulate precipitated calcium carbonate (PCC) filler and modify its surfaces. In the first step, the optimum conditions for filler treatment (i.e. pH, CMC and PAC contents) were obtained. Through the second step, different amounts of CMCencapsulated PCC were added to fiber suspension and some hand-sheets were made. Then, the effect of modified filler addition in different levels of 20, 25, and 35% on mechanical and optical properties of paper was investigated. The PAC dosage was found to be a critical factor for effective encapsulation of PCC fillers by carboxymethyl cellulose. When the dosages of CMC and PAC were 4% and 0.8% (based on the dry weight of PCC), respectively, filler modification caused to improve significantly the retention by more than twice. Strength properties of the hand-sheets fabricated with the CMC/PAC-modified PCC were also found to be significantly better than those obtained with the unmodified PCC at similar levels of filler content. In addition, the brightness and opacity of the filled papers at 30% addition of CMC-modified fillers were strikingly enhanced to 88,45 and 77%, respectively. SEM observations of the filled papers also demonstrated that CMC-encapsulated filler particles were clustered and retained efficiently onto the fiber network. The present method for modification of PCC may provide an alternative approach to increase the filler amount in the paper structure by alleviating filler drawbacks. [ABSTRACT FROM AUTHOR]

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

Background and aims: Sorption and precipitation reactions reduce the mobility of fertilizer-applied zinc (Zn), and hence reduce availability to plants. Here, we developed a method to visualize diffusion of Zn from fertilizers. Methods: Zinc diffusion was assessed for three fertilizers in three soils of varying pH. The fertilizer (ZnSO-coated monoammonium phosphate, MAP; ZnSO-coated diammonium phosphate, DAP; or ZnSO alone) was applied in the centre of a Petri dish filled with soil. The Zn diffusion zone was visualized at various incubation times (1, 7 and 18 days) by exposing a CaCO-impregnated filter paper on the soil surface and colouring the Zn captured on the filter paper using dithizone. The extent of diffusion was also assessed through concentric sampling and chemical analysis of soil sections. Results: The visualization results agreed with the chemical analyses and demonstrated the effects of soil properties and fertilizer formulation on Zn diffusion. Combining Zn with P fertilizer restricted its diffusion, particularly with DAP fertilizer or in high pH soils. Solubility considerations indicated that this was due to the formation of Zn phosphate minerals. Conclusions: The visualization method is a useful tool for studying diffusion of Zn from spot applications and allows easy comparison in Zn diffusion between fertilizer sources. [ABSTRACT FROM AUTHOR]

During autumn 2012 and winter 2013, two Special Observation Periods (SOPs) of the Hydrological cycle in the Mediterranean Experiment (HyMeX) took place. For the preparatory studies and to support the instrument deployment during the field campaign, a dedicated version of the operational convective-scale AROME-France model was developed: the AROME-WMED model. It covers the western Mediterranean basin with a 48 h forecast range. It provided real time analyses and forecasts which were sent daily to the HyMeX operational centre to forecast high precipitation events and to help decision makers on the deployment of observation instruments. This paper presents the main features of this numerical weather prediction system in terms of data assimilation and forecast. Some specific data of the HyMeX SOP were assimilated in real time. The forecast skill of the AROME-WMED is then assessed with objective scores and compared to the operational AROME-France model, for both autumn 2012 (5 September to 6 November 2012) and winter 2013 (1 February to 15 March 2013) SOPs. The overall performance of AROME-WMED is good and similar to those of AROME-France for the 0 to 30 h common forecast range. The 24 to 48 h forecast range is of course less accurate but remains useful for scheduling observation deployment. The characteristics of parameters such as precipitation, temperature or humidity, are illustrated by one heavy precipitation case study that occurred over the south of Spain. [ABSTRACT FROM AUTHOR]

The article assesses the usefulness of synthetic vortex insertion prior to the extratropical transition of hurricanes. Significant improvements in the wind and precipitation patterns within the storm at landfall were observed in the atmospheric model with vortex insertion employed in the initial conditions. The numerical hindcasts employing the technique resolved a particular forecast dilemma involving interaction of Hurricane Michael with a preexisting area of low pressure to its north. Operational forecast models at the time had incorrectly developed the northern low at the expense of the hurricane, while the opposite occurred in reality and in the numerical simulations run in hindcast mode.

Arsenic in groundwater above 0.05 mg/l was found in 61 out of the total of 64 districts, and 433 out of the total of the 496 thanas in Bangladesh. Groundwater arsenic contamination in Bangladesh is reported to be the biggest arsenic calamity in the world in terms of affected population. Water in around 65% of the areas of Bangladesh contain iron in excess of 2 mg/l, and arsenic has been found to co-exist with iron in many situations. Thus the presently used iron removal plants that operate on the principle of aerating ferrous iron to convert it into ferric iron for precipitation can be a cost-effective solution for treating both iron and arsenic together in the context of Bangladesh. This study investigates the efficiency of 60 arsenic and iron removal plants (AIRPS) presently operating in different geo-hydrological conditions of Bangladesh. [ABSTRACT FROM AUTHOR]

A simplified approach is presented for assessing the microwave response to the initial melting of realistically-shaped ice particles. This paper is divided into two parts: (1) a description of the Single Particle Melting Model (SPMM): a heuristic melting simulation for ice-phase precipitation particles of any shape or size. SPMM is applied to two simulated aggregate snow particles, simulating melting up to 0.15 melt fraction by mass; and (2) the computation of the single-particle microwave scattering and extinction properties these hydrometeors, using the discrete dipole approximation (via DDSCAT), at the following selected frequencies: 13.4, 35.6, 94.0 GHz for radar applications; and 89, 165.0 and 183.31 GHz for radiometer applications. These selected frequencies are consistent with current microwave remote sensing platforms, such as CloudSat and the Global Precipitation Measurement (GPM) mission. Comparisons with calculations using variable-density spheres indicate significant deviations in scattering and extinction properties throughout the initial range of melting (liquid volume fractions less than 0.15). Integration of the single-particle properties over an exponential particle-size distribution provides additional insight into idealized radar reflectivity and passive microwave brightness temperature sensitivity to variations in size/mass, shape, melt fraction, and particle orientation. [ABSTRACT FROM AUTHOR]

Rainfall-induced landslides not only cause property loss, but also kill and injure large numbers of people every year in mountainous areas in China. These losses and casualties may be avoided to some extent with rainfall threshold values used in an early warning system at a regional scale for the occurrence of landslides. However, the limited availability of data always causes difficulties. In this paper we present a method to calculate rainfall threshold values with limited data sets for the two rainfall parameters: maximum hourly rainfall intensity and accumulated precipitation. The method has been applied to the Huangshan region, in Anhui Province, China. Four early warning levels (Zero, Outlook, Attention, and Warning) have been adopted and the corresponding rainfall threshold values have been defined by probability lines. A validation procedure showed that this method can significantly enhance the effectiveness of a warning system, and finally reduce the risk from shallow landslides in mountainous regions. [ABSTRACT FROM AUTHOR]

More intense rainfall may cause a range of negative impacts upon society and the environment. In this study we analyzed trends in extreme ETCCDI (Expert Team on Climate Change Detection and Indices) rainfall indices in Montenegro for the period 1951-2010. Montenegro has been poorly studied in terms of rainfall extremes, yet it contains the wettest Mediterranean region known as Krivo²ije. Several indices of precipitation extremes were assessed including the number of dry days and rainfall totals, and their trends to identify possible changes. The results generally suggest that the number of days with precipitation decreased while rainfall intensity increased particularly in south-western parts of the country. A slight tendency towards intense rainfall events is suggested. Calculated trends for each index are spatially presented and examined using a plotGoogleMaps software package. This study also examined spatial pattern of relationship between extreme rainfall indices and North Atlantic Oscillation. Results suggested negative, mainly statistically significant correlations at annual, winter and autumn scale. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) can cause severe wind and rain hazards. Unusual TC tracks and their extreme precipitation forecasts have become two difficult problems faced by conventional models of primitive equations. The case study in this paper finds that the numerical computation of the climatological component in conventional models restricts the prediction of unusual TC tracks. The climatological component should be a forcing quantity, not a predictor in the numerical integration of all models. Anomaly-based variable models can overcome the bottleneck of forecast time length or the one-week forecasting barrier, which is limited to less than one week for conventional models. The challenge in extreme precipitation forecasting is how to physically get the vertical velocity. The anomalous moisture stress modulus (AMSM), as an indicator of heavy rainfall presented in this paper, considers the two conditions associated with vertical velocity and anomalous specific humidity in the lower troposphere. Vertical velocity is produced by the orthogonal collision of horizontal anomalous airflows. [ABSTRACT FROM AUTHOR]

This paper investigates the impact and potential use of the cut cell vertical discretisation for forecasts of 5 days and climate simulations. A first indication of the usefulness of this new method is obtained by a set of five-day forecasts, covering January 1989 by forecasts. The model area was chosen to include much of Asia, the Himalayas and Australia. The cut cell model LMZ provides a much more accurate representation of mountains on model forecasts than the terrain following coordinate used for comparison. Therefore we are in particular interested in potential forecast improvements in the target area downwind of the Himalaya, over South East China, Korea and Japan. The LMZ has been tested so far extensively for one-day forecasts on an European area. Following indications of a reduced temperature error for the short forecasts, this paper investigates the model error for five days in an area influenced by strong orography. The forecasts indicated a strong impact of the cut cell discretisation on forecast quality. The cut cell model is available only of an older (2003) Version of the model LM. It was compared using a control model differing by the use of the terrain following coordinate only. The cut cell model improved the precipitation forecasts of this old control model everywhere by a large margin. An improved version of the terrain following model LM has been developed since then under the name CLM. The CLM has been used and tested in all climates, while the LM was used for small areas in higher latitudes. The precipitation forecasts of cut cell model were compared also to the CLM. As the cut cell model LMZ did not incorporate the developments for CLM since 2003, the precipitation forecast of the CLM was not improved in all aspects. However, for the target area downstream of the Himalaya, the cut cell model improved the prediction of the monthly precipitation forecast even in comparison with the modern model version CLM considerably. The cut cell discretisation seems to improve in particular the localisation of precipitation, while the improvements leading from LM to CLM had a positive effect mainly on amplitude. [ABSTRACT FROM AUTHOR]

A new method to determine the shape and fall velocity of hydrometeors by using a single CCD camera is proposed in this paper, and a prototype of Video Precipitation Sensor (VPS) is developed. The instrument consists of an optical unit (collimated light source with multi-mode fiber cluster), an imaging unit (planar array CCD sensor), an acquisition and control unit, and a data processing unit, the cylindrical space between the optical unit and imaging unit is sampling volume (300mm × 40mm × 30 mm). As the precipitation particles fall through the sampling volume, the CCD camera exposures two times in a single frame, by which the double-exposure of particles images can be obtained. The size and shape can be obtained by the images of particles; the fall velocity can be calculated by particle displacement in double-exposure image and interval time; the drop size distribution and velocity distribution, precipitation intensity, and accumulated precipitation amount can be calculated by time integration. The innovation of VPS is that the shape, size, and velocity of precipitation particles can be measured by only one planar array CCD sensor, which can address the disadvantages of linear scan CCD disdrometer and impact disdrometer. Field measurements of rainfall demonstrate the VPS's capability to measure micro-physical properties of single particles and integral parameters of precipitation. [ABSTRACT FROM AUTHOR]

Detailed characterization and classification of precipitation is an important task in atmospheric research. Line scanning 2-D-video disdrometer technique is well established for rain observations. The two orthogonal views taken of each hydrometeor passing the sensitive area of the instrument qualify this technique especially for detailed characterization of non symmetric solid hydrometeors. However, in case of solid precipitation problems related to the matching algorithm have to be considered and the user must be aware of the limited spacial resolution when size and shape descriptors are analyzed. This work has the aim of clarifying the potential of 2-D-video disdrometer technique in deriving size, velocity and shape parameters from single recorded pictures. The need of implementing a matching algorithm suitable for mixed and solid phase precipitation is highlighted as an essential step in data evaluation. For this purpose simple reproducible experiments with solid steel spheres and irregularly shaped styrofoam particles are conducted. Self-consistency of shape parameter measurements is tested in 40 cases of real snow fall. As result it was found, that reliable size and shape characterization with a relative standard deviation of less than 5% is only possible for particles larger than 1 mm. For particles between 0.5 and 1.0mm the relative standard deviation can grow up to 22% for the volume, 17% for size parameters and 14% for shape descriptors. Testing the adapted matching algorithm with a reproducible experiment with styrofoam particles a mismatch probability of less than 2.5% was found. For shape parameter measurements in case of real solid phase precipitation the 2DVD shows self-consistent behavior. [ABSTRACT FROM AUTHOR]

This publication intends to proof that a network of low-cost local area weather radars (LAWR) is a reliable and scientifically valuable complement to nationwide radar networks. A network of four LAWRs has been installed in northern Germany within the framework of the project Precipitation and Attenuation Estimates from a High- Resolution Weather Radar Network (PATTERN) observing precipitation with temporal resolution of 30 s, azimuthal resolution of 1° and spatial resolution of 60 m. The network covers an area of 60km×80 km. In this paper algorithms used to obtain undisturbed precipitation fields from raw reflectivity data are described and their performance is analysed. In order to correct for background noise in reflectivity measurements operationally, noise level estimates from the measured reflectivity field is combined with noise levels from the last 10 time steps. For detection of non-meteorological echoes two different kinds of clutter filters are applied: single radar algorithms and network based algorithms that take advantage of the unique features of high temporal and spatial resolution of the network. Overall the network based clutter filter works best with a detection rate of up to 70 %, followed by the classic TDBZ filter using the texture of the logarithmic reflectivity field. A comparison of a reflectivity field from the PATTERN network with the product from a C-band radar operated by the German Meteorological Service indicates high spatial accordance of both systems in geographical position of the rain event as well as reflectivity maxima. A longterm study derives good accordance of X-band radar of the network with C-band radar. But especially at the border of precipitation events the standard deviation within a range gate of the C-band radar with range resolution of 1km is up to 3 dBZ. Therefore, a network of high-resolution low-cost LAWRs can give valuable information on the small scale structure of rain events in areas of special interest, e.g. urban regions, in addition the nationwide radar networks. [ABSTRACT FROM AUTHOR]

In the current work we present six hindcast Weather Research and Forecasting (WRF) simulations for the EURO-CORDEX domain with different configurations in microphysics, convection and radiation for the time period 1990-2008. All regional model simulations are forced by the ERA-Interim reanalysis and have the same spatial resolution (0.44°). These simulations are evaluated for surface temperature, precipitation, short- and longwave downward radiation at the surface and total cloud cover. The analysis of the WRF ensemble indicates systematic biases in both temperature and precipitation linked to different physical mechanisms for the summer and winter season. Overestimation of total cloud cover and underestimation of downward shortwave radiation at the surface, mostly when using Grell-Devenyi convection and the CAM radiation scheme, intensifies the negative summer temperature bias in northern Europe (max -2.5 °C). Conversely, a strong positive downward shortwave summer bias in central (40-60 %) and southern Europe mitigates the systematic cold bias in WRF over these regions, signifying a typical case of error compensation. Maximum winter cold bias is over north-eastern Europe (-2.8 °C); this location is indicative of land-atmosphere rather than cloud-radiation interactions. Precipitation is systematically overestimated in summer by all model configurations, especially the higher quantiles, which are associated with summertime deep cumulus convection. The Kain-Fritsch convection scheme produces the larger summertime precipitation biases over the Mediterranean. Winter precipitation is reproduced with lower biases by all model configurations (15-30 %). The results of this study indicate the importance of evaluating not only the basic climatic parameters of interest for climate change applications (temperature-precipitation), but also other components of the energy and water cycle, in order to identify the sources of systematic biases, possible compensatory or masking mechanisms and suggest methodologies for model improvement. [ABSTRACT FROM AUTHOR]

The interannual variability (IAV) in atmospheric CO2 growth rate (CGR) is closely connected with the El Niño-Southern Oscillation. However, sensitivities of CGR to temperature and precipitation remain largely uncertain. This paper analyzed the relationship between Mauna Loa CGR and tropical land climatic elements. We find that Mauna Loa CGR lags precipitation by 4 months with a correlation coefficient of -0.63, leads temperature by 1 month (0.77), and correlates with soil moisture (-0.65) with zero lag. Additionally, precipitation and temperature are highly correlated (-0.66), with precipitation leading by 4-5 months. Regression analysis shows that sensitivities of Mauna Loa CGR to temperature and precipitation are 2.92 ± 0.20 Pg C yr-1 K-1 and -0.46 ± 0.07 Pg C yr-1 100 mm-1, respectively. Unlike some recent suggestions, these empirical relationships favor neither temperature nor precipitation as the dominant factor of CGR IAV. We further analyzed seven terrestrial carbon cycle models, from the TRENDY project, to study the processes underlying CGR IAV. All models capture well the IAV of tropical land-atmosphere carbon flux (CFTA). Sensitivities of the ensemble mean CFTA to temperature and precipitation are 3.18 ± 0.11 Pg C yr-1 K-1 and -0.67 ± 0.04 Pg C yr-1 100 mm-1, close to Mauna Loa CGR. Importantly, the models consistently show the variability in net primary productivity (NPP) dominates CGR, rather than soil respiration. Because NPP is largely driven by precipitation, this suggests a key role of precipitation in CGR IAV despite the higher CGR correlation with temperature. Understanding the relative contribution of CO2 sensitivity to precipitation and temperature has important implications for future carbon-climate feedback using such "emergent constraint". [ABSTRACT FROM AUTHOR]

The article offers the author's insights on the study by O. A. Anisimov and colleague on the estimates of climate change in the regions in Russia in the 20th and 21st century based on observation. The authors state that the objectives of the study was to improve the spatial averaging technique of meteorological variables. They mention that it centers on the comparison of estimates of regional changes in precipitation and temperature without clear formulated conclusions.

As part of the High Definition Clouds and Precipitation for advancing Climate Prediction Observational Prototype Experiment (HOPE), a high spatial density network of 99 silicon photodiode pyranometers was set up around Jülich (10km×12km area) from April to July 2013, to capture the variability in the radiation field at the surface induced by small-scale cloud inhomogeneity. Each of these autonomously operated pyranometer stations was equipped with weather sensors for simultaneous measurements of ambient air temperature and relative humidity. In this paper, we provide the details of this unique setup of the pyranometer network and the data analysis with initial quality screening procedure we adopted. We also present some exemplary cases consisting of the days with clear, broken cloudy and overcast skies to assess our spatio-temporal observations from the network, and validate their consistency with other collocated radiation measurements available during the HOPE period. [ABSTRACT FROM AUTHOR]

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The effects on climate of land-cover change, predominantly from forests to crops or grassland, are reasonably well understood for low and high latitudes but are largely unknown for temperate latitudes. The main reason for this gap in our knowledge is that there are compensating effects on the energy and water balance when land cover changes. To obtain a better understanding of the direction of this response, we analyse the differential response of tall and short vegetation to the 2003 European drought. We analyse precipitation, temperature and normalized difference vegetation index data and compare these with direct measurements of vegetation height. At the height of the 2003 drought we find for tall vegetation a significantly smaller decrease in vegetation index and a smaller diurnal temperature range, indicating less water stress on tall vegetation, which can be explained by access of tall vegetation to deeper soil water. Based on these results we question the current parameterizations of short and tall vegetation in some land-surface models. [ABSTRACT FROM AUTHOR]

In Morocco, socioeconomic fields are vulnerable to weather extreme events. This work aims to analyze the frequency and the trends of temperature and rainfall extreme events in two contrasted Moroccan regions (the Tensift in the semi-arid South, and the Bouregreg in the sub-humid North), during the second half of the 20th century. This study considers long time series of daily extreme temperatures and rainfall, recorded in the stations of Marrakech and Safi for the Tensift region, and Kasba-Tadla and Rabat- Sale for the Bouregreg region, data from four other stations (Tanger, Fes, Agadir and Ouarzazate) from outside the regions were added. Extremes are defined by using as thresholds the 1st, 5th, 90th, 95th, and 99th percentiles. Results show upward trends in maximum and minimum temperatures of both regions and no generalized trends in rainfall amounts. Changes in cold events are larger than those for warm events, and the number of very cold events decrease significantly in the whole studied area. The southern region is the most affected with the changes of the temperature regime. Most of the trends found in rainfall heavy events are positive with weak magnitudes even though no statistically significant generalized trends could be identified during both seasons. [ABSTRACT FROM AUTHOR]

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05°) global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0, http://dx.doi.org/10.15780/G2159X), is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities. [ABSTRACT FROM AUTHOR]

Two radar pulses sent at different frequencies near the 60 GHz O2 absorption band can be used to determine surface pressure by measuring the differential absorption on and off the band. Results of inverting synthetic data assuming an airborne radar are presented. The analysis includes the effects of temperature, water vapor, hydrometeors as well as particle size distributions and surface backscatter uncertainties. Results show that an airborne radar (with sensitivity of -20 and 0.05 dBZ speckle and relative calibration uncertainties and a 400m by 400m footprint) can estimate surface pressure with a precision of ~1.0 hPa and accuracy better than 1.0 hPa for clear-sky and cloudy conditions and better than 3.5 hPa for precipitating conditions. Generally, accuracy would be around 0.5 and 2 hPa for non-precipitating and precipitating conditions, respectively. [ABSTRACT FROM AUTHOR]

This paper describes the new "First Guess Daily" product of the Global Precipitation Climatology Centre (GPCC). The new product gives an estimate of the global daily precipitation gridded at a spatial resolution of 1° latitude by longitude. It is based on rain gauge data reported in near real-time via the Global Telecommunication System (GTS) and available about three to five days after the end of each observation month. In addition to the gridded daily precipitation totals in mm day-1, the standard deviation in mm day-1, the Kriging interpolation error in % and the number of measurements per grid cell are also encoded into the monthly netCDF product file and provided for all months since January 2009. Prior to their interpolation the measured precipitation values undergo a preliminary automatic quality control. For the calculation of the areal mean of the grid, anomalies are interpolated with ordinary block Kriging. This approach allows for a near real-time release. However, the purely GTS-based data processing lacks an intensive quality control as well as a high data density. Therefore the product is denoted as "First Guess", and DOI referenced under doi:10.5676/DWD_GPCC/FG_D_100. Besides the "First Guess Daily" product, two further products are under development at GPCC ("Full Data Daily" and a merged satellite-gauge product), which will be based on all available daily data that have undergone a strict quality control. All GPCC products are available free of charge and provided via the GPCC webpage: ftp://ftp-anon.dwd.de/pub/data/gpcc/html/download_gate.html. [ABSTRACT FROM AUTHOR]

This paper presents a holistic approach to biological and agricultural research focused on the use of interconnected technologies in the context of climate change. Researchers from different countries have analyzed how smart technologies can help agriculture adapt to these changes. The most representative works in the field are analyzed. Among these technologies are graph database systems such as Neo4j, which have demonstrated success in predicting the studied phenomena. The paper describes the development of a soybean crop productivity prediction model using monthly and annual data of meteorological phenomena such as precipitation, air temperature, hydrothermal coefficient, soil moisture and others. Some of the results of this promising research are also presented. [ABSTRACT FROM AUTHOR]

This paper investigates the binning effects on drop size distribution (DSD) measurements obtained by Joss-Waldvogel disdrometer (JWD), Precipitation Occurrence Sensor System (POSS), Thies disdrometer (Thies), Parsivel OTT disdrometer, two-dimensional video disdrometer (2DVD) and optical spectro-pluviometer (OSP) instruments, therefore the evaluation comprises non-regular bin sizes and the effect of minimum and maximum measured sizes of drops. To achieve this goal, 2DVD measurements and simulated gamma size distributions were considered. The analysis of simulated gamma DSD binned according each instrument was performed to understand the role of discretisation and truncation effects together on the integral rainfall parameters and estimators of the DSD parameters. In addition, the drop-by-drop output of the 2DVD is binned to simulate the raw output of the other disdrometers which allowed us estimate sampling and binning effects on selected events from available dataset. From simulated DSD it has been found that binning effects exist in integral rainfall parameters and in the evaluation of DSD parameters of a gamma distribution. This study indicates that POSS and JWD exhibit underestimation of concentration and mean diameter due to binning. Thies and Parsivel report a positive bias for rainfall and reflectivity (reaching 5% for heavy rainfall intensity events). Regarding to DSD parameters, distributions of estimators for the shape and scale parameters were analyzed by moment, truncated moment and maximum likelihood methods. They reported noticeable differences between instruments for all methodologies of estimation applied. The measurements of 2DVD allow sampling error estimation of instruments with smaller capture areas than 2DVD. The results show that the instrument differences due to sampling were a relevant uncertainty but that concentration, reflectivity and mass-weighted diameter were sensitive to binning. [ABSTRACT FROM AUTHOR]

Using measurements from the national network of 12 weather radar stations for the last decade (2000-2010), we investigate the large-scale spatio-temporal variability of precipitation over Sweden. These statistics provide useful information to evaluate re- gional climate models as well as for hydrology and energy applications. A strict quality control is applied to filter out noise and artifacts from the radar data. We focus on investigating four distinct aspects namely, the diurnal cycle of precipitation and its seasonality, the dominant time scale (diurnal vs. seasonal) of variability, precipitation response to different wind directions, and the correlation of precipitation events with the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO). When classified based on their intensity, moderate to high intensity events (precipitation> 0.34mm(3h)-1) peak distinctly during late afternoon over the majority of radar stations in summer and during late night or early morning in winter. Precipitation variability is highest over the southwestern parts of Sweden. It is shown that the high intensity events (precipitation> 1.7mm(3h)-1) are positively correlated with NAO and AO (esp. over northern Sweden), while the low intensity events are negatively correlated (esp. over southeastern parts). It is further observed that southeasterly winds often lead to intense precipitation events over central and northern Sweden, while southwesterly winds contribute most to the total accumulated precipitation for all radar stations. Apart from its operational applications, the present study demonstrates the potential of the weather radar data set for studying climatic features of precipitation over Sweden. [ABSTRACT FROM AUTHOR]

Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationships exist between precipitation and TWS, the latter also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and hydrologic cycle, but also provide new model calibration constraints for improving the current land surface models. In this work, the connectivity of TWS is quantified using the climate network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS datasets, a remote-sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated dataset from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both datasets have 1° ×1 ° resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quanti15 fying pairwise correlation among all valid TWS anomaly time series, and then applying a statistical cutoff threshold to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show TWS hotspots around the globe and the patterns are consistent with recent GRACE 20 studies. Parallel analyses of networks constructed using the two datasets indicate that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide important insights for constraining land surface models, especially in data sparse regions. [ABSTRACT FROM AUTHOR]

A new, two-layer canopy module with thermal inertia as part of the detailed snow model SNOWPACK (version 3.2.1) is presented and evaluated. This module is designed to reproduce the difference in thermal response between leafy and woody canopy elements, and their impact on the underlying snowpack energy balance. Given the number of processes resolved, the SNOWPACK model with its enhanced canopy module constitutes a very advanced, physics-based atmosphere-to-soil-through-canopy-and-snow modelling chain. Comparisons of modelled sub-canopy thermal radiation to stand-scale observations at an Alpine site (Alptal, Switzerland) demonstrate the improvements of the new canopy module. Both thermal heat mass and the two-layer canopy formulation contribute to reduce the daily amplitude of the modelled canopy temperature signal, in agreement with observations. Particularly striking is the attenuation of the night-time drop in canopy temperature, which was a key model bias. We specifically show that a single-layered canopy model is unable to produce this limited temperature drop correctly. The impact of the new parameterizations on the modelled dynamics of the subcanopy snowpack is analysed and yields consistent results but the frequent occurrence of mixed-precipitation events at Alptal prevents a conclusive assessment of model performance against snow data. The new model is also successfully tested without specific tuning against measured tree temperatures and biomass heat storage fluxes at the boreal site of Norunda (Sweden). This provides an independent assessment of its physical consistency and stresses the robustness and transferability of the parameterizations used. [ABSTRACT FROM AUTHOR]

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

This work is a first assessment of the role of Doppler Weather radar (DWR) data in a mesoscale model for the prediction of a heavy rainfall. The study analyzes the event occurred during 19–22 May 2008 in the urban area of Rome. The impact of the radar reflectivity and radial velocity acquired from Monte Midia Doppler radar, on the assimilation into the Weather Research Forecasting (WRF) model version 3.2, is discussed. The goal is to improve the WRF high resolution initial condition by assimilating DWR data and using ECMWF analyses as First Guess thus improving the forecast of surface rainfall. Several experiments are performed using different set of Initial Conditions (ECMWF analyses and warm start or cycling) and a different assimilation strategy (3 h-data assimilation cycle). In addition, 3DVAR (three-dimensional variational) sensitivity tests to outer loops are performed for each of the previous experiment to include the nonlinearity in the observation operators. In order to identify the best ICs, statistical indicators such as forecast accuracy, frequency bias, false alarm rate and equitable threat score for the accumulated precipitation are used. The results show that the assimilation of DWR data has a positive impact on the prediction of the heavy rainfall of this event, both assimilating reflectivity and radial velocity, together with conventional observations. Finally, warm start results in more accurate experiments as well as the outer loops strategy. [ABSTRACT FROM AUTHOR]

The rates and processes that lead to non-tectonic rock fracture on the Earth's surface are widely debated but poorly understood. Few, if any, studies have made the direct observations of rock fracturing under natural conditions that are necessary to directly address this problem. An instrumentation design that enables concurrent high spatial and temporal monitoring resolution of (1) diurnal environmental conditions of a natural boulder and its surroundings in addition to (2) the fracturing of that boulder under natural full-sun exposure is described herein. The surface of a fluvially transported granite boulder was instrumented with (1) six acoustic emission (AE) sensors that record micro-crack associated, elastic wave-generated activity within the three-dimensional space of the boulder, (2) eight rectangular rosette foil strain gages to measure surface strain, (3) eight thermocouples to measure surface temperature, and (4) one surface moisture sensor. Additionally, a soil moisture probe and a full weather station that measures ambient temperature, relative humidity, wind speed, wind direction, barometric pressure, insolation, and precipitation were installed adjacent to the test boulder. AE activity was continuously monitored by one logger while all other variables were acquired by a separate logger every 60 s. The protocols associated with the instrumentation, data acquisition, and analyses are discussed in detail. During the first four months, the deployed boulder experienced almost 12 000 AE events, the majority of which occur in the afternoon when temperatures are decreasing. This paper presents preliminary data that illustrates data validity and typical patterns and behaviors observed. This system offers the potential to (1) obtain an unprecedented record of the natural conditions under which rocks fracture and (2) decipher the mechanical processes that lead to rock fracture at a variety of temporal scales under a range of natural conditions. [ABSTRACT FROM AUTHOR]

The article presents information on a study conducted on the impact of climate change on agriculture. In the study, Community Land Model (CLM)-Crop was validated against observations from two agricultural sites in the U.S., that were planted with maize and soybean. CLM-Crop was compared with the standard CLM3.5, which is associated with crops as grass. The study found that crop yields and productivity had a negative correlation with temperature, and a positive correlation with precipitation.

A simultaneous analysis of 13 years of remotely sensed data of land cover, fires, precipitation, and aerosols from the MODIS, TRMM, and MISR satellites and the AERONET network over Southeast Asia is performed, leading to a set of robust relationships be- tween land-use change and fire being found on inter-annual and intra-annual scales over Southeast Asia, reflecting the heavy amounts of anthropogenic influence over land use change and fires in this region of the world. First, we find that fires occur annually, but with a considerable amount of variance in their onset, duration, and intensity from year to year, and from two separate regions within Southeast Asia from each other. This variability is already partially understood from previous works, including the impacts of both inter-annually and intra-annually occurring influences such as the Monsoon and El-Nino events, but yet there are other as of yet unknown influences that also are found to strongly influence the results. Second, we show that a simple regression-model of the land-cover, fire, and precipitation data can be used to recreate a robust representation of the timing and magnitude of measured AOD from multiple measurements sources of this region using either 8-day (better for onset and duration) or monthly based (better for magnitude) measurements, but not daily measurements. We find that the reconstructed AOD matches the timing and intensity from AERONET measurements to within 70 to 90% and the timing and intensity of MISR measurements from to within 50 to 95%. This is a unique finding in this part of the world, since could-covered regions are large, yet the robustness of the model is still capable of holding over many of these regions, where otherwise no fires are observed and hence no emissions source contribution to AOD would otherwise be thought to occur. Third, we determine that while Southeast Asia is a source region of such intense smoke emissions, that it is also impacted by transport of smoke from other regions as well. There are regions in northern Southeast Asia which have two annual AOD peaks, one during the local fire season, and the second smaller peak corresponding to a combination of some local smoke sources as well as transport of aerosols from fires in southern Southeast Asia, and possibly even from anthropogenic sources in South Asia. Conversely, we show that southern Southeast Asia is affected exclusively by its own local fire sources during its own local fire season. Overall, this study highlights the importance of taking into account a simultaneous use of land-use, fire, and precipitation for understanding the impacts of fires on the atmospheric loading and distribution of aerosols in Southeast Asia over both space and time. [ABSTRACT FROM AUTHOR]

The article presents a study which provides reference publication on the description of the land-surface precipitation data products of the Global Precipitation Climatology Centre (GPCC) with applications such as centennial trend analysis. The study employs interpolation of gauge data, gridding method, and Kriging interpolation. It says that sample applications provide potential users of GPCC data products information regarding the constraints and capabilities of the gridded data sets.

We present a methodology to correct precipitation fluxes from the ECMWF atmospheric reanalysis (ERA-Interim) for oceanographic applications. The correction is performed by means of a spatially varying monthly climatological coefficient, computed within the period 1989-2008 by comparison between ERA-Interim and a satellite-based passive microwave precipitation product. ERA-Interim exhibits a systematic over-estimation of precipitation within the inter-tropical convergence zones (up to 3mmd-1) and underestimation at mid- and high- latitudes (up to -4mmd-1). The correction has been validated within eddy-permitting resolution global ocean hindcasts (1989-2009), demon strating the ability of our strategy in attenuating the 20-yr mean global EMP negative imbalance by 16 %, reducing the near-surface salinity fresh bias in the Tropics up to 1 psu and improving the representation of the sea level interannual variability, with an SSH error decrease of 8%. The ocean circulation is also proved to benefit from the correction, especially in correspondence of the Antarctic Circumpolar Current, where the error in the near-surface current speed decreases by a 9%. Finally, we show that the correction leads to volume and freshwater transports that better agree with independent estimates. [ABSTRACT FROM AUTHOR]

Podzol-ferralsol soil systems cover great areas in Amazonia and in other equatorial regions, they are an end-member of old equatorial landscape evolution, are frequently associated with kaolin deposits and store and export large amounts of carbon. Their biogeochemistry was usually inferred from soil mineralogy and from spring or river water properties. This paper presents a database for groundwaters sampled in situ in a typical podzol-ferralsol soil catena from the Alto Rio Negro region, Brazil; the sampling periods allowed to sample under high- and low-level water-table conditions. The compositions of the groundwaters percolating the soil system are consistent with the currently observed mineral and organic paragenesis. The acidity and the site density of the dissolved organic matter (DOM) produced and circulating in the podzol white sand horizons are similar to what was observed in acid podzolic temperate zone. The aggressiveness of the white sand groundwater with regard to secondary minerals favours the podzol development at the expense of the ferralsolic or kaolin material. Some DOM is able to percolate in depth through clayey material with concentrations up to 9.7mgCl-1 (4.0 on average). This DOM is characterized by high site densities indicating a large proportion of small carboxylic acids. In the deep kaolin and in the ferralsolic horizons, the Si and Al content of the groundwater is controlled by gibbsite and kaolinite precipitation/dissolution and by quartz dissolution. The mobility of Fe, mainly transported as Fe2+, is sensitive to small variations in EH. The bleaching of the deep kaolin at the upper part of the slopes is favoured by the high content of small carboxylic compounds and by the redox conditions of the solutions issuing from the podzolic horizons. The transfer of Al and Fe result in the precipitation of Al-nodules in slope horizons and of Fe-oxides in the upper downslope horizon. It can be inferred that thick bleached kaolin are likely everywhere presently active giant podzols are close to a slope gradient sufficient to allow deep percolation of groundwater. [ABSTRACT FROM AUTHOR]

The article offers a description of the experimental design and model results of the climate simulations of the mid-Pliocene Warm Period through the use of the Institut Pierre Simon Laplace model (IPSLCM5A). It describes the main features of the IPSL model as well as illustrates the boundary conditions used for atmospheric model and coupled model experiments. The difference of behaviour in the coupled model and the atmospheric model through simulated precipitation is discussed.

Karst groundwater is a crucial water source, but it has faced significant environmental risks in recent years. The complexity of the groundwater system necessitates innovative approaches to studying karst groundwater. This paper focuses on the karst groundwater of the Baotu Spring area in Jinan. Using the nanoparticle tracking analysis instrument, it is observed that the collected groundwater contains many natural nanoparticles, with particle sizes mainly ranging from 76.3 to 621.8 nm and concentrations primarily between 0.31 and 5.0 × 105 Particles/L. The transmission electron microscope (TEM) is used to study the characteristics of naturally occurring nanoparticles in the karst groundwater. The results show that the karst groundwater mainly contains particles of Ca, Na, Fe, Al, Si, and other elements, which exist in granular and irregular forms. The size of individual particles varies from 40 to 600 nm, and they are mostly amorphous and monocrystalline. The characteristics of the particles suggest that the direct recharge area mainly receives infiltration from atmospheric precipitation, with minimal influence from human activities and agriculture. In contrast, the indirect recharge and discharge areas are more significantly affected by external environments, including domestic sewage, industrial wastewater discharge, and agricultural fertilizers. These findings also suggest that elements can be transported in particle form during water-rock interactions, potentially playing a significant role in the cycling of elements between water and rocks. The particles in the study area are situated in a relatively oxidized environment, suggesting that fracture and oxidation are the main processes for particle formation. Particles can effectively transport metallic elements in groundwater, offering fresh perspectives on the migration of these elements and acting as carriers for inorganic substances, thereby increasing their mobility in aquatic environments. Given the widespread presence of natural nanoparticles in the water cycle system, some stable nanoparticles can serve as new types of groundwater tracing agents during the groundwater migration process. [ABSTRACT FROM AUTHOR]

This research paper explores the implementation of machine learning (ML) techniques in weather and climate forecasting, with a specific focus on predicting monthly precipitation. The study analyzes the efficacy of six multivariate machine learning models: Decision Tree, Random Forest, K-Nearest Neighbors (KNN), AdaBoost, XGBoost, and Long Short-Term Memory (LSTM). Multivariate time series models incorporating lagged meteorological variables were employed to capture the dynamics of monthly rainfall in Rabat, Morocco, from 1993 to 2018. The models were evaluated based on various metrics, including root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). XGBoost showed the highest performance among the six individual models, with an RMSE of 40.8 (mm). In contrast, Decision Tree, AdaBoost, Random Forest, LSTM, and KNN showed relatively lower performances, with specific RMSEs ranging from 47.5 (mm) to 51 (mm). A novel multi-view stacking learning approach is introduced, offering a new perspective on various ML strategies. This integrated algorithm is designed to leverage the strengths of each individual model, aiming to substantially improve the precision of precipitation forecasts. The best results were achieved by combining Decision Tree, KNN, and LSTM to build the meta-base while using XGBoost as the second-level learner. This approach yielded a RMSE of 17.5 millimeters. The results show the potential of the proposed multi-view stacking learning algorithm to refine predictive results and improve the accuracy of monthly precipitation forecasts, setting a benchmark for future research in this field. [ABSTRACT FROM AUTHOR]

Gridded precipitation (PRP) data have been largely used in diagnostic studies on the climate variability in several time scales, as well as to validate model results. The three most used gauge-based PRP datasets are from the Global Precipitation Climatology Centre (GPCC), University of Delaware (UDEL), and Climate Research Unit (CRU). This paper evaluates the performance of these datasets in reproducing spatiotemporal PRP climatological features over the entire South America (SA) for the 1901–2015 period, aiming to identify the differences and similarities among the datasets as well as time intervals and areas with potential uncertainties involved with these datasets. Comparisons of the PRP annual means and variances between the 1901–2015 period and the non-overlapping 30-year subperiods of 1901–1930, 1931–1960, 1961–1990, and the 25-year subperiod of 1991–2015 for each dataset show varying means of the annual PRP over SA depending on the subperiod and dataset. Consistent patterns among datasets are found in most of southeastern SA and southeastern Brazil, where they evolved gradually from less to more rainy conditions from 1901–1930 to the 1991–2015 subperiod. All three datasets present limitations and uncertainties in regions with poor coverage of gauge stations, where the differences among datasets are more pronounced. In particular, the GPCC presents reduced PRP variability in an extensive area west of 50° W and north of 20° S during the 1901–1930 subperiod. In monthly time scale, PRP time series in two areas show differences among the datasets for periods before 1941, which are likely due to spurious or missing data: central Bolivia (CBO), and central Brazil (CBR). The GPCC has less monthly variability before 1940 than the other two datasets in these two areas, and UDEL presents reduced monthly variability before 1940 and spurious monthly values from May to September of the years from 1929 to 1941 in CBO. Thus, studies with these three datasets might lead to different results depending on the study domain and period of analysis, in particular for those including years before 1941. The results here might be relevant for future diagnostic and modelling studies on climate variability from interannual to multidecadal time scales. [ABSTRACT FROM AUTHOR]

Multi-frequency radars offer enhanced detection of clouds and precipitation compared to single-frequency systems, and are able to make more accurate retrievals when several frequencies are available simultaneously. An evaluation of a spaceborne three-frequency Ku/Ka/W-band radar system is presented in this study, based on modeling radar reflectivities from the results of a global cloud-resolving model with a 875m grid spacing. To produce the reflectivities, a scattering model has been developed for each of the hydrometeor types produced by the model, as well as for melting snow. The effects of attenuation and multiple scattering on the radar signal are modeled using a radiative transfer model, while nonuniform beam filling is reproduced with spatial averaging. The combined effects of these are then quantified both globally and in five localized case studies. Two different orbital scenarios using the same radar are compared. Overall, based on the results, it is expected that the proposed radar would detect a high-quality signal in most clouds and precipitation. The main exceptions are the thinnest clouds that are below the detection threshold of the W-band channel, and at the opposite end of the scale, heavy convective rainfall where a combination of attenuation, multiple scattering and nonuniform beam filling commonly cause significant deterioration of the signal; thus, while the latter can be generally detected, the quality of the retrievals is likely to be degraded. [ABSTRACT FROM AUTHOR]

The theoretical framework of a novel approach for absolute radar calibration is presented and its potential analysed by means of synthetic data to lay out a solid basis for future practical application. The method presents the advantage of an absolute calibration with respect to the directly measured reflectivity, without needing a previously calibrated reference device. It requires a setup comprising three radars: two devices oriented towards each other, measuring reflectivity along the same horizontal beam and operating within a strongly attenuated frequency range (e.g. K or X band) and one vertical reflectivity and drop size distribution (DSD) profiler below this connecting line, which is to be calibrated. The absolute determination of the calibration factor is based on attenuation estimates. Using synthetic, smooth and geometrically idealised data calibration is found to perform best using homogeneous precipitation events with rain rates high enough to ensure a distinct attenuation signal (approx. 30 dBZ). Furthermore, the choice of the in terval width (in measuring range gates) around the vertically pointing radar, needed for attenuation estimation, is found to have an impact on the calibration results. Further analysis is done by means of synthetic data with realistic, inhomogeneous precipitation fields taken from measurements. A calibration factor is calculated for each considered case using the presented method. Based on the distribution of the calculated calibration factors, the most probable value is determined by estimating the mode of a fitted shifted logarithmic normal distribution function. After filtering the data set with respect to rain rate and in homogeneity and choosing an appropriate length of the considered attenuation path, the estimated uncertainty of the calibration factor is in the order of 1 %. Considering stability and accuracy of the method, an interval of 8 range gates on both sides of the vertically pointing radar is most appropriate for calibration. [ABSTRACT FROM AUTHOR]

Using decade-long continuous observations of tree mortality and predawn leaf water potential (Ψpd) at the Missouri Ozark AmeriFlux (MOFLUX) site, we studied how the mortality of important tree species varied along the isohydric to anisohydric continuum and how such variations may be predicted. Water stress determined inter-annual variations in tree mortality with a time delay of one year or more, which was predicted by predawn leaf water potential integral (PLWPI), mean effective precipitation interval (a time period with no daily precipitation rates exceeding a threshold) with a daily threshold precipitation at 5 mm day-1 (MEPI5), and precipitation variability index (PVI). Positive temperature anomaly integral (PTAI) and vapor pressure deficit integral (VPDI) also worked reasonably well, particularly for moderate droughts. The extreme drought of the year 2012 drastically increased the mortality of all species in the subsequent year. Regardless of the degree of isohydry and drought intensity, the Ψpd of all species recovered rapidly after sufficiently intense rain events. This, together with a lack of immediate leaf and branch desiccation, suggests that hydraulic disconnection in the xylem was absent even during extreme drought and tree death was caused by significant but indirect effects of drought. We also found that species occupying middle positions along the isohydric to anisohydric continuum suffered less mortality than those at either extremes (i.e. extremely isohydric or extremely anisohydric). Finally, our study suggested that species differences in mortality mechanisms can be overwhelmed and masked in extreme droughts and should be examined in a broad range of drought intensity. [ABSTRACT FROM AUTHOR]

Recent studies have drawn attention to a significant weakening trend of the South Asian monsoon circulation and an associated decrease in regional rainfall during the last few decades. While surface temperatures over the region have steadily risen during this period, most of the CMIP (Coupled Model Intercomparison Project) global climate models have dificulties in capturing the observed decrease of monsoon precipitation, thus limiting our understanding of the regional land surface response to monsoonal changes. This problem is investigated by performing two long-term simulation experiments, with and without anthropogenic forcing, using a variable resolution global climate model having high-resolution zooming over the South Asian region. The present results indicate that anthropogenic effects have considerably influenced the recent weakening of the monsoon circulation and decline of precipitation. It is seen that the simulated increase of surface temperature over the Indian region during the post-1950s is accompanied by a significant decrease of monsoon precipitation and soil moisture. Our analysis further reveals that the land surface response to decrease of soil moisture is associated with significant reduction in evapotranspiration over the Indian land region. A future projection, based on the representative concentration pathway 4.5 (RCP4.5) scenario of the Intergovernmental panel on Climate Change (IPCC), using the same high-resolution model indicates the possibility for detecting the summer-time soil drying signal over the Indian region during the 21st century, in response to climate change. While these monsoon hydrological changes have profound socioeconomic implications, the robustness of the high-resolution simulations provides deeper insights and enhances our understanding of the regional land surface response to the changing South Asian monsoon. [ABSTRACT FROM AUTHOR]

Metrics of storm activity in Northern Hemisphere high- and midlatitudes are evaluated from historical output and future projections by the Norwegian Earth System Model (NorESM1-M) coupled global climate model. The European Re-Analysis Interim (ERA- Interim) and the Community Climate System Model (CCSM4), a global climate model of the same vintage as NorESM1-M, provide benchmarks for comparison. The focus is on the autumn and early winter (September through December), the period when the ongoing and projected Arctic sea ice retreat is greatest. Storm tracks derived from a vorticity-based algorithm for storm identification are reproduced well by NorESM1- M, although the tracks are somewhat better resolved in the higher-resolution ERAInterim and CCSM4. The tracks are projected to shift polewards in the future as climate changes under the Representative Concentration Pathway (RCP) forcing scenarios. Cyclones are projected to become generally more intense in the high-latitudes, especially over the Alaskan region, although in some other areas the intensity is projected to decrease. While projected changes in track density are less coherent, there is a general tendency towards less frequent storms in midlatitudes and more frequent storms in high-latitudes, especially the Baffin Bay/Davis Strait region. Autumn precipitation is projected to increase significantly across the entire high-latitudes. Together with the projected increases in storm intensity and sea level and the loss of sea ice, this increase in precipitation implies a greater vulnerability to coastal flooding and erosion, especially in the Alaskan region. The projected changes in storm intensity and precipitation (as well as sea ice and sea level pressure) scale generally linearly with the RCP value of the forcing and with time through the 21st century. [ABSTRACT FROM AUTHOR]

An idealized synthetic database loosely resembling 3-channel passive microwave observations of precipitation against a variable background is employed to examine the performance of a conventional Bayesian retrieval algorithm. For this dataset, algorithm performance is found to be poor owing to an irreconcilable conflict between the need to find matches in the dependent database versus the need to exclude inappropriate matches. It is argued that the likelihood of such conflicts increases sharply with the dimensionality of the observation space of real satellite sensors, which may utilize 9 to 13 channels to retrieve precipitation, for example. An objective method is described for distilling the relevant information content from N real channels into a much smaller number (M) of pseudochannels while also regularizing the background (geophysical plus instrument) noise component. The pseudochannels are linear combinations of the original N channels obtained via a two-stage principal component analysis of the dependent dataset. Bayesian retrievals based on a single pseudochannel applied to the independent dataset yield striking improvements in overall performance. The differences between the conventional Bayesian retrieval and reduceddimensional Bayesian retrieval suggest that a major potential problem with conventional multichannel retrievals - whether Bayesian or not - lies in the common but of ten inappropriate assumption of diagonal error covariance. The dimensional reduction technique described herein avoids this problem by, in effect, recasting the retrieval problem in a coordinate system in which the desired covariance is lower-dimensional, diagonal, and unit magnitude [ABSTRACT FROM AUTHOR]

The article discusses two new versions of FAMOUS, which plays an important role in filling hierarchy of climate models. It is informed that carbon cycle parameters of FAMOUS model use a perturbed physics ensemble technique. It is informed that in comparion to previous versions of FAMOUS, these new models have improved climatologies of surface and tropospheric air temperature and precipitation.

The Synthetic Aperture Radar (SAR) is able to generate images of the sea surface that can be exploited to extract geophysical information of environmental interest. In order to enhance the operational use of these data in the marine applications the revisit time is to be improved. This goal can be achieved by using SAR virtual or real constellations and/or exploiting new antenna technologies that allow huge swath and fine resolution. Within this framework, the presence of the Italian and German X-band SAR constellations is of special interest while the new SAR technologies are not nowadays operated. Although SAR images are considered to be independent of weather conditions, this is only partially true at higher frequencies, e.g. X-band. In fact, observations can present signature corresponding to high intensity precipitating clouds, i.e. rain cells. Further, ScanSAR images may be characterized by the presence of processing artifacts, called scalloping, that corrupt image interpretation. In this paper we review these key facts that are at the basis of an effective use of X-band SAR images for marine applications. [ABSTRACT FROM AUTHOR]