Scaling of tropical rainfall as observed by TRMM precipitation radar

We used a three-year (1998–2000) dataset of TRMM Precipitation Radar observations to investigate the scaling properties of spatial rainfall fields. This dataset allows consideration of spatial scales ranging from about 4.3 km to 138 km and short temporal scales corresponding to the sensor overpasses. The focus is on the marginal spatial moment scaling, which allows estimation of the scaling parameters from a single scene of data. Here we present a global perspective of the scaling properties of tropical rainfall in terms of its spatial variability, atmospheric forcing, predictability, and applicability. Our results reveal the following: 1) the scaling parameters exhibit strong variability associated with land/ocean contrast and mean precipitation at the synoptic scale; 2) there exists a one-to-one relationship between the scaling parameters and the large-scale spatial average rain rate of a universal functional form; 3) the majority of the scenes are consistent with the hypothesis of scale invariance at the moment orders of 0 and 2; 4) relatively there are more scale-invariant rain scenes over land than over ocean; and 5) for the scenes that are non-scale-invariant, deviation from scale-invariance mainly arises from the increasingly intermittent behavior of rainfall as spatial scale decreases. These results have important implications for the development and calibration of downscaling procedures designed to reproduce rainfall properties at different spatial scales and lead to a better understanding of the nature of tropical rainfall at various spatial resolutions.     

An approach to response-based reliability analysis of quasi-linear Errors-in-Variables models

The paper presents an approach to internal reliability analysis of observation systems known as Errors-in-Variables (EIV) models with parameters estimated by the method of least squares. Such problems are routinely treated by total least squares adjustment, or orthogonal regression. To create a suitable environment for derivations in the analysis, a general nonlinear form of such EIV models is assumed, based on a traditional adjustment method of condition equations with unknowns, also known as the Gauss–Helmert model. However, in order to apply the method of reliability analysis based on the approach to response assessment in systems with correlated observations, presented in the earlier work of this author, it was necessary to confine the considerations to a quasi-linear form of the Gauss–Helmert model, representing quasi-linear EIV models. This made it possible to obtain a linear disturbance/response relationship needed in that approach. Several specific cases of quasi-linear EIV models are discussed. The derived formulas are consistent with those already functioning for standard least squares adjustment problems. The analysis shows that, as could be expected, the average level of response-based reliability for such EIV models under investigation is lower than that for the corresponding standard linear models. For EIV models with homoscedastic and uncorrelated observations, the relationship between the average reliability indices for the independent and the dependent variables is formulated for multiple regression and coordinate transformations. Numerical examples for these two applications are provided to illustrate this analysis.     

Analyses of the warm season rainfall climatology of the northeastern US using regional climate model simulations and radar rainfall fields

We examine the warm season (April-September) rainfall climatology of the northeastern US through analyses of high-resolution radar rainfall fields from the Hydro-NEXRAD system and regional climate model simulations using the weather research and forecasting (WRF) model. Analyses center on the 5-year period from 2003 to 2007 and the study area includes the New York-New Jersey metropolitan region covered by radar rainfall fields from the Fort Dix, NJ WSR-88D. The objective of this study is to develop and test tools for examining rainfall climatology, with a special focus on heavy rainfall. An additional emphasis is on rainfall climatology in regions of complex terrain, like the northeastern US, which is characterized by land-water boundaries, large heterogeneity in land use and cover, and mountainous terrain in the western portion of the region. We develop a 5-year record of warm season radar rainfall fields for the study region using the Hydro-NEXRAD system. We perform regional downscaling simulations for the 5-year study period using the WRF model. Radar rainfall fields are used to characterize the interannual, seasonal and diurnal variation of rainfall over the study region and to examine spatial heterogeneity of rainfall. Regional climate model simulations are characterized by a wet bias in the rainfall fields, with the largest bias in the high-elevation regions of the model domain. We show that model simulations capture broad features of the interannual, seasonal, and diurnal variation of rainfall. Model simulations do not capture spatial gradients in radar rainfall fields around the New York metropolitan region and land-water boundaries to the east. The model climatology of convective available potential energy (CAPE) is used to interpret the regional distribution of warm season rainfall and the seasonal and diurnal variability of rainfall. We use hydrologic and meteorological observations from July 2007 to examine the interactions of land surface processes and rainfall from a regional perspective.     

Assessment of mercury mobility and bioavailability by fractionation method in sediments from coastal zone inundated by the 26 December 2004 tsunami in Thailand

The 26 December 2004 tsunami covered significant portion of a coastal zone with a blanket of potentially contaminated sediments. In this report are presented results on mercury concentrations in sediments deposited by the tsunami in a coastal zone of Thailand. Since the total mercury concentrations are insufficient to assess mercury mobility and bioavailability in sediment, its fractionation was applied. Sediments were sampled within 50 days after the event and analyzed by sequential extraction method. The procedure of sequential extraction involved five subsequent stages performed with solutions of chloroform, deionized water, 0.5 M HCl, 0.2 M NaOH, and aqua regia. The mean concentration of total mercury in sediments was 119 ± 50 ng g⁻¹ dry mass (range 66–230). The fractionation revealed that mercury is mainly bound to the least bioavailable sulphides 75 ± 6% (range 62–86), organomercury compounds 14 ± 7% (range 4–26), and humic matter 9 ± 7% (range 1–27). The lowest contributions bring fractions of water-soluble mercury 0.8 ± 1.0% (range 0.1–3.6) and acid soluble mercury 0.9 ± 0.5% (range 0.2–2.1). Although, the total mercury content is similar in a reference sample and in the tsunami sediments, the highly toxic organomercury fraction contribution is higher in the latter. The results were compared with chemical and sedimentological properties of the sediments but no significant correlations were obtained between them.     

Three‐parameter discontinuous distributions for hydrological samples with zero values

A consistent approach to the frequency analysis of hydrologic data in arid and semiarid regions, i.e. the data series containing several zero values (e.g. monthly precipitation in dry seasons, annual peak flow discharges, etc.), requires using discontinuous probability distribution functions. Such an approach has received relatively limited attention. Along the lines of physically based models, the extensions of the Muskingum‐based models to three parameter forms are considered. Using 44 peak flow series from the USGS data bank, the fitting ability of four three‐parameter models was investigated: (1) the Dirac delta combined with Gamma distribution; (2) the Dirac delta combined with two‐parameter generalized Pareto distribution; (3) the Dirac delta combined with two‐parameter Weibull (DWe) distribution; (4) the kinematic diffusion with one additional parameter that controls the probability of the zero event (KD3). The goodness of fit of the models was assessed and compared both by evaluation of discrepancies between the results of both estimation methods (i.e. the method of moments (MOM) and the maximum likelihood method (MLM)) and using the log of likelihood function as a criterion. In most cases, the DWe distribution with MLM‐estimated parameters showed the best fit of all the three‐parameter models. Copyright © 2005 John Wiley & Sons, Ltd.     

Holocene paleohydrological reconstruction of Lake Strzeszyńskie (western Poland) and its implications for the central European climatic transition zone

Western Poland is located in the central European climatic transition zone, which separates the mild and humid Atlantic climate of Western Europe and the East European continental climate. This region is sensitive to lateral shifts of the European climate zones and is particularly suitable for reconstructing Holocene climate variability. This paper presents detailed analyses of the sedimentary record from Lake Strzeszyńskie since the Late Pleistocene. These include smear-slide and thin-section observations, X-ray fluorescence core scanning, magnetic susceptibility measurements, pollen analyses, and radiocarbon dating. The sediment record reveals three distinct sedimentary units consisting of: (1) an alternation of sand layers and laminated silt and clay deposits accumulated prior to 14,600 cal yr BP; (2) faintly laminated calcareous sediments intercalated with organic matter-rich layers deposited between 14,600 and 10,200 cal yr BP; and (3) massive calcareous mud deposited after 10,200 cal yr BP. The Holocene period is marked by nine phases of organic-rich sedimentation and enhanced Fe deposition, which occurred at ca. 10.1, 9.3, 6.4–6.1, 5.5–5.1, 4.7–4.5, 2.7–2.4, 1.3–1.2, 0.8–0.6, 0.4–0.2 kyr cal BP. These phases are associated with high lake levels and correspond with wet periods recognized in several other records from Poland and central Europe. These phases partly coincide with North Atlantic cold periods, which may suggest that high lake levels are triggered by an ocean-continent linking mechanism.     

DEVEX-disdrometer evaluation experiment: Basic results and implications for hydrologic studies

Increasing our understanding of the small scale variability of drop size distributions (DSD), and therefore of several bulk characteristics of rainfall processes, has major implications for our interpretation of the remote sensing based estimates of precipitation and its uncertainty. During the spring and summer of 2002 the authors conducted the DEVEX experiment (disdrometer evaluation experiment) to compare measurements of natural rain made with three different types of disdrometers collocated at the Iowa City Municipal Airport in Iowa City, Iowa in the Midwestern United States. This paper focuses on the evaluation of the instruments rather than analysis of the hydrometeorological aspects of the observed events. The comparison demonstrates discrepancies between instruments. The authors discuss the systematic and random effects in terms of rainfall quantities, drop size distribution properties, and the observed drop size vs. velocity relationships. Since the instruments were collocated, the effects of the natural variability of rain are reduced some with time integration, isolating the instrumental differences. The authors discuss the status of DSD measurement technologies and the implications for a range of hydrologic applications from remote sensing of rainfall to atmospheric deposition to soil erosion and sediment transport in the environment. The data set collected during the DEVEX experiment is made available to the research community.     

Clustering and visualization of earthquake data in a grid environment

We present a web client-server service WEB-IS, which we have developed for remote analysis and visualization of seismic data consisting of both small magnitude events and large earthquakes. We show that the problem-solving environment (PSE) intended for prediction of large magnitude earthquakes can be based on this WEB-IS idea. The clustering schemes, feature generation, feature extraction techniques and rendering algorithms form a computational framework of this environment. On the other hand, easy and fast access both to the seismic data distributed among distant computing resources and to computational and visualization resources can be realized in a GRID framework. We discuss the usefulness of NaradaBrokering (iNtegrated Asynchronous Real-time Adaptive Distributed Architecture) as a middleware, allowing for flexibility and high throughput for remote visualization of geophysical data. The WEB-IS functionality was tested both on synthetic and the actual earthquake catalogs. We consider the application of similar methodology for tsunami alerts.     

Kinematics from spectroscopy with a wide slit: detecting black holes in galaxy centres

We consider long-slit emission-line spectra of galactic nuclei when the slit is wider than the instrumental point spread function, and the target has large velocity gradients. The finite width of the slit generates complex distributions of brightness at a given spatial point in the measured spectrum, which can be misinterpreted as coming from additional physically distinct nuclear components. We illustrate this phenomenon for the case of a thin disc in circular motion around a nuclear black hole (BH). We develop a new method for estimating the mass of the BH that exploits a feature in the spectrum at the outer edge of the BH's sphere of influence, and therefore gives higher sensitivity to BH detection than traditional methods. Moreover, with this method we can determine the BH mass and the inclination of the surrounding disc separately, whereas the traditional approach to BH estimation requires two long-slit spectra to be taken. We show that, with a given spectrograph, the detectability of a BH depends on the sense of rotation of the nuclear disc. We apply our method to estimate the BH mass in M84 from a publicly available spectrum, and recover a value four times lower than that published previously from the same data.     

Comparison of Two Nonstationary Flood Frequency Analysis Methods within the Context of the Variable Regime in the Representative Polish Rivers

Changes in river flow regime resulted in a surge in the number of methods of non-stationary flood frequency analysis. Common assumption is the time-invariant distribution function with time-dependent location and scale parameters while the shape parameters are time-invariant. Here, instead of location and scale parameters of the distribution, the mean and standard deviation are used. We analyse the accuracy of the two methods in respect to estimation of time-dependent first two moments, time-invariant skewness and time-dependent upper quantiles. The method of maximum likelihood (ML) with time covariate is confronted with the Two Stage (TS) one (combining Weighted Least Squares and L-moments techniques). Comparison is made by Monte Carlo simulations. Assuming parent distribution which ensures the asymptotic superiority of ML method, the Generalized Extreme Value distribution with various values of linearly changing in time first two moments, constant skewness, and various time-series lengths are considered. Analysis of results indicates the superiority of TS methods in all analyzed aspects. Moreover, the estimates from TS method are more resistant to probability distribution choice, as demonstrated by Polish rivers’ case studies.