Review of the Different Sources of Uncertainty in Single Polarization Radar-Based Estimates of Rainfall

It is well acknowledged that there are large uncertainties associated with radar-based estimates of rainfall. Numerous sources of these errors are due to parameter estimation, the observational system and measurement principles, and not fully understood physical processes. Propagation of these uncertainties through all models for which radar-rainfall are used as input (e.g., hydrologic models) or as initial conditions (e.g., weather forecasting models) is necessary to enhance the understanding and interpretation of the obtained results. The aim of this paper is to provide an extensive literature review of the principal sources of error affecting single polarization radar-based rainfall estimates. These include radar miscalibration, attenuation, ground clutter and anomalous propagation, beam blockage, variability of the Z–R relation, range degradation, vertical variability of the precipitation system, vertical air motion and precipitation drift, and temporal sampling errors. Finally, the authors report some recent results from empirically-based modeling of the total radar-rainfall uncertainties. The bibliography comprises over 200 peer reviewed journal articles.     

Local tomography troposphere model over mountains area

The term GNSS meteorology refers to the utilization of the Global Navigation Satellite System's (GNSS) radio signals to derive information about the state of the troposphere. GNSS tomography allows to resolve the spatial structure and temporal behavior of the tropospheric water vapor. This paper presents the verification of GNSS tomography over dense local GNSS network. The paper addresses the problem of obtaining a stable tomographic solution from an ill-conditioned system of linear equations. The main interests are in suitable horizontal and vertical resolution in given conditions. Here the Moore–Penrose pseudo inverse of variance–covariance matrix is used. The minimum constraints solution is obtained with no additional assumptions. The results are validated with the help of simulated weather conditions. Three various scenarios are tested. As general output of this paper the optimal model construction scheme is presented with possible further improvements. The verification of the tomography model based on the local GPS KARKONOSZE, situated in the Karkonosze mountains area in Poland.     

Simulations of Gas Flow from a Galactic Disk Towards the Black-Hole Accretion Disk

We report preliminary results of hydrodynamical modeling of gas flow in a galaxy potential towards a central massive black hole. We use a bar-like perturbation on the large scale in order to cause the initial inflow, and we concentrate our attention on the inner parts of the galaxy, where the potential becomes axisymmetric, or where it is dominated by an inner, secondary bar. Our high-resolution grid-based algorithm allows us to get a detailed picture of gas dynamics down to about 10 pc from the galaxy center, where the black hole becomes dominant. We find that inner bars may not increase the gas inflow, but for certain potential and gas parameters, gas flows to the center in a spiral shock. This revised version was published online in September 2006 with corrections to the Cover Date.     

Complementary aspects of linear flood routing modelling and flood frequency analysis

Similarity and differences between linear flood routing modelling (LFRM) and flood frequency analysis (FFA) techniques are presented. The moment matching used in LFRM to approximate the impulse response function (IRF) was applied in FFA to derive the asymptotic bias caused by the false distribution assumption. Proceeding in this way, other estimation methods were used as approximation methods in FFA to derive the asymptotic bias. Using simulation experiments, the above investigation was extended to evaluate the sampling bias. As a feedback, the maximum likelihood method (MLM) can be used for approximating linear channel response (LCR) by the IRFs of conceptual models. Impulse responses of the convective diffusion and kinematic diffusion models were applied and developed as FFA models. Based on kinematic diffusion LFRM, the equivalence of estimation problems of discrete‐continuous distribution and single‐censored sample are shown both for the method of moments (MOM) and the MLM. Hence, the applicability of MOM is extended for the case of censored samples. Owing to the complexity and non‐linearity of hydrological systems and resulting processes, the use of simple models is often questionable. The rationale of simple models is discussed. The problems of model choice and overparameterization are common in mathematical modelling and FF modelling. Some results for the use of simple models in the stationary FFA are presented. The problems of model discrimination are then discussed. Finally, a conjunction of linear stochastic processes and LFRM is presented. The influence of river courses on stochastic properties of the runoff process is shown by combining Gaussian input with the LCR of the simplified Saint Venant model. It is shown that, from the classification of the ways of their development, both LFRM and FFA can benefit. Copyright © 2006 John Wiley & Sons, Ltd.     

Sediment accumulation rates in subpolar fjords – Impact of post-Little Ice Age glaciers retreat,Billefjorden, Svalbard

The Little Ice Age (∼1600–1900 AD) and 20th century sediment accumulation rates in Billefjorden, a subpolar fjord on Svalbard, were reconstructed by applying ²¹⁰Pb, ¹³⁷Cs and AMS ¹⁴C datings. The modern sediment accumulation rate decreases from more than 0.39 cm y⁻¹ at the fjord head to 0.08 cm y⁻¹ close to the fjord mouth. However, during the Little Ice Age the sediments accumulated at a much lower rate of 0.02 cm y⁻¹ in the central fjord basin. This difference is most likely related to the rapid retreat of glaciers during the 20th century, when most of them withdrew up to 2 km. The post-Little Ice Age increases in temperature and a negative glacier mass balance resulted in a larger meltwater discharge transferring substantial amounts of sediments released from the glaciers, as well as those eroded from previously stored unconsolidated glacial sediments. A comparison of data from the subpolar fjords of Svalbard suggests that the increase in the sediment accumulation rate is a common trend, and further increases might be expected if climate warming continues. The properties of the fjord sediments (grain size, IRD, coarse-fraction composition, clay mineralogy) from the Little Ice Age and the 20th century showed no distinct differences. The change in the accumulation rate may be the most evident sedimentary record of this climatic change.     

Effects of rainy season on mobilization of contaminants from tsunami deposits left in a coastal zone of Thailand by the 26 December 2004 tsunami

Study on contamination of tsunami sediments deposited on 26 December 2004 conducted shortly after the tsunami in coastal zone of Thailand revealed elevated contents of salts in water-soluble and some heavy metals and arsenic in bioavailable fractions (Szczuciński et al. in Env Geol 49:321–331, 2005). Few months later rainy season started and effected in total rainfall of over 3,300 mm. This paper presents results of survey repeated 1 year after the tsunami. To assess the effects of rainy season on mobilization of previously determined potential contaminants, the same locations were sampled again and analysed with the same methods. The tsunami deposit layer was well preserved but in many locations the sediments were coarser than just after tsunami due to washing out of finer fractions. The water-soluble salts contents were strongly reduced after the rainy season. However, the concentrations of acid leachable heavy metals and metalloids were still elevated in comparison to reference sample from an area not impacted by tsunami. It is possible that the metals and metalloids are successively moved to more bioavailable fraction from forms which were more resistant to mobilization.     

Impact of different regression frameworks on the estimation of the scaling properties of radar rainfall

Rainfall is characterized by high variability both in space and time. Despite continuous technological progress, the available instruments that are used to measure rainfall across several spatio-temporal scales remain inaccurate. To remedy this situation, scaling relationships of spatial rainfall offer the potential to link the observed or predicted precipitation quantities at one scale to those of interest at other scales. This paper focuses on the estimation of the spatial rainfall scaling functions. Standard scaling analysis constructed by means of the ordinary least squares method often violates such basic assumptions implicit in its use and interpretation as homoschedasticity, independence, and normality of the errors. Consequently, the authors consider alternative regression frameworks i.e. bootstrapping regression, semi parametric linear model, and multilevel normal linear model to show how these different approaches exert a significant impact on the multifractal analysis of radar rainfall. In addition, the uncertainties associated with the construction of the scaling function due solely to the regression procedure are quantified. The radar data come from the polarimetric C-band weather radar located in Rome, Italy, and the scaling properties are computed for a square domain centred on the radar site with a side length of 128 km and a finest resolution of 1 km².     

Impulse response of the kinematic diffusion model as a probability distribution of hydrologic samples with zero values

It is hypothesized that the unit impulse response of a linearized kinematic diffusion (KD) model is a probability distribution suitable for frequency analysis of hydrologic samples with zero values. Such samples may include data on monthly precipitation in dry seasons, annual low flow, and annual maximum peak discharge observed in arid and semiarid regions. The hypothesized probability distribution has two parameters, which are estimated using the methods of moments (MOM) and maximum likelihood (MLM). Also estimated are errors in quantiles for MOM and MLM. The distribution shows an equivalency of MOM and MLM with respect to the mean value—an important property for ML-estimation in the case of the unknown true distribution function. The hypothesized KD distribution is tested on 44 discharge data series and compared with the Muskingum-like (M-like) probability distribution function. A comparison of empirical distribution with KD and M-like distributions shows that MOM better reproduces the upper tail of the distribution, while MLM is more robust for higher sample values and more conditioned on the value of the probability of the zero value event. The KD-model is suitable for frequency analysis of short samples with zero values and it is more universal than the M-like model as its modal value cannot be only equaled to zero value but also to any positive value.     

Contamination of tsunami sediments in a coastal zone inundated by the 26 December 2004 tsunami in Thailand

Tsunami sediments deposited in a coastal zone of Thailand by the 26 December 2004 tsunami wave were sampled within 50 days after the event. All surface and ground waters in tsunami- inundated zone revealed significant salinity at that time. The tsunami sediments, composed mainly of fine to medium sand, contain significantly elevated contents of salts (Na⁺, K⁺, Ca⁺², Mg⁺², Cl and SO ₄ ⁻² ) in water-soluble fraction, and of Cd, Cu, Zn, Pb in the bioavailable fraction and As in the exchangeable fraction in relation to the reference sample. The origin of contaminants is marine, as well as litho- and anthropogenic. The salts and Pb, Zn and Cu reveal high correlation to each other and to the mean grain size (pore size and porosity). Serious environmental hazard exists in that region because, due to gentle morphology, there is a risk of migration of the contaminants into ground waters and food chain.