Ocean surface wave measurements from fully polarimetric SAR imagery

A new method for the retrieval of ocean wave parameters from SAR imagery is developed,based on the shape-from-shading(SFS)technique.Previously,the SFS technique has been used in the reconstruction of 3D landform information from SAR images,in order to generate elevation maps of topography for land surfaces.Here,in order to retrieve ocean wave characteristics,we apply the SFS methodology,together with a method to orient the angular measurements of the azimuth slope and range slope,in the measurement of ocean surface waves.This method is applied to high resolution fine-quad polarization mode(HH,VV,VH and HV)C-band RADARSAT-2 SAR imagery,in order to retrieve ocean wave spectra and extract wave parameters.Collocated in situ buoy measurements are used to validate the reliability of this method.Results show that the method can reliably estimate wave height,dominant wave period,dominant wave length and dominant wave direction from C-band SAR images.The advantage of this method is that it does not depend on modulation transfer functions(MTFs),in order to measure ocean surface waves.This method can be used in monitoring ocean surface wave propagation through open water areas into ice-covered areas,especially the marginal ice zone(MIZ)in polar oceans.     

A multi‐source precipitation estimation approach to fill gaps over a radar precipitation field: a case study in the Colorado River Basin

The present work develops an approach to seamlessly blend satellite, available radar, climatological and gauge precipitation products to fill gaps in ground‐based radar precipitation field. To mix different precipitation products, the error of any of the products relative to each other should be removed. For bias correction, the study uses an ensemble‐based method that aims to estimate spatially varying multiplicative biases in SPEs using a radar precipitation product. A weighted successive correction method (SCM) is used to make the merging between error corrected satellite and radar precipitation estimates. In addition to SCM, we use a combination of SCM and Bayesian spatial model for merging the rain gauges (RGs) and climatological precipitation sources with radar and SPEs. We demonstrated the method using a satellite‐based hydro‐estimator; a radar‐based, stage‐II; a climatological product, Parameter‐elevation Regressions on Independent Slopes Model and a RG dataset for several rain events from 2006 to 2008 over an artificial gap in Oklahoma and a real radar gap in the Colorado River basin. Results show that: the SCM method in combination with the Bayesian spatial model produced a precipitation product in good agreement with independent measurements. The study implies that using the available radar pixels surrounding the gap area, RG, Parameter‐elevation Regressions on Independent Slopes Model and satellite products, a radar‐like product is achievable over radar gap areas that benefit the operational meteorology and hydrology community. Copyright © 2013 John Wiley & Sons, Ltd.     

准时间可预报复发行为与断裂带分段发震概率估计

反不确定性引入“时间可预报模式”，可将一次地震之后的平静时间表示成与这次地震位错量在小呈正相关的随机变量。称这种带有不确定性的地震原地复发行为为“准时间可预报行为”。对于历史地震资料，准时间可预报复发行为可由地震后平静时间的对数与地震烈度的回归方程。文中给出了估计一条枯断裂带不同段落以上一次地震烈度值为背景的平均复发时间间隔的方法，以及可用 于对未来地震潜势进行不确定评价的实时概率模型，并以鲜水河     

Free core nutation period inferred from the gravity measurements at Józefosław

The Free Core Nutation (FCN) is an important eigenmode which affects both Earth rotation and body tide. The FCN parameters, the resonance period and the quality factor are important for understanding the dynamics of the Earth at nearly diurnal periods. Those parameters are usually estimated either from the Very Long Baseline Interferometry (VLBI) observations of nutation, or from the tidal gravity measurements. In this paper we investigate the determination of the FCN parameters from gravity records covering a period of more than three years, collected with the use of a LaCoste&Romberg Earth Tide no. 26 gravimeter, located at Józefos?aw observatory near Warsaw. From the resonant enhancements of gravimetric factors and phases of diurnal tidal gravity waves, we could infer the FCN period to be equal to 430 sidereal days. This result is in very good agreement with previous gravimetric and VLBI nutation results, confirming the discrepancy in the dynamic flattening of the outer liquid core from its theoretical value based on the hydrostatic equilibrium assumption. The estimated FCN quality factor (Q ≈ 1300) is considerably smaller than the VLBI nutation result, which confirms that the local gravity measurements are more sensitive than VLBI global analyses to site-dependent phenomena (such as atmospheric and indirect ocean tidal effects). We also investigated the importance of gravimetric corrections in the FCN analysis, including numerical tests and simulations. This allowed us to estimate the uncertainty of FCN parameters due to improper or incomplete set of environmental corrections. We took also into account the impact of gravimetric factor errors and tidal wave selection on estimated FCN parameters. We demonstrated that despite relatively noisy measurements due to unfavorable gravimeter location, we were able to obtain very good results in case when proper correction and tidal wave selection were applied.     

Surface heat fluxes in the Western Equatorial Pacific Ocean

Estimates of the components of the surface heat flux in the Western Equatorial Pacific Ocean are presented for a 22-day period, together with a critical analysis of the errors. It is shown that the errors in latent heat, and solar and longwave radiation fluxes, dominate the net heat flux for this period. It is found that the net heat flux into the ocean over the 22-day period is not significantly different from zero. It is also demonstrated that because of the variability in daily averaged values of solar radiation and the latent heat of evaporation, a large number of independent flux measurements will be required to determine with confidence the climatological net heat flux in this region. The variability of latent fluxes over the 22-day period suggest that climatological estimates based on monthly mean observations may lead to a significant underestimate of the latent heat flux.     

Predicting streamflow distributions and flow duration curves from landscape and climate

Characterizing the probability distribution of streamflows in catchments lacking in discharge measurements represents an attractive prospect with consequences for practical and scientific applications, in particular water resources management. In this paper, a physically-based analytic model of streamflow dynamics is combined with a set of water balance models and a geomorphological recession flow model in order to estimate streamflow probability distributions based on catchment-scale climatic and morphologic features. The models used are described and the novel parameterization approach is elaborated on. Starting from rainfall data, potential evapotranspiration and digital terrain maps, the method proved capable of capturing the statistics of observed streamflows reasonably well in 11 test catchments distributed throughout the United States, east of the rocky mountains. The method developed offers a unique approach for estimating probability distribution of streamflows where only climatic and geomorphologic features are known.     

Adjustment of wind-drift effect for real-time systematic error correction in radar rainfall data

An effective bias correction procedure using gauge measurement is a significant step for radar data processing to reduce the systematic error in hydrological applications. In these bias correction methods, the spatial matching of precipitation patterns between radar and gauge networks is an important premise. However, the wind-drift effect on radar measurement induces an inconsistent spatial relationship between radar and gauge measurements as the raindrops observed by radar do not fall vertically to the ground. Consequently, a rain gauge does not correspond to the radar pixel based on the projected location of the radar beam. In this study, we introduce an adjustment method to incorporate the wind-drift effect into a bias correlation scheme. We first simulate the trajectory of raindrops in the air using downscaled three-dimensional wind data from the weather research and forecasting model (WRF) and calculate the final location of raindrops on the ground. The displacement of rainfall is then estimated and a radar–gauge spatial relationship is reconstructed. Based on this, the local real-time biases of the bin-average radar data were estimated for 12 selected events. Then, the reference mean local gauge rainfall, mean local bias, and adjusted radar rainfall calculated with and without consideration of the wind-drift effect are compared for different events and locations. There are considerable differences for three estimators, indicating that wind drift has a considerable impact on the real-time radar bias correction. Based on these facts, we suggest bias correction schemes based on the spatial correlation between radar and gauge measurements should consider the adjustment of the wind-drift effect and the proposed adjustment method is a promising solution to achieve this.     

Estimation of atmospheric predictability for multivariable system using information theory in nonlinear error growth dynamics

To estimate atmospheric predictability for multivariable system, based on information theory in nonlinear error growth dynamics, a quantitative method is introduced in this paper using multivariable joint predictability limit (MJPL) and corresponding single variable predictability limit (SVPL). The predictability limit, obtained from the evolutions of nonlinear error entropy and climatological state entropy, is not only used to measure the predictability of dynamical system with the constant climatological state entropy, but also appropriate to the case of climatological state entropy changed with time. With the help of daily NCEP-NCAR reanalysis data, by using a method of local dynamical analog, the nonlinear error entropy, climatological state entropy, and predictability limit are obtained, and the SVPLs and MJPL of the winter 500-hPa temperature field, zonal wind field and meridional wind field are also investigated. The results show that atmospheric predictability is well associated with the analytical variable. For single variable predictability, there exists a big difference for the three variables, with the higher predictability found for the temperature field and zonal wind field and the lower predictability for the meridional wind field. As seen from their spatial distributions, the SVPLs of the three variables appear to have a property of zonal distribution, especially for the meridional wind field, which has three zonal belts with low predictability and four zonal belts with high predictability. For multivariable joint predictability, the MJPL of multivariable system with the three variables is not a simple mean or linear combination of its SVPLs. It presents an obvious regional difference characteristic. Different regions have different results. In some regions, the MJPL is among its SVPLs. However, in other regions, the MJPL is less than its all SVPLs.     

CMBEAR: Python-Based Recharge Estimator Using the Chloride Mass Balance Method in Australia

The chloride mass balance (CMB) method is widely used to estimate long-term rates of groundwater recharge. In regions where surface water runoff is negligible, recharge can be estimated using measurements of chloride concentrations of groundwater and precipitation, and an estimate of long-term average rainfall. This paper presents the Chloride Mass Balance Estimator of Australian Recharge (CMBEAR), a Jupyter (Python) Notebook that is set up to rapidly apply the CMB method using gridded maps of chloride deposition rates across the Australian continent. For an Australian context, the chloride deposition rate and rainfall maps have been provided. Thus, CMBEAR requires only a spreadsheet with the groundwater chloride concentration, the latitude and longitude of the sample location, and some simple user inputs. CMBEAR may be easily applied in other regions, providing that a gridded chloride deposition map is available. Recharge estimates from CMBEAR are compared against published applications of the CMB method. CMBEAR is also applied to a large dataset from the Northern Territory and is used to produce a gridded map of recharge for western Victoria. CMBEAR provides a reproducible and straightforward approach to apply the CMB method to estimate groundwater recharge.     

PART I: Theoretical Site Response Estimation for Microzoning Purposes

— We estimate the theoretical site response along seven cross sections located in the city of Thessaloniki (Greece). For this purpose the 2-D structural models used are based on the known geometry and the dynamic soil properties derived from borehole measurements and other geophysical techniques. Several double-couple sources have been employed to generate the seismic wavefield, and a hybrid method that combines the modal summation with finite differences, has been deployed to produce synthetic accelerograms to a maximum frequency of 6 Hz for all components of motion. The ratios between the response spectra of signals derived for the 2-D local model and the corresponding spectra of signals derived for the 1-D bedrock reference model at the same site, allow us to estimate the site response due to lateral heterogeneities. We interpret the results in terms of both geological and geometrical features of the models and of the characteristics of the wave propagation. The cases discussed confirm that the geometry and depth of the rock basement, along with the impedance contrast, are responsible for ground amplification phenomena such as edge effects and generation and entrapment of local surface waves. Our analysis also confirms that the peak ground acceleration is not well correlated with damage and that a substantially better estimator for possible damage is the spectral amplification.     

Fast seismic horizon reconstruction based on local dip transformation

We propose a fast and real-time interactive method to reconstruct a seismic horizon with respect to a set of picked input points. The reconstruction domain is subdivided in quadrilateral domains which are determined from input points while the entire horizon is obtained part-by-part by juxtaposing independent partial reconstructions. Each quadrilateral domain is mapped onto a rectangular domain on which a non-linear partial derivative equation relied on local dip is solved by an iterative process based on a Poisson equation. The key point is the transformation of the local dip which allows the carrying out of a direct Fourier method with a low computational cost.     

Parameterization of synoptic weather systems in the South Atlantic Bight for modeling applications

An event based, long-term, climatological analysis is presented that allows the creation of coastal ocean atmospheric forcing on the coastal ocean that preserves both frequency of occurrence and event time history. An algorithm is developed that identifies individual storm event (cold fronts, warm fronts, and tropical storms) from meteorological records. The algorithm has been applied to a location along the South Atlantic Bight, off South Carolina, an area prone to cyclogenesis occurrence and passages of atmospheric fronts. Comparison against daily weather maps confirms that the algorithm is efficient in identifying cold fronts and warm fronts, while the identification of tropical storms is less successful. The average state of the storm events and their variability are represented by the temporal evolution of atmospheric pressure, air temperature, wind velocity, and wave directional spectral energy. The use of uncorrected algorithm-detected events provides climatologies that show a little deviation from those derived using corrected events. The effectiveness of this analysis method is further verified by numerically simulating the wave conditions driven by the characteristic wind forcing and comparing the results with the wave climatology that corresponds to each storm type. A high level of consistency found in the comparison indicates that this analysis method can be used for accurately characterizing event-based oceanic processes and long-term storm-induced morphodynamic processes on wind-dominated coasts.     

A method for simulating sharp fluid interfaces in groundwater flow

We present a numerical model for two-phase porous media flow, where the phases are separated by a sharp interface. The model is based on a unified pressure equation, and an advection equation for tracking a pseudo-concentration function. The zero-level set of this function defines the interface between the fluids. The finite element method is used for spatial discretization, with local grid refinements in the vicinity of the interface. Examples on applications involving moving interface and steady-state seepage problems are investigated.     

Spatial modelling of palsa mires in relation to climate in northern Europe

Palsa mires are mire complexes that occur in the Northern Hemisphere, representing one of the most marginal permafrost features at the outer limit of the permafrost zone. A climate‐based spatial model is presented for the distribution of palsa mires in northern Europe. The model is based on an extensive spatial data of palsa mires and climatological variables from 1913 grid cells in an area of c. 240 000 km². Generalized linear modelling (GLM) with curvilinear and interaction terms is used to derive the palsa mire–climate relationships. The ?nal model correctly classi?ed 77·6 per cent of the palsa mire presence squares. The results indicate a positive association of the distribution of palsa mires with increasing frost number and continentality, whereas precipitation and temperature showed a negative correlation with the distribution of palsa mires. Additionally, interaction of thawing degree days and summer time precipitation showed a negative association. Climatologically, the optimum areas of palsa mires occur in areas of low precipitation (<450 mm) and a mean annual temperature between ?3 °C and ?5 °C. Potential reasons for the performance of the model and the sensitivity of palsa mires to climate change are discussed. The application of a GIS‐based generalized linear modelling as used here provides a versatile method to study the distribution of different geomorphological phenomena across climatological gradients. Copyright © 2004 John Wiley & Sons, Ltd.     

Testing the Quality of Sea-Level Data Using the GECCO Adjoint Assimilation Approach

Besides providing an estimate of the changing ocean state, an important result of the dynamically consistent estimating the circulation and climate of the ocean (ECCO) state estimate approach is the provision of a posterior model–data residuals which contain important information about elements in the assimilated observations that are inconsistent with the model dynamics or with the information present in other ocean data sets that are being used as constraints in the assimilation procedure. Based on decreased GECCO2 model–data residuals, upon using the altimeter data through the ESA climate change initiative (cci) sea-level (SL) project, we show here that the recently reprocessed ESA SL_cci altimeter data set (SL1) has been improved relative to the earlier AVISO altimetry data set and is now more consistent with the GECCO2 estimate and with the information about the changing ocean state embedded in other ocean data sets. The improvement can be shown to exist separately for both TOPEX/POSEIDON and ERS data sets. The study reveals that especially in regions characterized by small sea surface height (SSH) variability and small signal-to-noise ratio in the SSH data, improvements can be on the order of 30% of previously existing model–data residuals. However, in some regions we can find degradations, particulary in those where GECCO2 has little skill in representing the altimeter data and where evaluation of the products with GECCO2 is thus not advisable. Upon the assimilation of the new SL1 data set, the GECCO2 synthesis was further improved. However, adding the sea surface temperature (SST) from the SST_cci project as additional constrain, no further impact can be identified.     

Application of random sets to model uncertainties of natural entities extracted from remote sensing images

Remotely sensed images as a major data source to observe the earth, have been extensively integrated into spatial-temporal analysis in environmental research. Information on spatial distribution and spatial-temporal dynamic of natural entities recorded by series of images, however, usually bears various kinds of uncertainties. To deepen our insight into the uncertainties that are inherent in these observations of natural phenomena from images, a general data modeling methodology is developed to embrace different kinds of uncertainties. The aim of this paper is to propose a random set method for uncertainty modeling of spatial objects extracted from images in environmental study. Basic concepts of random set theory are introduced and primary random spatial data types are defined based on them. The method has been applied to dynamic wetland monitoring in the Poyang Lake national nature reserve in China. Four Landsat images have been used to monitor grassland and vegetation patches. Their broad gradual boundaries are represented by random sets, and their statistical mean and median are estimated. Random sets are well suited to estimate these boundaries. We conclude that our method based on random set theory has a potential to serve as a general framework in uncertainty modeling and is applicable in a spatial environmental analysis.     

基于有限元方法的陆海大地水准面衔接

大陆上用重力数据和GPS水准数据确定(似)大地水准面,海洋上用卫星测高数据确定(似)大地水准面.由于沿海地区和近岸海域往往缺少完好的重力数据,近岸海域卫星测高数据质量相对较差,两类大地水准面在陆海相接区域精度偏低且存在拼合差.纯几何方法拟合陆海局部区域大地水准面,不能顾及大地水准面的物理特性,拟合结果不稳定.顾及到大地水准面的物理特性,依据其在局部所应满足的数学物理方程,拟合陆海局部区域大地水准面问题,转化为Laplace第一边值问题.讨论了有限元法衔接陆海局部区域大地水准面的数学思想,给出了相应的数学模型.     

Nonlinear estimation of spatial distribution of rainfall — An indicator cokriging approach

Indicator cokriging (Journel 1983) is examined as a tool for real-time estimation of rainfall from rain gage measurements. The approach proposed in this work obviates real-time estimation of real-time statistics of rainfall by using ensemble or climatological statistics exclusively, and reduces computational requirements attendant to indicator cokriging by employing only a few auxiliary cutoffs in estimation of conditional probabilities. Due to unavailability of suitable rain gage measurements, hourly radar rain fall data were used for both indicator covariance estimation and a comparative evaluation. Preliminary results suggest that the indicator cokriging approach is clearly superior to its ordinary kriging counterpart, whereas the indicator kriging approach is not. The improvement is most significant in estimation of light rainfall, but drops off significantly for heavy rainfall. The lack of predictability in spatial estimation of heavy rainfall is borne out in the integral scale of indicator correlation: peaking to its maximum for cutoffs near the median, indicator correlation scale becomes increasingly smaller for larger cutoffs of rainfall depth. A derived-distribution analysis, based on the assumption that radar rainfall is a linear sum of ground-truth and a random error, suggests that, at low cutoffs, indicator correlation scale of ground-truth can significantly differ from that of radar rainfall, and points toward inclusion of rainfall intermittency, for example, within the framework proposed in this work.     

海潮对卫星重力场恢复的影响

本文讨论了海潮对卫星重力测量的影响问题. 首先介绍了海潮对卫星重力测量影响的基本理论;采用FES02和TPXO6海潮模型计算了海潮负荷对卫星重力结果前60阶的影响;并用两个模型之间的差异作为海潮模型精度的估计量,据此计算了海潮模型误差对卫星重力结果的影响. 与GRACE恢复的重力场精度的比较说明：海潮对重力场40阶以下的影响都超过了目前重力场恢复精度;尽管由于卫星测高技术的发展,海潮模型的精度有了很大的提高,但目前的全球海潮模型用于GRACE重力场恢复的前12阶的改正还是不够精确. 另外,我们也利用中国东海和南海潮汐资料以及FES02海潮模型讨论了中国近海潮汐效应对GRACE观测的影响. 结果说明该影响与海潮模型的误差相当. 这反映了当前海潮模型的不确定度,因此通过结合全球验潮站资料有望提高海潮对卫星重力测量的改正精度.