Monitoring the Kuroshio Extension with Dynamically Constrained Synthesis of the Acoustic Tomography, Satellite Altimeter and in situ Data

A finite-difference quasigeostrophic (QG) model of an open ocean region has been employed to produce a dynamically constrained synthesis of acoustic tomography and satellite altimetry data with in situ observations. The assimilation algorithm is based upon the 4D variational data interpolation scheme controlled by the model's initial and boundary conditions. The data sets analyzed include direct and differential travel times measured at the array of five acoustic transceivers deployed by JAMSTEC in the region of the Kuroshio Extension in 1997, Topex/Poseidon altimetry, CTD soundings, and ADCP velocity profiles. The region monitored is located within the area 27.5°–36.5°N, 143°–155°. The results of assimilation show that mesoscale variability can be effectively reconstructed by five transceivers measuring direct and reciprocal travel times supported by relatively sparse in situ measurements. The misfits between model and data lie within the observational error bars for all the data types used in assimilation. We have compared the results of assimilation with the statistical inversion of travel time data and analyzed energy balances of the optimized model solution. Energy exchange between the depth-averaged and shear components of the observed currents reveals a weak decay of the barotropic mode at the rate of 0.2 ± 0.7⋅10⁻⁵ cm²/s³ due to topographic interaction. Mean currents in the region are unstable with an estimate of the available potential energy flux from the mean current to the eddies of 4.7 ± 2.3⋅10⁻⁵ cm²/s³. Kinetic energy transition has the same sign and is estimated as 2.8 ± 2.5⋅10⁻⁵ cm²/s³. Potential enstrophy is transferred to the mesoscale at a rate of 5.5 ± 2.7⋅10⁻¹⁸ s⁻³. These figures provide observational evidence of the properties of free geostrophic turbulence which were predicted by theory and observed in numerical experiments. This revised version was published online in July 2006 with corrections to the Cover Date.     

Nitrogen utilisation by size‐fractionated phytoplankton assemblages associated with an upwelling event off Westland,New Zealand

Abstract

Uptake rates of ammonium (NH₄ ⁺ ), nitrate (NO₃ ^? ), and urea by three subgroups of phytoplankton (< 200, < 20, < 2 μm) off Westland, were measured using ¹⁵ N tracer techniques in midwinter 1988, after a recent upwelling. For all size fractions at surface irradiance (I₁₀₀), nitrogen (N) was taken up primarily as NO₃ ^?. This accounted for 67–85% of total N uptake (SρN), whereas at 40 and 7% of surface irradiance, the regenerated N (NH₄ ⁺ ) and urea) made up 31–72% of SρN. Depth profile experiments for all three size components showed that uptake of NO₃ ^? was most light‐sensitive, followed by that of NH₄ ⁺ and urea. The irradiance and nutrient availability plot indicated that light was substantially more important than the nutrient concentrations in controlling the assimilation of N by microplankton (20–200 μm). Nano‐ (2–20 μm) and picoplankton (< 2 μm) however, were not as sensitive to either light or nutrient concentrations. High winds and the resulting deep mixing, combined with offshore and alongshore advection in the midwinter, were suggested to be the major cause of the low biomass and N productivity.     

A model‐based data‐driven dictionary learning for seismic data representation

Planar waves events recorded in a seismic array can be represented as lines in the Fourier domain. However, in the real world, seismic events usually have curvature or amplitude variability, which means that their Fourier transforms are no longer strictly linear but rather occupy conic regions of the Fourier domain that are narrow at low frequencies but broaden at high frequencies where the effect of curvature becomes more pronounced. One can consider these regions as localised “signal cones”. In this work, we consider a space–time variable signal cone to model the seismic data. The variability of the signal cone is obtained through scaling, slanting, and translation of the kernel for cone‐limited (C‐limited) functions (functions whose Fourier transform lives within a cone) or C‐Gaussian function (a multivariate function whose Fourier transform decays exponentially with respect to slowness and frequency), which constitutes our dictionary. We find a discrete number of scaling, slanting, and translation parameters from a continuum by optimally matching the data. This is a non‐linear optimisation problem, which we address by a fixed‐point method that utilises a variable projection method with ?₁ constraints on the linear parameters and bound constraints on the non‐linear parameters. We observe that slow decay and oscillatory behaviour of the kernel for C‐limited functions constitute bottlenecks for the optimisation problem, which we partially overcome by the C‐Gaussian function. We demonstrate our method through an interpolation example. We present the interpolation result using the estimated parameters obtained from the proposed method and compare it with those obtained using sparsity‐promoting curvelet decomposition, matching pursuit Fourier interpolation, and sparsity‐promoting plane‐wave decomposition methods.     

A drought outlook study in Korea

Abstract

Techniques are proposed for developing a monthly and weekly drought outlook and the drought outlook components are evaluated. A drought index, the surface water supply index (SWSI) was modified and used for the drought outlook. A water balance model (abcd) was successfully calibrated using a regional regression, including monthly and weekly factors, and was used to convert meteorology to hydrology. For the monthly drought outlook, an ensemble technique was applied, both with and without monthly industrial meteorology information (MIMI). For the weekly drought outlook, a deterministic forecasting technique was applied employing the Global Data Assimilation and Prediction System (GDAPS). The methodologies were applied to the Geum River basin in Korea. While only the weekly outlook using the GDAPS has sufficient forecasting capability to suggest it might be useful, the accuracy of the monthly drought outlook is expected to improve as the climate forecast accuracy increases.

Editor Z.W. Kundzewicz; Associate editor D. Hughes

Citation Kim, Y.-O., Lee, J.-K., and Palmer, R.N., 2012. A drought outlook study in Korea. Hydrological Sciences Journal, 57 (6), 1141–1153.     

GPS/LEO掩星观测的变分同化技术

在简单介绍GPS/LEO掩星探测大气的发展历史和科学意义之后,详细阐述了反演的基本原理;分析了标准反演中存在的问题,并说明一维变分同化(1DVAR)在反演方法中的重要性;给出了一维变分同化中价值函数的求解,以及各种同化因子;简单介绍了对当前气象学中普遍使用的四维变分同化(4DVAR);重点讨论了各种同化方法,以及使用各种同化因子的优缺点。最后,通过CHAMP卫星的观测实例分析,验证了GPS数据在数值天气预报(NWP)中的作用,以及相对于标准反演法一维变分对气象要素的改进。     

The REM Adjoint System and Its 4DVar Data Assimilation Experiments

The Regional Eta-coordinate Model(REM) has performed well in forecasting heavy rainfalls in China in recent years.A four-dimensional variational assimilation system(4DVar) is developed to improve the forecast skill of the REM.The tangent linear model and adjoint model codes are written according to thecode to coderule,and the establishment of the REM adjoint modeling system is introduced in detail in this paper.The tangent linear and adjoint models of the REM are validated against the observational data,...     

Application of FY-2C Cloud Drift Winds in a Mesoscale Numerical Model

Statistical tests and error analysis of cloud drift winds(CDWs) from the FY-2C satellite were made by using radiosonde observations.According to the error characteristics of the CDW,a bias correction using the thermal wind theory was applied in the data quality control.The CDW data were then assimilated into the GRAPES-meso model via the GRAPES-3DVar.A torrential rain event that occurred in northwestern China during 1-2 July 2005 was simulated.The results indicate that the CDW data were mainly distribute...     

Integration of remote sensing data into hydrological models for reservoir management

Abstract

The purpose of this paper is to present the methodology set up to derive catchment soil moisture from Earth Observation (EO) data using microwave spaceborne Synthetic Aperture Radar (SAR) images from ERS satellites and to study the improvements brought about by an assimilation of this information into hydrological models. The methodology used to derive EO data is based on the appropriate selection of land cover types for which the radar signal is mainly sensitive to soil moisture variations. Then a hydrological model is chosen, which can take advantage of the new information brought by remote sensing. The assimilation of soil moisture deduced from EO data into hydrological models is based principally on model parameter updating. The main assumption of this method is that the better the model simulates the current hydrological system, the better the following forecast will be. Another methodology used is a sequential one based on Kalman filtering. These methods have been put forward for use in the European AIMWATER project on the Seine catchment upstream of Paris (France) where dams are operated to alleviate floods in the Paris area.     

国家气象中心数值预报业务的进展

在最近的１５年中，国家气象中心的数值预报业务高速度发展，预报模式从北半球模式发展为全球谱模式，并配套建立了资料同化系统和用于降水预报的有限区预报模式，暴雨和台风预报模式正在研制中。目前数值预报时效已延至７天，Ｔ６３９３丙上时的预报水平已优于的数值预报产品的应用技术在不断改进，最高（低）气温下两天ＭＯＳ预报精度已接近预报员制作的综合预报结果。