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Shi Jiang and Michael Ghil

Abstract

Numerical ocean diagnoses and predictions rely on two types of information: model information and data information. Sequential estimation theory shows that the most probable state is a linear combination of the two, weighted according to their error statistics. A Kalman filter technique is applied to a one-layer reduced-gravity linear ocean model in a rectangular midlatitude basin. The model reproduces the main features of the subtropical wind-driven gyre; the filter is used to study the dynamical behavior of the error statistics.

On a midlatitude f plane, the error-correlation patterns among the state variables revealed by the Kalman filter are isotropic and homogeneous and satisfy a geostrophic relation. Introducing the β effect breaks the isotropy and homogeneity of the correlations, inducing behavior that is in agreement with two observational facts: 1) the latitudinal dependence of horizontal correlations and 2) the elliptic correlation shape of the mass field, elongated along the southwest–northeast orientation in the Northern Hemisphere. When a meridional line of observations is assimilated intermittently, the correlation patterns are dynamically adjusted to be wider to the east of the observing line than to the west. This is due to the westward propagation of errors by the model's Rossby wave dynamics.

The influence function of observations, based on the gain matrix of the Kalman filter, is subjected to polar decomposition into an amplitude part and a vector normalized by the amplitude—that is, a solid angle. The amplitude part contains the current observational information and determines the absolute weight given to an observation. The angular part is related to the previous observations only and reflects the structure of relative weights, whose behavior is similar to that of error correlations.

A criterion measuring the relative importance of different types of observations is defined, using Kalman filter techniques and geostrophic-error assumptions. The results from numerical experiments to examine the correctness of this criterion resolve apparent contradictions among the recent results of R. Daley, M. Ghil, and N. A. Phillips.

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Shi Jiang and Michael Ghil

Abstract

Low-frequency variability of western boundary currents (WBCs) is pervasive in both observations and numerical models of the oceans. Because advection is of the essence in WBCs, nonlinearities are thought to be important in causing their variability. In numerical models, this variability can be distorted by our incomplete knowledge of the system’s dynamics, manifested in model errors. A reduced-gravity shallow-water model is used to study the interaction of model error with nonlinearity. Here our focus is on a purely periodic solution and a weakly aperiodic one.

For the periodic case, the noise-corrupted system loses its periodicity due to nonlinear processes. For the aperiodic case, the intermittent occurrences of two relatively persistent states—a straight jet with high total energy and a meandering one with low total energy—in the perturbed model are almost out of phase with the unperturbed one. For both cases, the simulation errors are trapped in the WBC region, where the nonlinear dynamics is most vigorous.

Satellite altimeters measure sea surface height globally in space and almost synoptically in time. They provide an opportunity to track WBC variability through its pronounced sea surface signature. By assimilating simulated Geosat data into the stochastically perturbed model with the improved optimal interpolation method, the authors can faithfully track the periodic behavior that had been lost and capture the correct occurrences of two relatively persistent patterns for the aperiodic case. The simulation errors accumulating in the WBC region are suppressed, thus improving the system’s predictability. The domain-averaged rms errors reach a statistical equilibrium below the observational error level.

Comparison experiments using simulated Geosat and TOPEX/POSEIDON tracks show that spatially dense sampling yields lower rms errors than temporally frequent sampling for the present model. A criterion defining spatial oversampling—that is, diminishing returns—is also addressed.

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Shi Jiang, Fei-fei Jin, and Michael Ghil

Abstract

A reduced-gravity shallow-water (SW) model is used to study the nonlinear behavior of western boundary currents (WBCs), with particular emphasis on multiple equilibria and low-frequency variations. When the meridionally symmetric wind stress is sufficiently strong, two steady solutions–nearly antisymmetric about the x axis–are achieved from different initial states. These results imply that 1) the inertial WBCs could overshoot either southward or northward along the western boundary, depending on their initial states; and thus, 2) the WBC separation and eastward jet could occur either north or south of the maximum wind stress line. The two equilibria arise via a perturbed pitchfork bifurcation, as the wind stress increases. A low-order, double-gyre, quasigeostrophic (QG) model is studied analytically to provide further insight into the physical nature of this bifurcation. In this model, the basic state is exactly antisymmetric when the wind stress is symmetric. The perturbations destroying the symmetry of the pitchfork bifurcation can arise, therefore. in the QG model only from the asymmetric components of the wind stress. In the SW model, the antisymmetry of the system's basic response to the symmetric forcing is destroyed already at arbitrarily low wind stress. The pitchfork bifurcation from this basic state to more complex states at high wind stress is accordingly perturbed in the absence of any forcing asymmetry.

Periodic solutions arise by Hopf bifurcation from either steady-state branch of the SW model. A purely periodic solution is studied in detail. The subtropical and subpolar recirculations, separation, and eastward jet exhibit a perfectly periodic oscillation with a period of about 2.8 years. Outside the recirculation zones, the solutions are nearly steady. The alternating anomalies of the upper-layer thickness are periodically generated adjacent to the ridge of the first and strongest downstream meander and are then propagated and advected into the two WBC zones, by Rossby waves and the recirculating currents, respectively. These anomalies periodically change the pressure gradient field near the WBCs and maintain the periodic oscillation. Aperiodic solutions are also studied by either increasing wind forcing or decreasing the viscosity.

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Yi Shi, Zhihong Jiang, Zhengyu Liu, and Laurent Li

Abstract

The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) platform is used to simulate Lagrangian trajectories of air parcels in East China during the summer monsoon. The investigation includes four distinct stages of the East Asian summer monsoon (EASM) during its seasonal migration from south to north. Correspondingly, the main water vapor channel migrates from the west Pacific Ocean (PO) for the premonsoon in South China (SC) to the Indian Ocean (IO) for the monsoon in SC and in the Yangtze–Huaihe River basin, and finally back to the PO for the terminal stage of monsoon in North China. Further calculations permit us to determine water vapor source regions and water vapor contribution to precipitation in East China. To a large extent, moisture leading to precipitation does not come from the strongest water vapor pathways. For example, the proportions of trajectories from the IO are larger than 25% all of the time, but moisture contributions to actual precipitation are smaller than 10%. This can be explained by the large amount of water vapor lost in the pathways across moisture-losing areas such as the Indian and Indochina Peninsulas. Local water vapor recycling inside East China (EC) contributes significantly to regional precipitation, with contributions mostly over 30%, although the trajectory proportions from subregions in EC are all under 10%. This contribution rate can even exceed 55% for the terminal stage of the monsoon in North China. Such a result provides important guidance to understand the role of land surface conditions in modulating rainfall in North China.

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Nanxuan Jiang, Qing Yan, Zhiqing Xu, Jian Shi, and Ran Zhang

Abstract

To advance our knowledge of the response of midlatitude westerlies to various external forcings, we investigate the meridional shift of midlatitude westerlies over arid central Asia (ACA) during the past 21 000 years, which experienced more varied forcings than the present day based on a set of transient simulations. Our results suggest that the evolution of midlatitude westerlies over ACA and driving factors vary with time and across seasons. In spring, the location of midlatitude westerlies over ACA oscillates largely during the last deglaciation, driven by meltwater fluxes and continental ice sheets, and then shows a long-term equatorward shift during the Holocene controlled by orbital insolation. In summer, orbital insolation dominates the meridional shift of midlatitude westerlies, with poleward and equatorward migration during the last deglaciation and the Holocene, respectively. From a thermodynamic perspective, variations in zonal winds are linked with the meridional temperature gradient based on the thermal wind relationship. From a dynamic perspective, variations in midlatitude westerlies are mainly induced by anomalous sea surface temperatures over the Indian Ocean through the Matsuno–Gill response and over the North Atlantic Ocean by the propagation of Rossby waves, or both, but their relative importance varies across forcings. Additionally, the modeled meridional shift of midlatitude westerlies is broadly consistent with geological evidence, although model–data discrepancies still exist. Overall, our study provides a possible scenario for a meridional shift of midlatitude westerlies over ACA in response to various external forcings during the past 21 000 years and highlights important roles of both the Indian Ocean and the North Atlantic Ocean in regulating Asian westerlies, which may shed light on the behavior of westerlies in the future.

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Bin Xu, Pingping Xie, Ming Xu, Lipeng Jiang, Chunxiang Shi, and Ran You

Abstract

Level 2 rain-rate retrievals from the Microwave Radiation Imager (MWRI) on board the Chinese FengYun (FY)-3B satellite are verified using minute rainfall measurements from a dense automatic weather station (AWS) network over eastern China for the warm seasons (May–September) of 2012 and 2013. First, analyses of minute rainfall are constructed on a 0.05° latitude–longitude grid box through interpolation of quality-controlled gauge reports. Ground truth for the FY-3B rain-rate retrievals is defined as the 5-min mean rate centering at the satellite observation time and over the 0.05° latitude–longitude grid boxes falling into the target field-of-view (FOV) coverage determined with parallax correction. Parallax displacement is about the same as the height of cloud or half of the FY-3B FOV size. Parallax correction is crucial to ensure accurate evaluation and applications of the level 2 precipitation retrievals from FY-3B and other satellites, including the Global Precipitation Mission (GPM) core satellite, and should be implemented before the level 2 retrievals may be used as inputs to the level 3 integrated satellite precipitation analyses. FY-3B level 2 retrievals present good skills in detecting raining pixels and quantifying rain rate as retrievals from other PMW sensors. However, they tend to miss rainfall from warm and low clouds of small scales and underestimate (overestimate) heavy (light) precipitation. In particular, the limited maximum rain rate yields significant underestimation for many heavy rainfall events. Maximum rainfall detected by the FY-3B retrievals for the afternoon orbits is shifted by about 7–8 km toward the leeward direction, most likely caused by the displacement between the heavy rainfall and tallest cloud top.

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Z. Q. Fan, Z. Sheng, H. Q. Shi, X. Yi, Y. Jiang, and E. Z. Zhu

Abstract

The accuracy of temperature data from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) radio occultation and Thermosphere, Ionosphere, Mesosphere Energetics, and Dynamics/Sounding of the Atmosphere using Broadband Emission Radiometry (TIMED/SABER) observation over China is analyzed. High-resolution sounding data are used to assess the accuracy of these two kinds of satellite observation data at corresponding heights, and the two sets of data are compared in the height range 15–40 km. Very good agreement between radiosondes and COSMIC is observed in the stratosphere. In the troposphere COSMIC temperatures are about 2 K higher than the radiosonde observations. SABER detection at 15–32 km agrees well with a maximum warm bias of ~2 K around 25-km altitude. The comparison between SABER and COSMIC for altitudes 15–40 km also indicates higher temperatures of SABER in the lower stratosphere. The standard deviations are all greater than 2.5 K and are larger near 15 km and smallest at 20 km. The temperature deviation and in particular the standard deviation comparing SABER and COSMIC changes with altitude, season, and latitude. The results of this comparative assessment can offer a basis for research into the application of COSMIC and TIMED/SABER over China.

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Z. Sheng, J. W. Li, Y. Jiang, S. D. Zhou, and W. L. Shi

Abstract

Stratospheric winds play a significant role in middle atmosphere dynamics, model research, and carrier rocket experiments. For the first time, 65 sets of rocket sounding experiments conducted at Jiuquan (41.1°N, 100.2°E), China, from 1967 to 2004 are presented to study horizontal wind fields in the stratosphere. At a fixed height, wind speed obeys the lognormal distribution. Seasonal mean winds are westerly in winter and easterly in summer. In spring and autumn, zonal wind directions change from the upper to the lower stratosphere. The monthly zonal mean winds have an annual cycle period with large amplitudes at high altitudes. The correlation coefficients for zonal winds between observations and the Horizontal Wind Model (HWM) with all datasets are 0.7. The MERRA reanalysis is in good agreement with rocketsonde data according to the zonal winds comparison with a coefficient of 0.98. The sudden stratospheric warming is an important contribution to biases in the HWM, because it changes the zonal wind direction in the midlatitudes. Both the model and the reanalysis show dramatic meridional wind differences with the observation data.

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Lifen Jiang, Yaner Yan, Oleksandra Hararuk, Nathaniel Mikle, Jianyang Xia, Zheng Shi, Jerry Tjiputra, Tongwen Wu, and Yiqi Luo

Abstract

Model intercomparisons and evaluations against observations are essential for better understanding of models’ performance and for identifying the sources of uncertainty in their output. The terrestrial vegetation carbon simulated by 11 Earth system models (ESMs) involved in phase 5 of the Coupled Model Intercomparison Project (CMIP5) was evaluated in this study. The simulated vegetation carbon was compared at three distinct spatial scales (grid, biome, and global) among models and against the observations (an updated database from Olson et al.’s “Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: A Database”). Moreover, the underlying causes of the differences in the models’ predictions were explored. Model–data fit at the grid scale was poor but greatly improved at the biome scale. Large intermodel variability was pronounced in the tropical and boreal regions, where total vegetation carbon stocks were high. While 8 out of 11 ESMs reproduced the global vegetation carbon to within 20% uncertainty of the observational estimate (560 ± 112 Pg C), the simulated global totals varied nearly threefold between the models. The goodness of fit of ESMs in simulating vegetation carbon depended strongly on the spatial scales. Sixty-three percent of the variability in contemporary global vegetation carbon stocks across ESMs could be explained by differences in vegetation carbon residence time across ESMs (P < 0.01). The analysis indicated that ESMs’ performance of vegetation carbon predictions can be substantially improved through better representation of plant longevity (i.e., carbon residence time) and its respective spatial distributions.

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