Initialization and simulation of a landfalling typhoon using a variational bogus mapped data assimilation (BMDA)

Summary Recently, a new data assimilation method called “3-dimensional variational data assimilation of mapped observation (3DVM)” has been developed by the authors. We have shown that the new method is very efficient and inexpensive compared with its counterpart 4-dimensional variational data assimilation (4DVar). The new method has been implemented into the Penn State/NCAR mesoscale model MM5V1 (MM5_3DVM). In this study, we apply the new method to the bogus data assimilation (BDA) available in the original MM5 with the 4DVar. By the new approach, a specified sea-level pressure (SLP) field (bogus data) is incorporated into MM5 through the 3DVM (for convenient, we call it variational bogus mapped data assimilation – BMDA) instead of the original 4DVar data assimilation. To demonstrate the effectiveness of the new 3DVM method, initialization and simulation of a landfalling typhoon – typhoon Dan (1999) over the western North Pacific with the new method are compared with that with its counterpart 4DVar in MM5. Results show that the initial structure and the simulated intensity and track are improved more significantly using 3DVM than 4DVar. Sensitivity experiments also show that the simulated typhoon track and intensity are more sensitive to the size of the assimilation window in the 4DVar than that in the 3DVM. Meanwhile, 3DVM takes much less computing cost than its counterpart 4DVar for a given time window.     

Measurements and Langevin simulations of mean tracer concentration fields downwind from a circular line source inside an alfalfa canopy

Two Langevin simulations of trajectories of marked fluid elements in inhomogenous turbulence, where the Lagrangian length and vertical velocity scales are height dependent, were compared with field data. A CO₂ tracer was released from a circular line source and the concentration profiles were measured for diffusion distances of 50 and 100 cm inside and above an alfalfa canopy.One of the simulations, suggested by Wilson et al. (1983), biases the vertical velocities by adding a mean upward drift. The second simulation proposed here by-passes this difficulty by reflecting marked particles according to a probability calculated from the gradient in vertical velocity variance between the beginning and the end of each step. This simulation also makes use of a constant time-scale within the canopy, following preliminary results from a turbulence experiment within a forest (Leclerc, 1987).Comparing the results of these simulations with the field data shows that the simulation proposed by Wilson et al. (1983) does not correctly reproduce the difusion for the larger fetch in systems exhibiting strong gradients in vertical velocity variance. Instead, the modelled plumes exhibit a bulge at the source height whereas the field data show smooth profiles. In addition, the modelled plumes overestimate the vertical spread of the plumes, which is possibly due to the inadequacy of the approach in severely inhomogeneous systems. In contrast, the results from the tracer experiments indicate that the diffusion can be better reproduced with the use of a reflection probability calculated at each step. The discrepancies between the experimental results and the simulation using a reflection probability are attributed to stability effects.     

Nonlinear seismic soil–pile–structure interactions: Shaking table tests and FEM analyses

In this paper, a soil–pile–structure model is tested on a shaking table subject to both a sinusoidal wave and the acceleration time history of the scaled 1940 El Centro earthquake. A medium-size river sand is compacted into a 1.7-m-high laminar rectangular tank to form a loose fill with a relative density of 15%. A single-storey steel structure of 2.54 ton is placed on a concrete pile cap, which is connected to the four end-bearing piles. A very distinct pounding phenomenon between soil and pile is observed; and, the acceleration response of the pile cap can be three times larger than that of the structural response. The pounding is due to the development of a gap separation between soil and pile, and the extraordinary large inertia force suffered at the top of the pile also induces cracking in the pile. To explain this observed phenomenon, nonlinear finite element method (FEM) analyses with a nonlinear gap element have been carried out. The spikes in the acceleration response of the pile cap caused by pounding can be modeled adequately by the FEM analyses. The present results suggest that one of the probable causes of pile damages is due to seismic pounding between the laterally compressed soil and the pile near the pile cap level.     

A Multi-Observatory Inter-Comparison of Line-of-Sight Synoptic Solar Magnetograms

The observed photospheric magnetic field is a crucial parameter for understanding a range of fundamental solar and heliospheric phenomena. Synoptic maps, in particular, which are derived from the observed line-of-sight photospheric magnetic field and built up over a period of 27 days, are the main driver for global numerical models of the solar corona and inner heliosphere. Yet, in spite of 60 years of measurements, quantitative estimates remain elusive. In this study, we compare maps from seven solar observatories (Stanford/WSO, NSO/KPVT, NSO/SOLIS, NSO/GONG, SOHO/MDI, UCLA/MWO, and SDO /HMI) to identify consistencies and differences among them. We find that while there is a general qualitative consensus, there are also some significant differences. We compute conversion factors that relate measurements made by one observatory to another using both synoptic map pixel-by-pixel and histogram-equating techniques, and we also estimate the correlation between datasets. For example, Wilcox Solar Observatory (WSO) synoptic maps must be multiplied by a factor of 3?–?4 to match Mount Wilson Observatory (MWO) estimates. Additionally, we find no evidence that the MWO saturation correction factor should be applied to WSO data, as has been done in previous studies. Finally, we explore the relationship between these datasets over more than a solar cycle, demonstrating that, with a few notable exceptions, the conversion factors remain relatively constant. While our study was able to quantitatively describe the relationship between the datasets, it did not uncover any obvious “ground truth.” We offer several suggestions for how this may be addressed in the future.     

On causes and impacts of land subsidence in Bandung Basin, Indonesia

The Bandung Basin is a large intra-montane basin surrounded by volcanic highlands, in western Java, Indonesia, inhabited by more than seven million people. The basin, an area of about 2,300 km², is a highland plateau at approximately 650–700 m above sea level and is surrounded by up to 2,400 m high Late Tertiary and Quaternary volcanic terrain. Based on the results of nine GPS surveys conducted since 2000 up to 2011, it was shown that several locations in the Bandung Basin have experienced land subsidence, with an average rate of about ?8 cm/year and can go up to about ?23 cm/year in certain locations. A hypothesis has been proposed by several studies that land subsidence observed in several locations in the Bandung Basin has been caused mainly by excessive groundwater extraction. It is found that there is a strong correlation between the rates of groundwater level lowering with the GPS-derived rates of land subsidence in several locations in Bandung Basin. The GPS results in this study detected significant subsidence in the textile industry area, where very large volumes of groundwater are usually extracted. The impact of land subsidence in Bandung can be seen in several forms, mainly in the cracking and damage of houses, buildings and infrastructure. Land subsidence also aggravates the flooding in Bandung Basin, which has brought huge economic losses and deteriorated the quality of life and environment in the affected areas.     

A study of hybrid and chaotic long-range propagation in a doublesound channel environment

This paper presents the results of the analysis of long range propagation (~200 km) in a range-dependent environment. The propagation medium is characterized by two deep sound channels. The range dependence enables energy transfer between the channels and leads to a mismatch between real data and ray predictions. To explain this mismatch, an analysis of hybrid ray propagation is presented. This analysis is completed by an interpretation in terms of chaos. This chaos is quantified in the particular case of the Bay of Biscay environment. This paper puts forward that mesoscale perturbations, such as the Mediterranean outflow in the North Atlantic, can affect long-range propagation. However, it shows that the ray theory remains reliable for a propagation range of several hundred kilometers     

Long‐term trend analysis for major climate variables in the Yellow River basin*

Some previous studies have shown that drying‐up of the lower Yellow River resulted from decreasing precipitation and excessive industrial and agricultural consumption of water from the middle and downstream regions of the Yellow River. On the basis of average air temperature, precipitation, and pan evaporation data from nearly 80 gauging stations in the Yellow River basin, the monotonic trends of major climate variables over the past several decades are analysed. The analysis was mainly made for 12 months and the annual means. The isograms for annual and typical months are given in the paper. The result shows that the average temperature in the study area exhibits an increasing trend, mainly because of the increase of temperature in December, January and February. The largest trend is shown in December and the smallest is in August. There are 65 of 77 stations exhibiting a downward trend for annual precipitation. In all seasons except summer, there is a similar trend in the upstream region of the Yellow River, south of latitude 35°N. It is interesting to note that the pan evaporation has decreased in most areas of the Yellow River basin during the past several decades. April and July showed the greatest magnitude of slope, and the area from Sanmenxia to Huayuankou as well as the Yiluo River basin exhibited the strongest declining trend. The conclusion is that the decreasing pan evaporation results from complex changes of air temperature, relative humidity, solar radiation, and wind speed, and both climate change and human activities have affected the flow regime of the Yellow River during the past several decades. Copyright © 2007 John Wiley & Sons, Ltd.     

An overview of the ACE‐2 CLOUDYCOLUMN closure experiment

CLOUDYCOLUMN is one of the 6 ACE‐2 projects which took place in June‐July 1997, between Portugal and the Canary Islands. It was specifically dedicated to the study of changes of cloud radiative properties resulting from changes in the properties of those aerosols which act as cloud condensation nuclei. This process is also refered to as the aerosol indirect effect on climate. CLOUDYCOLUMN is focused on the contribution of stratocumulus clouds to that process. In addition to the basic aerosol measurements performed at the ground stations of the ACE‐2 project, 5 instrumented aircraft carried out in situ characterization of aerosol physical, chemical and nucleation properties and cloud dynamical and microphysical properties. Cloud radiative properties were also measured remotely with radiometers and a lidar. 11 case studies have been documented, from pure marine to significantly polluted air masses. The simultaneity of the measurements with the multi‐aircraft approach provides a unique data set for closure experiments on the aerosol indirect effect. In particular CLOUDYCOLUMN provided the 1st experimental evidence of the existence of the indirect effect in boundary layer clouds forming in polluted continental outbreacks. This paper describes the objectives of the project, the instrumental setup and the sampling strategy. Preliminary results published in additional papers are briefly summarized.     

A neural network atmospheric model for hybrid coupled modelling

 The possibility of using a nonlinear empirical atmospheric model for hybrid coupled atmosphere-ocean modelling has been examined by using a neural network (NN) model for predicting the contemporaneous wind stress field from the upper ocean state. Upper ocean heat content (HC) from a 6-layer ocean model was a better predictor of the wind stress than the (observed or modelled) sea surface temperature (SST). Our results showed that the NN model generally had slightly better skills in predicting the contemporaneous wind stress than the linear regression (LR) model in the off-equatorial tropical Pacific and in the eastern equatorial Pacific. When the wind stresses from the NN and LR models were used to drive the ocean model, slightly better SST skills were found in the off-equatorial tropical Pacific and in the eastern equatorial Pacific when the NN winds were used instead of the LR winds. Better skills for the model HC were found in the western and central equatorial Pacific when the NN winds were used instead of the LR winds. Why NN failed to show more significant improvement over LR in the equatorial Pacific for the wind stress and SST is probably because the relationship between the surface ocean and the atmosphere in the equatorial Pacific over the seasonal time scale is almost linear. Received: 2 March 1999 / Accepted: 13 July 2000