On the Correlation between Convective Plume Updrafts and Downdrafts,Lidar Reflectivity and Depolarization Ratio

We question the correlation between vertical velocity (w) on the one hand and the occurrence of convective plumes in lidar reflectivity (i.e. range corrected backscatter signal Pz ²) and depolarization ratio (Δ) on the other hand in the convective boundary layer (CBL). Thermal vertical motion is directly investigated using vertical velocities measured by a ground-based Doppler lidar operating at 2 μm. This lidar provides also simultaneous measurements of lidar reflectivity. In addition, a second lidar 200 m away provides reflectivities at 0.53 and 1 μm and depolarization ratio at 0.53 μm. The time series from the two lidars are analyzed in terms of linear correlation coefficient (ρ). The main result is that the plume-like structures provided by lidar reflectivity within the CBL as well as the CBL height are not a clear signature of updrafts. It is shown that the lidar reflectivity within the CBL is frequently anti-correlated (ρ (w, Pz ² )) with the vertical velocity. On the contrary, the correlation coefficient between the depolarization ratio and the vertical velocity ρ (w, Δ ) is always positive, showing that the depolarization ratio is a fair tracer of updrafts. The importance of relative humidity on the correlation coefficient is discussed. An erratum to this article can be found at     

Incorporation of a dynamic root distribution into CLM4.5: Evaluation of carbon and water fluxes over the Amazon

Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon–nitrogen(CN) interactions(CLM4.5-CN) to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83(BRSa3) site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production(GPP) and latent heat flux(LE) for the dry season, and improved the carbon(C) and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m~(-2)d~(-1), net ecosystem exchange by 1.96 g C m~(-2)d~(-1), LE by 5.0 W m~(-2), and soil moisture by 0.03 m~3m~(-3), at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses(including GPP and LE) to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated.     

Analytical solutions for the equations of motion of a space vehicle during the atmospheric re-entry phase on a 2-D trajectory

A practical and important problem encountered during the atmospheric re-entry phase is to determine analytical solutions for the space vehicle dynamical equations of motion. The author proposes new solutions for the equations of trajectory and flight-path angle of the space vehicle during the re-entry phase in Earth’s atmosphere. Explicit analytical solutions for the aerodynamic equations of motion can be effectively applied to investigate and control the rocket flight characteristics. Setting the initial conditions for the speed, re-entering flight-path angle, altitude, atmosphere density, lift and drag coefficients, the nonlinear differential equations of motion are linearized by a proper choice of the re-entry range angles. After integration, the solutions are expressed with the Exponential Integral, and Generalized Exponential Integral functions. Theoretical frameworks for proposed solutions as well as, several numerical examples, are presented.     

Coastal upwelling along the north coast of Papua New Guinea and SST cooling over the pacific warm pool: A case study for the 2002/03 El Niño event

We investigate an overlooked mechanism—coastal upwelling—for sea surface temperature (SST) cooling in the western side of the mean location of the Pacific warm pool (WSWP: 5°S–5°N, 140°E–150°E) prior to El Niño onset. We analyze various observed data such as the TRIangle Trans-Ocean buoy Network (TRITON) moored buoy data, Conductivity-Temperature-Depth (CTD) data, satellite data and a hindcast experiment output by a high-resolution ocean general circulation model (OGCM). We focus on the precondition of the 2002/03 El Niño event, for which many datasets are available. Relatively cool water upwelled along the north coast of Papua New Guinea (PNG) during December 2001, prior to the onset of the 2002/03 El Niño event, and then spread out over a wider area to the northeast. Simultaneously, strong west-northerly surface winds occur along the north coast. Heat budget analysis of TRITON buoy data in the WSWP reveals that negative zonal heat advection due to eastward current is the main factor for cooling the mixed layer in the WSWP in contrast to the warming effect of the surface heat flux during the period. This cooling requires a source of colder water to the west. Similar analysis of OGCM outputs also suggests that the upwelled relatively cool water along the PNG north coast, and its northeastward extension to the equatorial region, contributes to cooling of the surface water over the WSWP mainly via negative zonal heat advection. Similar mechanisms are confirmed also for the 1982/83 and 1997/98 El Niño events by analyses of OGCM outputs and historical SST data. The low SST in the WSWP generated a positive zonal SST gradient together with high SST east of the WSWP. It may contribute to enhancement of the westerly surface wind in this region, leading to the onset of the 2002/03 El Niño event.     

Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Blasting is a widely used technique for rock fragmentation in opencast mines and tunneling projects. Ground vibration is one of the most environmental effects produced by blasting operation. Therefore, the proper prediction of blast-induced ground vibrations is essential to identify safety area of blasting. This paper presents a predictive model based on gene expression programming (GEP) for estimating ground vibration produced by blasting operations conducted in a granite quarry, Malaysia. To achieve this aim, a total number of 102 blasting operations were investigated and relevant blasting parameters were measured. Furthermore, the most influential parameters on ground vibration, i.e., burden-to-spacing ratio, hole depth, stemming, powder factor, maximum charge per delay, and the distance from the blast face were considered and utilized to construct the GEP model. In order to show the capability of GEP model in estimating ground vibration, nonlinear multiple regression (NLMR) technique was also performed using the same datasets. The results demonstrated that the proposed model is able to predict blast-induced ground vibration more accurately than other developed technique. Coefficient of determination values of 0.914 and 0.874 for training and testing datasets of GEP model, respectively show superiority of this model in predicting ground vibration, while these values were obtained as 0.829 and 0.790 for NLMR model.     

Variability and teleconnections of South and East Asian summer monsoons in present and future projections of CMIP5 climate models

Coupled Model Inter-comparison Project Phase 5 (CMIP5) model outputs of the South and East Asian summer monsoon variability and their tele-connections are investigated using historical simulations (1861-2005) and future projections under the RCP4.5 scenario (2006-2100). Detailed analyses are performed using nine models having better representation of the recent monsoon teleconnections for the interactive Asian monsoon sub-systems. However, these models underestimate rainfall mainly over South Asia and Korea-Japan sector, the regions of heavy rainfall, along with a bias in location of rainfall maxima. Indeed, the simulation biases, underestimations of monsoon variability and teleconnections suggest further improvements for better representation of Asian monsoon in the climate models. Interestingly, the performance of Australian Community Climate and Earth System Simulator version 1.0 (ACCESS1.0) in simulating the annual cycle, spatial pattern of rainfall and multi-decadal variations of summer monsoon rainfall over South and East Asia appears to more realistic. In spite of large spread among the CMIP5 models, historical simulations as well as future projections of summer monsoon rainfall indicate multi-decadal variability. These rainfall variations, displaying certain epochs of more rainfall over South Asia than over East Asia and vice versa, suggest an oscillatory behaviour. Teleconnections between South and East Asian monsoon rainfall also exhibit a multi-decadal variation with alternate epochs of strengthening and weakening relationship. Furthermore, large-scale circulation features such as South Asian monsoon trough and north Pacific subtropical high depict zonal oscillatory behaviour with east-west-east shifts. Periods with eastward or westward extension of the Mascarene High, intensification and expansion of the upper tropospheric South Asian High are also projected by the CMIP5 models.     

The polar form of the spherical harmonic spectrum: implications for filtering <Emphasis Type="BoldSmallCaps">grace</Emphasis> data

Representing the spherical harmonic spectrum of a field on the sphere in terms of its amplitude and phase is termed as its polar form. In this study, we look at how the amplitude and phase are affected by linear low-pass filtering. The impact of filtering on amplitude is well understood, but that on phase has not been studied previously. Here, we demonstrate that a certain class of filters only affect the amplitude of the spherical harmonic spectrum and not the phase, but the others affect both the amplitude and phase. Further, we also demonstrate that the filtered phase helps in ascertaining the efficacy of decorrelation filters used in the grace community.     

What Can be Expected from the GRACE-FO Laser Ranging Interferometer for Earth Science Applications?

The primary objective of the gravity recovery and climate experiment follow-on (GRACE-FO) satellite mission, due for launch in August 2017, is to continue the GRACE time series of global monthly gravity field models. For this, evolved versions of the GRACE microwave instrument, GPS receiver, and accelerometer will be used. A secondary objective is to demonstrate the effectiveness of a laser ranging interferometer (LRI) in improving the satellite-to-satellite tracking measurement performance. In order to investigate the expected enhancement for Earth science applications, we have performed a full-scale simulation over the nominal mission lifetime of 5 years using a realistic orbit scenario and error assumptions both for instrument and background model errors. Unfiltered differences between the synthetic input and the finally recovered time-variable monthly gravity models show notable improvements with the LRI, on a global scale, of the order of 23 %. The gain is realized for wavelengths smaller than 240 km in case of Gaussian filtering but decreases to just a few percent when anisotropic filtering is applied. This is also confirmed for some typical regional Earth science applications which show randomly distributed patterns of small improvements but also degradations when using DDK4-filtered LRI-based models. Analysis of applied error models indicates that accelerometer noise followed by ocean tide and non-tidal mass variation errors are the main contributors to the overall GRACE-FO gravity model error. Improvements in these fields are therefore necessary, besides optimized constellations, to make use of the increased LRI accuracy and to significantly improve gravity field models from next-generation gravity missions.     

Effect of snow cover on pan-Arctic permafrost thermal regimes

This study quantitatively evaluated how insulation by snow depth (SND) affected the soil thermal regime and permafrost degradation in the pan-Arctic area, and more generally defined the characteristics of soil temperature (T_SOIL) and SND from 1901 to 2009. This was achieved through experiments performed with the land surface model CHANGE to assess sensitivity to winter precipitation as well as air temperature. Simulated T_SOIL, active layer thickness (ALT), SND, and snow density were generally comparable with in situ or satellite observations at large scales and over long periods. Northernmost regions had snow that remained relatively stable and in a thicker state during the past four decades, generating greater increases in T_SOIL. Changes in snow cover have led to changes in the thermal state of the underlying soil, which is strongly dependent on both the magnitude and the timing of changes in snowfall. Simulations of the period 2001–2009 revealed significant differences in the extent of near-surface permafrost, reflecting differences in the model’s treatment of meteorology and the soil bottom boundary. Permafrost loss was greater when SND increased in autumn rather than in winter, due to insulation of the soil resulting from early cooling. Simulations revealed that T_SOIL tended to increase over most of the pan-Arctic from 1901 to 2009, and that this increase was significant in northern regions, especially in northeastern Siberia where SND is responsible for 50 % or more of the changes in T_SOIL at a depth of 3.6 m. In the same region, ALT also increased at a rate of approximately 2.3 cm per decade. The most sensitive response of ALT to changes in SND appeared in the southern boundary regions of permafrost, in contrast to permafrost temperatures within the 60°N–80°N region, which were more sensitive to changes in snow cover. Finally, our model suggests that snow cover contributes to the warming of permafrost in northern regions and could play a more important role under conditions of future Arctic warming.     

The Spatial Characteristics of a Line and Their Application to Line Simplification

This paper discusses the spatial knowledge related to a line,and the characteristic points of lines is detected.According to the requirements of line generalization,new algorithms for identifying characteristic line points are presented.These characteristic points are used to improve the algorithms of line generalization.An algorithm for identifying bends is shown.In this paper,improved algorithms based on those by Douglas-Peucker,Visvalingam and Whyatt are shown.In this test,the progressive process of line generalization is emphasized.