New granular rock-analogue materials for simulation of multi-scale fault and fracture processes

In this study, we present a new granular rock-analogue material (GRAM) with a dynamic scaling suitable for the simulation of fault and fracture processes in analogue experiments. Dynamically scaled experiments allow the direct comparison of geometrical, kinematical and mechanical processes between model and nature. The geometrical scaling factor defines the model resolution, which depends on the density and cohesive strength ratios of model material and natural rocks. Granular materials such as quartz sands are ideal for the simulation of upper crustal deformation processes as a result of similar nonlinear deformation behaviour of granular flow and brittle rock deformation. We compared the geometrical scaling factor of common analogue materials applied in tectonic models, and identified a gap in model resolution corresponding to the outcrop and structural scale (1–100 m). The proposed GRAM is composed of quartz sand and hemihydrate powder and is suitable to form cohesive aggregates capable of deforming by tensile and shear failure under variable stress conditions. Based on dynamical shear tests, GRAM is characterized by a similar stress–strain curve as dry quartz sand, has a cohesive strength of 7.88 kPa and an average density of 1.36 g cm−3. The derived geometrical scaling factor is 1 cm in model = 10.65 m in nature. For a large-scale test, GRAM material was applied in strike-slip analogue experiments. Early results demonstrate the potential of GRAM to simulate fault and fracture processes, and their interaction in fault zones and damage zones during different stages of fault evolution in dynamically scaled analogue experiments.

Representation of Spatial Variability of the Water Fluxes over the Congo Basin Region

The Congo Basin, being one of the major basins in the tropics, is important to the global climate, yet its hydrology is perhaps the least understood. Although various reanalysis/analysis datasets have been used to improve our understanding of the basin’s hydroclimate, they have been historically difficult to validate due to sparse in situ measurements. This study analyzes the impact of model resolution on the spatial variability of the Basin’s hydroclimate using the Decorrelation Length Scale (DLCS) technique, as it is not subject to uniform model bias. The spatial variability within the precipitation (P), evaporation/evapotranspiration (E), and precipitation-minus-evaporation (P-E) fields were investigated across four spatial resolutions using reanalysis/analysis datasets from the ECMWF ranging from 9–75 km. Results show that the representation of P and P-E fields over the Basin and the equatorial Atlantic Ocean are sensitive to model resolution, as the spatial patterns of their DCLS results are resolution-dependent. However, the resolution-independent features are predominantly found in the E field. Furthermore, the P field is the dominant source of spatial variability of P-E, occurring over the land and the equatorial Atlantic Ocean, while over the Southern Atlantic, P-E is mainly governed by the E field, with both showing weak spatial variability.

Impact of Model Resolution on the Simulation of Precipitation Extremes over China

Climate models tend to overestimate light precipitation and underestimate heavy precipitation due to low model resolution. This work investigated the impact of model resolution on simulating the precipitation extremes over China during 1995–2014, based on five models from Coupled Model Intercomparison Project 6 (CMIP6), each having low- and high-resolution versions. Six extreme indices were employed: simple daily intensity index (SDII), wet days (WD), total precipitation (PRCPTOT), extreme precipitation amount (R95p), heavy precipitation days (R20mm), and consecutive dry days (CDD). Models with high resolution demonstrated better performance in reproducing the pattern of climatological precipitation extremes over China, especially in the western Sichuan Basin along the eastern side of the Tibetan Plateau (D1), South China (D2), and the Yangtze-Yellow River basins (D3). Decreased biases of precipitation exist in all high-resolution models over D1, with the largest decease in root mean square error (RMSE) being 48.4% in CNRM-CM6. The improvement could be attributed to fewer weak precipitation events (0 mm/day–10 mm/day) in high-resolution models in comparison with their counterparts with low resolutions. In addition, high-resolution models also show smaller biases over D2, which is associated with better capturing of the distribution of daily precipitation frequency and improvement of the simulation of the vertical distribution of moisture content.

On the Potential of 3D Transdimensional Surface Wave Tomography for Geothermal Prospecting of the Reykjanes Peninsula

Seismic travel time tomography using surface waves is an effective tool for three-dimensional crustal imaging. Historically, these surface waves are the result of active seismic sources or earthquakes. More recently, however, surface waves retrieved through the application of seismic interferometry have also been exploited. Conventionally, two-step inversion algorithms are employed to solve the tomographic inverse problem. That is, a first inversion results in frequency-dependent, two-dimensional maps of phase velocity, which then serve as input for a series of independent, one-dimensional frequency-to-depth inversions. As such, a set of localized depth-dependent velocity profiles are obtained at the surface points. Stitching these separate profiles together subsequently yields a three-dimensional velocity model. Relatively recently, a one-step three-dimensional non-linear tomographic algorithm has been proposed. The algorithm is rooted in a Bayesian framework using Markov chains with reversible jumps, and is referred to as transdimensional tomography. Specifically, the three-dimensional velocity field is parameterized by means of a polyhedral Voronoi tessellation. In this study, we investigate the potential of this algorithm for the purpose of recovering the three-dimensional surface-wave-velocity structure from ambient noise recorded on and around the Reykjanes Peninsula, southwest Iceland. To that end, we design a number of synthetic tests that take into account the station configuration of the Reykjanes seismic network. We find that the algorithm is able to recover the 3D velocity structure at various scales in areas where station density is high. In addition, we find that the standard deviation of the recovered velocities is low in those regions. At the same time, the velocity structure is less well recovered in parts of the peninsula sampled by fewer stations. This implies that the algorithm successfully adapts model resolution to the density of rays. It also adapts model resolution to the amount of noise in the travel times. Because the algorithm is computationally demanding, we modify the algorithm such that computational costs are reduced while sufficiently preserving non-linearity. We conclude that the algorithm can now be applied adequately to travel times extracted from station–station cross correlations by the Reykjanes seismic network.

Numerical study of western disturbances over western Himalayas using mesoscale model

Hkkjrh; {ks= esa ’khr _rq ds nkSjku if’peh fo{kksHkksa ¼MCY;w-Mh-½ dh egRoiw.kZ fo’ks"krkvksa dks izfr:fir djus ds fy, isu LVsV ;wfuoflZVh&us’kuy lsUVj Qksj ,V~eksLQsfjd fjlpZ ¼ih-,l-;w-&,u-lh-,-vkj-½ la;qDr jkT; vejhdk ds xSj ty LFkSfrd :ikUrj ds rkSj ij eslksLdsy ekWMy ¼,e- ,e- 5½ dk mi;ksx fd;k x;k gSA bl v/;;u esa nks xzgh; ifjlhek Lrj i)fr;ksa uker%&CySdknj ,oa gkSax&iSu rFkk pkj laogu izkpyhdj.k i)fr;ksa uker% dqvks] xzsy] dSufÝz’k ,oa csV~l&feYyj ds 60 fd- eh- ds {kSfrt foHksnu ekWMy dk mi;ksx djds vkB lqxzkfgrk iz;ksx fd, x, gaSA blesa {kSfrt foHksnu ekWMy rFkk LFkykÑfr ds egRo ds nks dkjdksa&30 fd-eh-] 60 fd-eh- ,oa 90 fd- eh- ds {kSfrt foHksnu ekWMy ftlesa ,d fLFkfr esa LFkykÑfr ij fopkj ugha fd;k x;k gS rFkk nwljh esa lkekU; LFkykÑfr ij fopkj fd;k x;k gS] ds vk/kkj ij N% iz;ksx djds v/;;u fd;k x;k gSA bl v/;;u ds fy, nks lfØ; if’peh fo{kksHkksa dk p;u fd;k x;k gS ftlds dkj.k if’peh fgeky; {ks= esa Hkkjh o`f"V gqbZA izFke v/;;u ds fy, 18 tuojh ls 21 tuojh] 1997 rd dh vof/k ds nkSjku ds if’peh fo{kksHk dk p;u fd;k x;k gS rFkk nwljs iz;ksx ds fy, 20 tuojh ls 25 tuojh] 1999 dh vof/k ds nkSjku ds if’peh fo{kksHk dk p;u fd;k x;k gSA blesa vkjafHkd rFkk lhekar fLFkfr;ksa ds fy, us’kuy lsUVj QkWj bu~okbjWuesUV fizMhD’ku&us’kuy lsUVj QkWj ,V~eksLQsfjd fjlpZ ¼,u- lh- b- ih-&,u- lh- , - vkj-½ la;qDr jkT; vejhdk }kjk iqufoZ’ysf"kr vkaadM+ksa dk mi;ksx fd;k x;k gSA bl v/;;u ls ;g irk pyk gS fd gkSax&iSu vkSj csV~l feYyj dh Øe’k% xzgh; ifjlhek Lrj rFkk es?k laogu izkpyhdj.k i)fr ds la;kstu dk izn’kZu mi;ksx dh xbZ vU; la;kstu i)fr;ksa ds rqyuk esa lcls vPNk jgk gSA vkn’kZ HkkSfrdh ¼ekWMy fQftDl½ vU; la;kstu i)fr;ksa dh rqyuk esa bl la;kstu ds }kjk leqnz ry dk nkc T;knk lgh izfr:fir djus esa l{ke jgh gSA blds vykok LFkykÑfr jfgr {ks= esa if’peh fo{kksHk dk izfr:i.k lkekU; LFkykÑfr esa izfr:fIkr if’peh fo{kksHk dh rqyuk esa de o"kkZ dh ek=k dks n’kkZrk gSA tc blesa lkekU; LFkykÑfr dks ’kkfey fd;k x;k rks fgeky; {ks= ds vkl&ikl Hkkjh o"kkZ gqbZA o"kkZ ds {ks=ksa ds ,dhÑr ekWMy lR;kfir fo’ys"k.k ds vuq:Ik ik, x, gaSA o"kkZ {ks=ksa ds lqxzkfgrk v/;;u ls irk pyk gS fd NksVs izHkko& {ks= ¼30 fd-eh-½ ds izfr:fir ekWMy vPNs ifj.kke nsrs gSaA ” A non-hydrostatic version of the Penn State University - National Center for Atmospheric Research (PSU-NCAR), US, Mesoscale Model (MM5) is used to simulate the characteristic features of the Western Disturbances (WDs) occurred over the Indian region during winter. In the present study sensitivity eight experiments are carried out by using two planetary boundary layer schemes, viz., Blackadar and Hong-Pan, and four convection parameterization schemes, viz., Kuo, Grell, Kain-Fristch and Betts-Miller, with 60 km horizontal model resolution. And also the role of horizontal model resolution and topography is studied by carrying out six experiments based on two factors: horizontal model resolution of 30 km, 60 km and 90 km with assumed no topography and normal topography. For this study two active WDs are chosen which yielded extensive precipitation over western Himalayas. WD from 18 to 21 January 1997 is chosen for study one and WD from 20 to 25 January 1999 is chosen for experiment two. National Center for Environmental Prediction – National Center for Atmospheric Research (NCEP-NCAR), US, reanalyzed data is used for initial and boundary conditions. It is found that the performance of combination of the Hong-Pan and Betts-Miller as planetary boundary layer and cloud convection parameterization schemes respectively is best compared to the other combinations of schemes used in this study. The model physics could able to simulate sea level pressure better with this combination as compared to the combinations with other schemes. Further, WD simulations with assumed no topography shows lesser amount of precipitation compared to WD simulations with normal topography. When normal topography is included, intense localized of precipitation was observed along the Himalayan range. Model integrations of precipitation fields are found close to the corresponding verification analysis. Sensitivity studies of precipitation field shows that finer domain (30 km) of the model simulation gives better results.