Application of magnetic method to characterize Abaya campus building site, Southern Ethiopia

A geophysical survey involving magnetic method is conducted using ENVI-MAG proton precision magnetometer. The study is carried out with the aim of identifying the possible geological structures which may responsible for the failure of engineering structures. Three traverses having east –west orientation with a ten meters profile spacing and a readings station spacing and one traverse across the three traverses and randomly collected magnetic data were used. At each station three readings were taken and averaged out in order to increase the accuracy of data and diurnal and geomagnetic corrections were made. With the corrected data different anomalous maps were produced like total magnetic field anomaly map, residual magnetic anomaly map and analytical signal map using Oasis montaji6.4 software for further interpretation. The result of this research has shown that the area is affected by different geological structures which may be the cause for the crack and the failure of the building in the area.

Effects of Multi-Shell Free Water Correction on Glioma Characterization

Diffusion MRI is a useful tool to investigate the microstructure of brain tumors. However, the presence of fast diffusing isotropic signals originating from non-restricted edematous fluids, within and surrounding tumors, may obscure estimation of the underlying tissue characteristics, complicating the radiological interpretation and quantitative evaluation of diffusion MRI. A multi-shell regularized free water (FW) elimination model was therefore applied to separate free water from tissue-related diffusion components from the diffusion MRI of 26 treatment-naïve glioma patients. We then investigated the diagnostic value of the derived measures of FW maps as well as FW-corrected tensor-derived maps of fractional anisotropy (FA). Presumed necrotic tumor regions display greater mean and variance of FW content than other parts of the tumor. On average, the area under the receiver operating characteristic (ROC) for the classification of necrotic and enhancing tumor volumes increased by 5% in corrected data compared to non-corrected data. FW elimination shifts the FA distribution in non-enhancing tumor parts toward higher values and significantly increases its entropy (p ≤ 0.003), whereas skewness is decreased (p ≤ 0.004). Kurtosis is significantly decreased (p < 0.001) in high-grade tumors. In conclusion, eliminating FW contributions improved quantitative estimations of FA, which helps to disentangle the cancer heterogeneity.

Assessment of the Feasibility of PPP-B2b Service for Real-Time Coseismic Displacement Retrieval

Traditional coseismic displacement retrieval generally uses real-time kinematic (RTK) and precise point positioning (PPP) services. However, both RTK and real-time PPP need a network link to transmit the corrected data. Although the network link may be interrupted when an earthquake happens, the PPP-B2b service broadcasted by geostationary orbit (GEO) satellites will not be affected. Its service range mainly covers China and the surrounding areas. In this research, the PPP method with PPP-B2b service based on constrained coordinates is proposed and overcomes the limitation of the network link and long convergence time. First, the accuracy of orbits and clock offsets for the PPP-B2b service is evaluated and compared with real-time service (RTS). Then, the simulated experiments are carried out using the PPP method with PPP-B2b service based on constrained coordinates, which tests the accuracy by calculating the coordinate displacement of the measurement station. The results show that the accuracy of PPP-B2b orbits in the radial direction is within 0.1 m. Moreover, regarding the accuracy of clock offsets, the PPP-B2b service is no more than 3.5 cm. This validates the feasibility of replacing RTS products with PPP-B2b. In the 15 min simulated experiments, the root mean square (RMS) of horizontal and vertical directions is maintained within 3 cm.

Validation of Climate Hazard Group InfraRed Precipitation with Station (CHIRPS) Data in Wonorejo Reservoir, Indonesia

This study aims to test the validation of precipitation data from CHIRPS compared to measurement data. The study location is Wonorejo Reservoir, Indonesia. The methods in this research were 1) data quality test with the consistency test and stationary test, and 2) validity test with parameters of NSE value and correlation. The study results show that 1) The data quality test shows that the precipitation data from CHIRPS are consistent and homogeneous; 2) The validity test is carried out in two stages, for uncorrected data and corrected data. According to NSE value, the validity of test results on uncorrected data shows that CHIRPS’s precipitation data are unsatisfactory. When viewed from the correlation, the precipitation data from CHIRPS has a very strong relationship to precipitation measurement data. The next step is to test the validity of the corrected data. The validation test of corrected data shows that precipitation data from CHIRPS is satisfactory according to NSE value. Moreover, the precipitation data from CHIRPS strongly correlates with the precipitation measurement data. This study indicates that the precipitation data from CHIRPS can be utilized as alternative precipitation data if measurement data are limited.

Necessity of Terrain Correction in Magnetotelluric Data Recorded from Garhwal Himalayan Region, India

The magnetotelluric (MT) method is one of the useful geophysical techniques to investigate deep crustal structures. However, in hilly terrains, e.g., the Garhwal Himalayan region, due to the highly undulating topography, MT responses are distorted. Such responses, if not corrected, may lead to the incorrect interpretation of geoelectric structures. In the present paper, we implemented terrain corrections in MT data recorded from the Garhwal Himalayan Corridor (GHC). We used AP3DMT, a 3D MT data modeling and inversion code written in the MATLAB environment. Terrain corrections in the MT impedance responses for 39 sites along the Roorkee–Gangotri profile in the period range of 0.01 s to 1000 s were first estimated using a synthetic model by recording the topography and locations of MT sites. Based on this study, we established the general character of the terrain and established where terrain corrections were necessary. The distortion introduced by topography was computed for each site using homogenous and heterogeneous models with actual topographic variations. Period-dependent, galvanic and inductive distortions were observed at different sites. We further applied terrain corrections to the real data recorded from the GHC. The corrected data were inverted, and the inverted model was compared with the corresponding inverted model obtained with uncorrected data. The modification in electrical resistivity features in the model obtained from the terrain-corrected response suggests the necessity of terrain correction in MT data recorded from the Himalayan region.

Bias-corrected CMIP6 global dataset for dynamical downscaling of the historical and future climate (1979–2100)

Dynamical downscaling is an important approach to obtaining fine-scale weather and climate information. However, dynamical downscaling simulations are often degraded by biases in the large-scale forcing itself. We constructed a bias-corrected global dataset based on 18 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) dataset. The bias-corrected data have an ERA5-based mean climate and interannual variance, but with a non-linear trend from the ensemble mean of the 18 CMIP6 models. The dataset spans the historical time period 1979–2014 and future scenarios (SSP245 and SSP585) for 2015–2100 with a horizontal grid spacing of (1.25° × 1.25°) at six-hourly intervals. Our evaluation suggests that the bias-corrected data are of better quality than the individual CMIP6 models in terms of the climatological mean, interannual variance and extreme events. This dataset will be useful for dynamical downscaling projections of the Earth’s future climate, atmospheric environment, hydrology, agriculture, wind power, etc.

Correction of Systematic Error in Global Temperature Analysis Related to Aging Effects

The white paint or white plastic of the housings of weather stations ages which leads to increased absorption of solar radiation and to increased temperature measurements. This alone would be a small error. However, the homogenization algorithms used by many different organizations repeatedly add this small value each time a weather station is renovated, renewed or replaced, which results in a substantial systematic error. This error occurs, because steps in the temperature data series are corrected as if they were permanent, but this is not always the case, particularly not in case of weather station aging and renewal.An in-depth analysis of the weather station data sets (homogenized and non-homogenized) confirmed the presence of the systematic error, proved the existence of statistically significant aging effects and allowed to quantify the size of the aging effects.I have quantified the effect of the aging effects on the climate curves by adding the aging functions to the temperature data points in the intervals between homogenizations. This corrected data base is analyzed using the GISTEMP tool.Here I show a reduction of the temperature change between the decades 1880-1890 and 2010-2020 from 1.43°C to 0.83°C CI(95%) [0.46°C; 1.19°C].

Data Agreement Analysis And Correction of Comparative Geomagnetic Vector Observations

Geomagnetism, similar to other areas of geophysics, is an observation-based science. Data agreement between comparative geomagnetic vector observations is one of the most important evaluation criteria for high-quality geomagnetic data. The main influencing factors affecting the agreement between comparative observational data are the attitude angle, scale factor, long-term time drift, and temperature. In this paper, we propose a method based on a genetic algorithm and linear regression to correct for these effects and use the distribution pattern of points in Bland–Altman plots with a 95% confidence interval length to qualitatively and quantitatively evaluate the agreement between the comparative observational data. In Bland–Altman plots with better agreement, that is, with the corrected data, more than 95% of the points are distributed within the 95% confidence interval and there is no obvious pattern in the distribution of the points. Meanwhile, the length of 95% confidence interval decreased significantly after the correction. The method presented here has positive effects on the vector instrumentation detection, enhancing the robustness of comparative observatory observations and reducing errors in judgments of the size and arrival time of large magnetic disturbances or rapid magnetic variations.

Creating hippocampal PPI connectivity maps with SPM12 batch files v1

Protocol for task-specific, effective connectivity analysis of hippocampus using SPM12 batch files and PPI analysis. This protocol requires input from an SPM analysis on smoothed, normalized, slice-time corrected data (files with swa prefix) using 4mm isovoxels, with the first contrast specifying effects of interest (an F-contrast, excluding any movement covariates but specifying every experimental and control condition). The batch files in this protocol generate connectivity maps from each voxel in both the left and right hippocampus, then generates averaged connectivity maps from specified regions of the hippocampus, eliminating the necessity to identify seed regions a priori from methods (such as activation) not directly related to connectivity analysis. This procedure can be repeated for as many as 30 subjects. The final step creates a random effects group analysis for each of 9 bilateral structural seeds, as described elsewhere (e.g., Burman, 2021 "Topography of hippocampal connectivity with sensorimotor cortex revealed by optimizing smoothing kernel and voxel size", doi: https://doi.org/10.1101/2020.05.14.096339); however, connectivity maps created by the protocol allow an investigator to run group analysis on any region of interest.