467 research outputs found
Global and Multi-level Thermosphere Neutral Density for selected periods with high geomagnetic activity
No full textThis repository contains the main outputs of the project entitled ESA's multi-level global thermosphere data products consistent with Swarm and GRACE (-FO). Find the details and the Technical Report by Ehsan Forootan from https://earth.esa.int/eogateway/activities/swarm-disc-pre-study-5-2 The multi-level global neutral density estimations during the seven storm periods can be found in this link. Storm1_2003_10_28_31.mat Storm5_2015_3_15_26.mat Storm2_2004_7_21_29.mat Storm6_2017_9_6_9.mat Storm3_2008_3_25_29.mat Storm7_2020_9_23_29.mat Storm4_2010_4_3_7.mat An animation of the Storm 2015 is uploaded as TND.gi
ESA’s multi-level global thermosphere data products consistent with Swarm and GRACE(-FO)
No full textIn this project, the possibility of using the space-based along-track Thermospheric Neutral Density (TND) estimates for generating the European Space Agency (ESA)'s Level 3 (L3) global multi-level TND data products is assessed. For this, the TND estimates along the CHAMP, GRACE, and Swarm satellites are used as observation within the sequential Calibration and Data Assimilation (C/DA) framework proposed by (Forootan et al., 2020 & 2022: doi:10.1093/gji/ggaa507 & doi:10.1038/s41598-022-05952-y).The C/DA approach is applied to re-calibrate four key parameters of the NRLMSISE-00 model, which are most sensitive to the thermospheric neutral mass and thermospheric temperature. The model with re-calibrated parameters is called 'C/DA-NRLMSISE-00', whose outputs fit to the space-based TNDs. The C/DA-NRLMSISE-00 is able to forecast TNDs and individual neutral mass compositions at any predefined vertical level (i.e., the same vertical coverage as the NRLMSISE-00) and arbitrary spatial-temporal resolution. Therefore, the C/DA method is tested to produce level 3 (L3) TND data consistent with space-based TND estimates.Seven periods (October 2003, July 2004, March 2008, April 2010, March 2015, September 2017, and September 2020), associated with relatively high geomagnetic activity, are selected for investigating the L3 products because most of available models represent difficulties to provide reasonable TND estimations. Independent comparisons (validations) are performed with the space-based TNDs that were not used within the C/DA framework (from CHAMP, GRACE, GOCE and Swarm missions), as well as with the outputs of other thermosphere models such as the Jacchia-Bowman 2008 (JB08) and the High Accuracy Satellite Drag Model (HASDM).The Project Report is available for download
Ein Bild und seine Geschichte
No full textAbedi E. A Picture and Its Story. Du : das Kulturmagazin. 2022;(912):93-97.Hermann Hesse's Siddhartha helped the Iranian mathematician Ehsan Abedi get over a difficult time in his life. During a study and research stay in Switzerland, he dedicated a painting to the author. Today it is part of the collection of the Museum Hermann Hesse.Dem iranischen Mathematiker Ehsan Abedi half Hermann Hesses Siddhartha über eine schwere Zeit in seinem Leben hinweg. Während eines Studien- und Forschungsaufenthalts in der Schweiz widmete er dem Autor ein Bild. Heute ist es Teil der Sammlung des Museums Hermann Hesse
Compiled notes for beloved juniors - series 1
No full textThese notes are kept by the author for more than 12 years. Author had started writing these notes since few weeks after he had completed his final MBBS exam with the intention to share officially with his juniors one day. He previously has shared some of them through social media since 13th May 2009. He decided to share now, he chooses year 202
Author Correction: RNAa-mediated epigenetic attenuation of the cell senescence via locus specific induction of endogenous SIRT1 (Scientific Reports, (2022), 12, 1, (15826), 10.1038/s41598-022-17972-9)
Full text link\ua9 The Author(s) 2023.The original version of this Article contained an error in the spelling of the author Ehsan Soleymaninejadian which was incorrectly given as Ehsan Soleimaninejadian. The original Article has been corrected
Assessing a calibration and data assimilation technique for predicting multi-level global thermospheric neutral density fields
No full textAn accurate estimation of the Thermospheric Neutral Density (TND) is important for predicting the orbit of satellites and objects, for example, those with the altitude of less than 1000 km. Models are often used to simulate TNDs but their accuracy is limited due to uncertainties. Satellite missions such as CHAMP, GRACE, GOCE, Swarm, and GRACE-FO or the Satellite Laser Ranging (SLR) missions can be used to estimate along-track TNDs. However, spatial and temporal coverage of these space borne TNDs is restricted to the mission design. To make the best use of the modelling tools and measurements, we applied these along-track TND measurements within the sequential Calibration and Data Assimilation (C/DA) framework proposed by (Forootan et al., 2022, doi:10.1038/s41598-022-05952-y). The C/DA is used to re-calibrate the NRLMSISE00 model, which is called “C/DA-NRLMSISE00”, whose outputs fit well to the introduced space-borne TNDs. The C/DA-NRLMSISE00 is applicable for forecasting TNDs and individual neutral mass compositions at any predefined vertical level (between ~100 and ~600 km) with user-defined spatial-temporal sampling. Seven periods (between 2003 - 2020) with considerable geomagnetic activity are selected for our investigations because most of the available models lack accuracy to provide reasonable TND simulations. Independent comparisons are performed with the space-borne TNDs that were not used within the C/DA framework, as well as with the outputs of other thermospheric models such as Jacchia-Bowman 2008 (JB2008) and the High Accuracy Satellite Drag Model (HASDM) database. The numerical results indicate that indeed the new model is suitable for producing multi-level global thermospheric neutral density fields
Statistical signal decomposition techniques for analyzing time-variable satellite gravimetry data
Full text linkThe time-variable gravity fields from the Gravity Recovery and Climate Experiment (GRACE) satellite mission provide valuable information about total water storage variations on a global scale. This quantity is difficult to observe with in-situ measurements but important for understanding regional energy balance, as well as for agricultural, and water resource management. In order to utilize GRACE time-variable level 2 products for studying global mass transport, there are two major problems that users face: 1) the presence of correlated noise in the level 2 potential spherical harmonic coefficients that increases with harmonic degree and causes ‘striping’ in the spatial domain, and 2) the fact that different physical signals are overlaid and difficult to separate from each other. These problems are termed the ‘signal-noise’ separation problem and the ‘signal-signal’ separation problem.
In this thesis, statistical decomposition methods are investigated to perform signal-noise and signal-signal separation using the time series of total water storage changes derived from satellite gravimetry products. In particular, the focus lies on the mathematical foundation of the second order statistical decomposition approach such as the principal component analysis (PCA), and its ordinary extensions, as well as the higher order statistical decomposition method of independent component analysis (ICA). The mathematical relationships between second and higher order statistical signal decomposition techniques are discussed. Uncertainties introduced in the extracted patterns, e.g., due to the limited time span of observations in computing auto-covariance matrices and higher order moment tensors, are addressed. The ICA approach is extended to the Complex ICA technique, which allows extraction of patterns that vary in space and time. Simulations of GRACE-like total water storage time series are used to assess the performance of the introduced statistical approaches. The ICA approach is applied to reduce the spatial leakage over the Australian continent, and to partition total water storage changes into terrestrial and groundwater storage changes over the Middle East. A new statistical approach is also introduced to forecast total water storage changes over West Africa, where it exhibits strong atmosphere-land-ocean interactions.Statistische Methoden der Signaltrennung zur Analyse zeitabhängiger Satellitengravimetriedaten
Zeitabhängige Gravitationsfelder der Gravity Recovery And Climate Experiment (GRACE) Satellitenmission liefern wertvolle Informationen über Gesamtwasserspeicheränderungen auf der Erde mit globaler Abdeckung. Diese Größe ist einerseits schwierig mit Hilfe lokaler Messungen zu beobachten, andererseits aber wichtig für das Verständnis regionaler Energiebilanzen und ebenfalls für Agrarwirtschaft und Gewässerbewirtschaftung. Um die zeitabhängigen Level 2 Produkte der GRACE-Mission zur Untersuchung globaler Massentransporte zu verwenden, muss der Nutzer sich mit zwei wichtigen Problemen auseinandersetzen: 1) mit dem Vorhandensein korrelierten Rauschens in den sphärisch harmonischen Potentialkoeffizienten, das mit zunehmendem harmonischen Grad ansteigt und ein ‘Streifenmuster’ im Ortsbereich verursacht und 2) mit der Tatsache, dass sich verschiedene physikalische Signale überlagern und schwer voneinander zu trennen sind. Diese Problematiken werden als ‘Signal-Rausch’ Trennungsproblem und ‘Signal-Signal’ Trennungsproblem bezeichnet.
In der vorliegenden Arbeit werden statistische Methoden der Signaltrennung untersucht, um ‘Signal-Rausch’ und ‘Signal-Signal’ Trennung unter Verwendung von Zeitreihen terrestrischer Wasserspeicheränderungen, die aus Produkten der Satellitengravimetrie abgeleitet werden, durchzuführen. Der Fokus liegt besonders auf der mathematischen Grundlage statistischer Ansätze zweiter Ordnung zur Zerlegung des Signals, wie der Principle Component Analysis (PCA) und seiner gebräuchlichen Erweiterungen, sowie der statistischen Methode höherer Ordnung zur Signaltrennung, bekannt als Independent Component Analysis (ICA). Die mathematischen Zusammenhänge der statistischen Methoden zweiter und höherer Ordnung zur Signalzerlegung werden erörtert. Unsicherheiten, die z.B. durch die Verwendung begrenzter Beobachtungszeiträume bei der Berechnung der Auto-Kovarianzmatrizen und Momente/Tensoren höherer Ordnung entstehen, werden behandelt. Der ICA Ansatz wird weiterentwickelt zur Komplexen ICA Methode, die das Extrahieren räumlich und zeitlich veränderlicher Muster ermöglicht. Simulierte Zeitreihen des GRACE Gesamtwasserspeichers werden erzeugt, um das Ergebnis der vorgestellten statistischen Methoden zu bewerten. Die ICA Methode wird zur Reduktion des (räumlichen) Leakage Effektes über Australien und zur Trennung der Gesamtwasserspeicheränderungen in Änderungen des terrestrischen und des Grundwasserspeichers im Mittleren Osten verwendet. Außerdem wird ein neuer statistischer Ansatz eingeführt, der Gesamtwasserspeicheränderungen über Westafrika, einer Region, die starke Interaktionen der Atmosphäre, des Landes und des Ozeans aufweist, prognostiziert
Water storage changes of the High Plain aquifer between 2015-2021
No full textThese data sets are the input and the outputs of ConBay and MCMC-DA approach to merge GRACE/GRACE-FO TWSC, SMAP and W3RA within the High Plain aquifer, between 2015-2021. The article to describe the approach can be cited as: Mehrnegar, N., Schumacher, M., Jagdhuber, T., & Forootan, E. (2023). Making the best use of GRACE, GRACE-FO and SMAP data through a Constrained Bayesian data-model integration. Water Resources Research, 59, e2023WR034544. https://doi.org/10.1029/2023WR03454
Efficient Implementation of Spontaneous Calcium Oscillations in the Central Nervous System on Reconfigurable Digital Boards
No full textThis work was supported by the Deanship of Scientific Research at King Khalid University under Grant RGP.1/243/42. This article was recommended by Associate Editor P. K. Meher. (Corresponding author: Yisu Ge.
Interannual variability of temperature in the UTLS region over Ganges–Brahmaputra–Meghna river basin based on COSMIC GNSS RO data
Full text linkPoor reliability of radiosonde records across South Asia imposes serious challenges in understanding the structure of upper-tropospheric and lower-stratospheric (UTLS) region. The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission launched in April 2006 has overcome many observational limitations inherent in conventional atmospheric sounding instruments. This study examines the interannual variability of UTLS temperature over the Ganges–Brahmaputra–Meghna (GBM) river basin in South Asia using monthly averaged COSMIC radio occultation (RO) data, together with two global reanalyses. Comparisons between August 2006 and December 2013 indicate that MERRA (Modern-Era Retrospective Analysis for Research Application) and ERA-Interim (European Centre for Medium-Range Weather Forecasts reanalysis) are warmer than COSMIC RO data by 2 °C between 200 and 50 hPa levels. These warm biases with respect to COSMIC RO data are found to be consistent over time. The UTLS temperature show considerable interannual variability from 2006 to 2013 in addition to warming (cooling) trends in the troposphere (stratosphere). The cold (warm) anomalies in the upper troposphere (tropopause region) are found to be associated with warm ENSO (El Niño–Southern Oscillation) phase, while quasi-biennial oscillation (QBO) is negatively (positively) correlated with temperature anomalies at 70 hPa (50 hPa) level. PCA (principal component analysis) decomposition of tropopause temperatures and heights over the basin indicate that ENSO accounts for 73 % of the interannual (non-seasonal) variability with a correlation of 0.77 with Niño3.4 index whereas the QBO explains about 10 % of the variability. The largest tropopause anomaly associated with ENSO occurs during the winter, when ENSO reaches its peak. The tropopause temperature (height) increased (decreased) by about 1.5 °C (300 m) during the last major El Niño event of 2009/2010. In general, we find decreasing (increasing) trend in tropopause temperature (height) between 2006 and 2013
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