scholarly journals The blessing of dimensionality for the analysis of climate data

2021 ◽  
Vol 28 (3) ◽  
pp. 409-422
Author(s):  
Bo Christiansen
Keyword(s):  
Climate Data ◽  
High Dimensions ◽  
Sample Mean ◽  
Simple Description ◽  
Atmospheric Sciences ◽  
Large Samples ◽  
Concentration Phenomena ◽  
Spatially Extended ◽  
Long Time ◽  
Effective Dimensions

Abstract. We give a simple description of the blessing of dimensionality with the main focus on the concentration phenomena. These phenomena imply that in high dimensions the lengths of independent random vectors from the same distribution have almost the same length and that independent vectors are almost orthogonal. In the climate and atmospheric sciences we rely increasingly on ensemble modelling and face the challenge of analysing large samples of long time series and spatially extended fields. We show how the properties of high dimensions allow us to obtain analytical results for e.g. correlations between sample members and the behaviour of the sample mean when the size of the sample grows. We find that the properties of high dimensionality with reasonable success can be applied to climate data. This is the case although most climate data show strong anisotropy and both spatial and temporal dependence, resulting in effective dimensions around 25–100.

scholarly journals The blessing of dimensionality for the analysis of climate data

2021 ◽  
Author(s):  
Bo Christiansen
Keyword(s):  
Climate Data ◽  
High Dimensions ◽  
Sample Mean ◽  
Simple Description ◽  
Atmospheric Sciences ◽  
Large Samples ◽  
Concentration Phenomena ◽  
Spatially Extended ◽  
Long Time ◽  
Effective Dimensions

Abstract. We give a simple description of the blessing of dimensionality with the main focus on the concentration phenomena. These phenomena imply that in high dimensions the length of independent random vectors from the same distribution have almost the same length and that independent vectors are almost orthogonal. In climate and atmospheric sciences we rely increasingly on ensemble modelling and face the challenge of analysing large samples of long time-series and spatially extended fields. We show how the properties of high dimensions allow us to obtain analytical results for, e.g., correlations between sample members and the behaviour of the sample mean when the size of the sample grows. We find that the properties of high dimensionality with reasonable success can be applied to climate data. This is the case although most climate data show strong anisotropy and both spatial and temporal dependence resulting in effective dimensions around 25–100.

scholarly journals Noise performance of microwave humidity sounders over their life time

2017 ◽  
Author(s):  
Imke Hans ◽  
Martin Burgdorf ◽  
Viju O. John ◽  
Jonathan Mittaz ◽  
Stefan A. Buehler
Keyword(s):  
Uncertainty Propagation ◽  
Life Time ◽  
Noise Spectrum ◽  
Data Series ◽  
Allan Deviation ◽  
Noise Performance ◽  
Climate Data ◽  
Time Data ◽  
Accessible Information ◽  
Long Time

Abstract. The microwave humidity sounders Special Sensor Microwave Water Vapour Profiler (SSMT-2), Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Humidity Sounder (MHS) to date have been providing data records for 25 years. So far, the data records lack uncertainty information essential for constructing consistent long time data series. In this study, we assess the quality of the recorded data with respect to the uncertainty caused by noise. We calculate the noise on the raw calibration counts from the deep space view (DSV) of the instrument and the Noise Equivalent Differential Temperature (NEΔT) as a measure for the radiometer sensitivity. For this purpose, we use the Allan Deviation that is not biased from an underlying varying mean of the data and that has been suggested only recently for application in atmospheric remote sensing. Moreover, we use the bias function related to the Allan Deviation to infer the underlying spectrum of the noise. As examples, we investigate the noise spectrum in flight for some instruments. For the assessment of the noise evolution in time, we provide a descriptive and graphical overview of the calculated NEΔT over the life span of each instrument and channel. This overview can serve as an easily accessible information for users interested in the noise performance of a specific instrument, channel and time. Within the time evolution of the noise, we identify periods of instrumental degradation, which manifest themselves in an increasing NEΔT, and periods of erratic behaviour, which show sudden increases of NEΔT interrupting the overall smooth evolution of the noise. From this assessment and subsequent exclusion of the aforementioned periods, we present a chart showing available data records with NEΔT < K. Due to overlapping life spans of the instruments, these reduced data records still cover without gaps the time since 1994 and may therefore serve as first step for constructing long time series. Our method for count noise estimation, that has been used in this study, will be used in the data processing to provide input values for the uncertainty propagation in the generation of a new set of Fundamental Climate Data Records (FCDR) that are currently produced in the project Fidelity and Uncertainty in Climate data records from Earth Observation (FIDUCEO).

Solar Signals in Surface Climate

2015 ◽  
Author(s):  
Joanna D. Haigh ◽  
Peter Cargill
Keyword(s):  
Climate Change ◽  
The Sun ◽  
Climate Data ◽  
Growth Rings ◽  
Surface Climate ◽  
Annual Growth Rings ◽  
Weather And Climate ◽  
Long Time ◽  
Established Technique

This chapter looks at how the Sun varies in terms of its emissions of radiation and particles and how these changes might be associated with variations in weather and climate on Earth. Investigations of climate variability and climate change depend crucially on the existence, length, and quality of meteorological records. Ideally, records would consist of long time series of measurements made by well-calibrated instruments densely situated across the globe. For longer periods, and in remote regions, records have to be reconstructed from indirect indicators of climate known as proxy data. The chapter introduces one well-established technique for providing proxy climate data: dendrochronology, or the study of the successive annual growth rings of trees.

scholarly journals QUANTIFYING EMERGENCE IN TERMS OF PERSISTENT MUTUAL INFORMATION

2010 ◽  
Vol 13 (03) ◽  
pp. 327-338 ◽  
Author(s):  
ROBIN C. BALL ◽  
MARINA DIAKONOVA ◽  
ROBERT S. MACKAY
Keyword(s):  
Mutual Information ◽  
Chaotic Behavior ◽  
Past History ◽  
Logistic Map ◽  
Period Doubling ◽  
Emergent Behavior ◽  
Complexity Measures ◽  
Spatially Extended ◽  
Long Time ◽  
Definition Of

We define Persistent Mutual Information (PMI) as the Mutual (Shannon) Information between the past history of a system and its evolution significantly later in the future. This quantifies how much past observations enable long-term prediction, which we propose as the primary signature of (Strong) Emergent Behavior. The key feature of our definition of PMI is the omission of an interval of "present" time, so that the mutual information between close times is excluded: this renders PMI robust to superposed noise or chaotic behavior or graininess of data, distinguishing it from a range of established Complexity Measures. For the logistic map, we compare predicted with measured long-time PMI data. We show that measured PMI data captures not just the period doubling cascade but also the associated cascade of banded chaos, without confusion by the overlayer of chaotic decoration. We find that the standard map has apparently infinite PMI, but with well-defined fractal scaling which we can interpret in terms of the relative information codimension. Whilst our main focus is in terms of PMI over time, we can also apply the idea to PMI across space in spatially-extended systems as a generalization of the notion of ordered phases.

scholarly journals Winterization of Texan power system infrastructure is profitable but risky

2021 ◽  
Author(s):  
Katharina Gruber ◽  
Tobias Gauster ◽  
Gregor Laaha ◽  
Peter Regner ◽  
Johannes Schmidt
Keyword(s):  
Time Series ◽  
Power Plant ◽  
Power Plants ◽  
Large Scale ◽  
Low Frequency ◽  
Cold Spell ◽  
Climate Data ◽  
Temperature Dependent ◽  
Long Time ◽  
Regulatory Measures

We deliver the first analysis of the 2021 cold spell in Texas which combines temperature dependent load estimates with temperature dependent estimates of power plant outages to understand the frequency of loss of load events, using a 71 year long time series of climate data. The expected avoided loss from full winterization is 11.74bn\$ over a 30 years investment period. We find that large-scale winterization, in particular of gas infrastructure and gas power plants, would be profitable, as related costs for winterization are substantially lower. At the same moment, the necessary investments involve risk due to the low-frequency of events – the 2021 event was the largest and we observe only 8 other similar ones in the set of 71 simulated years. Regulatory measures may therefore be necessary to enforce winterization.

scholarly journals Hydrodynamics of quantum entropies in Ising chains with linear dissipation

2022 ◽  
Author(s):  
Vincenzo Alba ◽  
Federico Carollo
Keyword(s):  
Mutual Information ◽  
Hydrodynamic Limit ◽  
Transverse Field ◽  
Quantum Correlations ◽  
Von Neumann Entropy ◽  
Simple Description ◽  
Von Neumann ◽  
Long Time ◽  
Dynamics Of Correlations ◽  
Quasiparticle Picture

Abstract We study the dynamics of quantum information and of quantum correlations after a quantum quench, in transverse field Ising chains subject to generic linear dissipation. As we show, in the hydrodynamic limit of long times, large system sizes, and weak dissipation, entropy-related quantities —such as the von Neumann entropy, the Rényi entropies, and the associated mutual information— admit a simple description within the so-called quasiparticle picture. Specifically, we analytically derive a hydrodynamic formula, recently conjectured for generic noninteracting systems, which allows us to demonstrate a universal feature of the dynamics of correlations in such dissipative noninteracting system. For any possible dissipation, the mutual information grows up to a time scale that is proportional to the inverse dissipation rate, and then decreases, always vanishing in the long time limit. In passing, we provide analytic formulas describing the time-dependence of arbitrary functions of the fermionic covariance matrix, in the hydrodynamic limit.

scholarly journals The infection tree of global epidemics

2014 ◽  
Vol 2 (1) ◽  
pp. 132-137 ◽  
Author(s):  
ANA PASTORE Y PIONTTI ◽  
MARCELO FERREIRA DA COSTA GOMES ◽  
NICOLE SAMAY ◽  
NICOLA PERRA ◽  
ALESSANDRO VESPIGNANI
Keyword(s):  
Visual Analytics ◽  
Information Technologies ◽  
Large Scale ◽  
Human Mobility ◽  
Global Dynamics ◽  
The World ◽  
Spatially Extended ◽  
Long Time ◽  
Reduction Methods ◽  
The One

The spreading of transmissible infectious diseases is inevitably entangled with the dynamics of human population. Humans are the carrier of the pathogen, and the large-scale travel and commuting patterns that govern the mobility of modern societies are defining how epidemics and pandemics travel across the world. For a long time, the development of quantitative spatially explicit models able to shed light on the global dynamics of pandemic has been limited by the lack of detailed data on human mobility. In the last 10 years, however, these limits have been lifted by the increasing availability of data generated by new information technologies, thus triggering the development of computational (microsimulation) models working at a level of single individuals in spatially extended regions of the world. Microsimulations can provide information at very detailed spatial resolutions and down to the level of single individuals. In addition, computational implementations explicitly account for stochasticity, allowing the study of multiple realizations of epidemics with the same parameters' distribution. While on the one hand these capabilities represent the richness of microsimulation methods, on the other hand they face us with a huge amount of information that requires the use of specific data reduction methods and visual analytics.

Partial differential equations and stochastic methods in molecular dynamics

Acta Numerica ◽  
2016 ◽  
Vol 25 ◽  
pp. 681-880 ◽  
Author(s):  
Tony Lelièvre ◽  
Gabriel Stoltz
Keyword(s):  
Molecular Dynamics ◽  
Partial Differential Equations ◽  
Differential Equations ◽  
Statistical Physics ◽  
Stochastic Dynamics ◽  
Planck Equation ◽  
Stochastic Methods ◽  
High Dimensions ◽  
Partial Differential ◽  
Long Time

The objective of molecular dynamics computations is to infer macroscopic properties of matter from atomistic models via averages with respect to probability measures dictated by the principles of statistical physics. Obtaining accurate results requires efficient sampling of atomistic configurations, which are typically generated using very long trajectories of stochastic differential equations in high dimensions, such as Langevin dynamics and its overdamped limit. Depending on the quantities of interest at the macroscopic level, one may also be interested in dynamical properties computed from averages over paths of these dynamics.This review describes how techniques from the analysis of partial differential equations can be used to devise good algorithms and to quantify their efficiency and accuracy. In particular, a crucial role is played by the study of the long-time behaviour of the solution to the Fokker–Planck equation associated with the stochastic dynamics.

scholarly journals In Vitro Estimation of Lead Content in Nepalese Traditional Ayurvedic Medicines Commonly Used in Children

2013 ◽  
Vol 33 (2) ◽  
pp. 103-105
Author(s):  
Anil Ojha
Keyword(s):  
Heavy Metals ◽  
Side Effects ◽  
Paediatric Population ◽  
Detectable Level ◽  
Lead Content ◽  
Ayurvedic Medicine ◽  
Over The Counter ◽  
Large Samples ◽  
Long Time

Introduction: Ayurvedic remedies are popularly used in practice for long time in Nepal. It is regarded as safe and free from side effects. However there are published reports of the high content of heavy metals like lead in such preparations. No such study has been done in Nepal looking at the lead content in ayurvedic preparations. The aim of this study was to detect the level of lead in commonly used ayurvedic remedies used in paediatric population if any. Materials and Methods: Seventeen samples were selected for lead estimation based on frequency of prescription and over the counter dispense. All of them were analyzed using Atomic Absorption Spectrophotometer (AAS) 6300 using flame mode. Results: None of the samples had detectable level of lead in parts per billion. Conclusion: Though this study did not detect lead in the seventeen samples of ayurvedic medicine, a larger study is needed involving large samples of these medicines with use of more sensitive equipment for testing. DOI: http://dx.doi.org/10.3126/jnps.v33i2.8314   J Nepal Paediatr Soc. 2013; 33(2):103-105

scholarly journals Interactive access to climate data from Germany

2021 ◽  
Author(s):  
Frank Kratzenstein ◽  
Frank Kaspar
Keyword(s):  
Meteorological Data ◽  
Free Access ◽  
Climate Data ◽  
Oracle Database ◽  
Phenological Data ◽  
Observation Systems ◽  
Long Time ◽  
Data Portal ◽  
Set Up ◽  
User Friendly

&lt;p&gt;In recent years, the DWD has significantly expanded free access to its climate observations. A first step was a simple FTP site with the possibility to download archives with different data categories, e.g. national and international station-based meteorological data, derived parameters, gridded products, and special categories like phenological data. The data are based on the DWD's observation systems for Germany as well as on the DWD's international activities.&lt;/p&gt;&lt;p&gt;Based on the consistent implementation of OGC standards, an interactive and user-friendly access to the data has been created with the development of the DWD climate portal.&lt;/p&gt;&lt;p&gt;In addition to browsing, previewing, running basic analysis and downloading the data, the available OGC services enable users to set up their own services on the DWD data. Along with the free and extended access to the data and services, the users' demands on the availability, quality, and detail of the metadata also increased significantly. Maintaining and linking metadata to the opendata and services remains a challenge. However, INSPIRE and WIGOS are paving the way to a unified solution and overcoming the problems.&lt;/p&gt;&lt;p&gt;Another challenging requirement was to provide interactive access to long time series from gridded products to the users. To accomplish this, we have moved away from a previously file-based approach to storing the raster data as a georaster in an Oracle database. This design allows us a combined analysis of raster and station data not only in the climate data portal but also in the central climate database.&lt;/p&gt;&lt;p&gt;The presentation will provide a technical and functional overview of the DWD climate data portal.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document