scholarly journals Weather control in radon flux time series from Schleswig-Holstein, Germany

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Manfred Mudelsee ◽  
Johannes Albert ◽  
Frank Sirocko
Keyword(s):  
Time Series ◽  
Close Association ◽  
Indoor Radon ◽  
Nonlinear Effects ◽  
Uranium Content ◽  
Temporal Variations ◽  
Meteorological Variables ◽  
Meteorological Forcing ◽  
Radon Flux ◽  
Time Lagged

AbstractIndoor radon exposure is a serious hazard to human health. The radon concentration in surface air varies spatially as a result of the uranium content in the underlying rocks. However, there exist also considerable knowledge gaps about temporal variations. Here we document the high temporal variability of radon flux from exhalation in high-resolution (hourly) time series from a site near Kleinneudorf, Schleswig-Holstein, Germany. By means of advanced techniques of statistical time series analysis, we show a close association between radon and meteorological variables (air temperature and air pressure). We identify four principal weather regimes that lead to different radon exhalation modes. For each of the modes, we construct a statistical linear model for radon prediction via the meteorological variables and their derivatives or time-lagged versions. The model explains between 53 and 86 percent of the variance. Many model deviations consist in excessively high measured radon values and hint at nonlinear effects. Other model deviations hint at non-meteorological forcing.

Temporal Variations of Radon Levels in Dwellings

1994 ◽  
Vol 56 (1-4) ◽  
pp. 323-325 ◽  
Author(s):  
P.R. Lomas ◽  
B.M.R. Green
Keyword(s):  
Structural Changes ◽  
Indoor Radon ◽  
Uranium Content ◽  
Temporal Variations ◽  
Geological Factors ◽  
The Stability ◽  
Over Time

Abstract Several factors determine the concentration of radon in a dwelling: the uranium content and permeability of the building ground; the construction and integrity of the floor; the habits and preferences of the occupants. Whereas the geological factors are unlikely to alter over time, it is quite possible for structural changes to occur, such as settlement cracking, which increases radon ingress, and for the occupants to change their living habits, such as increasing ventilation, which may reduce radon levels. New occupants may arrive with entirely different lifestyles. Questions arise about the variability of indoor radon levels as time progresses and as occupants change. The database of radon results for UK homes, which extends backwards for about a decade, is examined for repeat measurements, and the data are analysed so as to assess the stability or otherwise of the levels under changing circumstances.

Estimating time series of aerosol particle number concentrations in the five HEAPSS cities on the basis of measured air pollution and meteorological variables

2005 ◽  
Vol 39 (12) ◽  
pp. 2261-2273 ◽  
Author(s):  
Pentti Paatero ◽  
Pasi Aalto ◽  
Sally Picciotto ◽  
Tom Bellander ◽  
Gemma Castaño ◽  
...  
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Aerosol Particle ◽  
Particle Number ◽  
Meteorological Variables

scholarly journals The correlation between three teleconnections and leptospirosis incidence in the Kandy District, Sri Lanka, 2004–2019

2021 ◽  
Vol 49 (1) ◽  
Author(s):  
N. D. B. Ehelepola ◽  
Kusalika Ariyaratne ◽  
A. M. S. M. C. M. Aththanayake ◽  
Kamalanath Samarakoon ◽  
H. M. Arjuna Thilakarathna
Keyword(s):  
Time Series ◽  
Sri Lanka ◽  
Wavelet Analysis ◽  
Southern Oscillation ◽  
Population Data ◽  
Enso Modoki ◽  
Cross Correlation Analysis ◽  
Teleconnection Indices ◽  
Weather Parameters ◽  
Time Lagged

Abstract Background Leptospirosis is a bacterial zoonosis. Leptospirosis incidence (LI) in Sri Lanka is high. Infected animals excrete leptospires into the environment via their urine. Survival of leptospires in the environment until they enter into a person and several other factors that influence leptospirosis transmission are dependent upon local weather. Past studies show that rainfall and other weather parameters are correlated with the LI in the Kandy district, Sri Lanka. El Niño Southern Oscillation (ENSO), ENSO Modoki, and the Indian Ocean Dipole (IOD) are teleconnections known to be modulating rainfall in Sri Lanka. There is a severe dearth of published studies on the correlations between indices of these teleconnections and LI. Methods We acquired the counts of leptospirosis cases notified and midyear estimated population data of the Kandy district from 2004 to 2019, respectively, from weekly epidemiology reports of the Ministry of Health and Department of Census and Statistics of Sri Lanka. We estimated weekly and monthly LI of Kandy. We obtained weekly and monthly teleconnection indices data for the same period from the National Oceanic and Atmospheric Administration (NOAA) of the USA and Japan Agency for Marine-Earth Science and Technology (JAMSTEC). We performed wavelet time series analysis to determine correlations with lag periods between teleconnection indices and LI time series. Then, we did time-lagged detrended cross-correlation analysis (DCCA) to verify wavelet analysis results and to find the magnitudes of the correlations detected. Results Wavelet analysis displayed indices of ENSO, IOD, and ENSO Modoki were correlated with the LI of Kandy with 1.9–11.5-month lags. Indices of ENSO showed two correlation patterns with Kandy LI. Time-lagged DCCA results show all indices of the three teleconnections studied were significantly correlated with the LI of Kandy with 2–5-month lag periods. Conclusions Results of the two analysis methods generally agree indicating that ENSO and IOD modulate LI in Kandy by modulating local rainfall and probably other weather parameters. We recommend further studies about the ENSO Modoki and LI correlation in Sri Lanka. Monitoring for extreme teleconnection events and enhancing preventive measures during lag periods can blunt LI peaks that may follow.

scholarly journals GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses

2019 ◽  
Vol 12 (11) ◽  
pp. 4661-4679 ◽  
Author(s):  
Bin Cao ◽  
Xiaojing Quan ◽  
Nicholas Brown ◽  
Emilie Stewart-Jones ◽  
Stephan Gruber
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Ground Surface ◽  
Reanalysis Data ◽  
Meteorological Variables ◽  
Ensemble Simulations ◽  
Driving Time ◽  
Wide Range ◽  
Global Coverage ◽  
Uncertain Input

Abstract. Simulations of land-surface processes and phenomena often require driving time series of meteorological variables. Corresponding observations, however, are unavailable in most locations, even more so, when considering the duration, continuity and data quality required. Atmospheric reanalyses provide global coverage of relevant meteorological variables, but their use is largely restricted to grid-based studies. This is because technical challenges limit the ease with which reanalysis data can be applied to models at the site scale. We present the software toolkit GlobSim, which automates the downloading, interpolation and scaling of different reanalyses – currently ERA5, ERA-Interim, JRA-55 and MERRA-2 – to produce meteorological time series for user-defined point locations. The resulting data have consistent structure and units to efficiently support ensemble simulation. The utility of GlobSim is demonstrated using an application in permafrost research. We perform ensemble simulations of ground-surface temperature for 10 terrain types in a remote tundra area in northern Canada and compare the results with observations. Simulation results reproduced seasonal cycles and variation between terrain types well, demonstrating that GlobSim can support efficient land-surface simulations. Ensemble means often yielded better accuracy than individual simulations and ensemble ranges additionally provide indications of uncertainty arising from uncertain input. By improving the usability of reanalyses for research requiring time series of climate variables for point locations, GlobSim can enable a wide range of simulation studies and model evaluations that previously were impeded by technical hurdles in obtaining suitable data.

scholarly journals Evaluation of multiple forcing data sets for precipitation and shortwave radiation over major land areas of China

2017 ◽  
Vol 21 (11) ◽  
pp. 5805-5821 ◽  
Author(s):  
Fan Yang ◽  
Hui Lu ◽  
Kun Yang ◽  
Jie He ◽  
Wei Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Temporal Variations ◽  
Spatiotemporal Variability ◽  
Shortwave Radiation ◽  
Data Sets ◽  
Precipitation Data ◽  
Land Data Assimilation ◽  
Land Data Assimilation System ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. Precipitation and shortwave radiation play important roles in climatic, hydrological and biogeochemical cycles. Several global and regional forcing data sets currently provide historical estimates of these two variables over China, including the Global Land Data Assimilation System (GLDAS), the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) and the China Meteorological Forcing Dataset (CMFD). The CN05.1 precipitation data set, a gridded analysis based on CMA gauge observations, also provides high-resolution historical precipitation data for China. In this study, we present an intercomparison of precipitation and shortwave radiation data from CN05.1, CMFD, CLDAS and GLDAS during 2008–2014. We also validate all four data sets against independent ground station observations. All four forcing data sets capture the spatial distribution of precipitation over major land areas of China, although CLDAS indicates smaller annual-mean precipitation amounts than CN05.1, CMFD or GLDAS. Time series of precipitation anomalies are largely consistent among the data sets, except for a sudden decrease in CMFD after August 2014. All forcing data indicate greater temporal variations relative to the mean in dry regions than in wet regions. Validation against independent precipitation observations provided by the Ministry of Water Resources (MWR) in the middle and lower reaches of the Yangtze River indicates that CLDAS provides the most realistic estimates of spatiotemporal variability in precipitation in this region. CMFD also performs well with respect to annual mean precipitation, while GLDAS fails to accurately capture much of the spatiotemporal variability and CN05.1 contains significant high biases relative to the MWR observations. Estimates of shortwave radiation from CMFD are largely consistent with station observations, while CLDAS and GLDAS greatly overestimate shortwave radiation. All three forcing data sets capture the key features of the spatial distribution, but estimates from CLDAS and GLDAS are systematically higher than those from CMFD over most of mainland China. Based on our evaluation metrics, CLDAS slightly outperforms GLDAS. CLDAS is also closer than GLDAS to CMFD with respect to temporal variations in shortwave radiation anomalies, with substantial differences among the time series. Differences in temporal variations are especially pronounced south of 34° N. Our findings provide valuable guidance for a variety of stakeholders, including land-surface modelers and data providers.

scholarly journals Identification and Modeling Carbon and Energy Fluxes from Eddy Covariance Time Series Measurements in Rice and Rainfed Crops

2021 ◽  
Vol 9 (1) ◽  
pp. 9
Author(s):  
Víctor Cicuéndez ◽  
Javier Litago ◽  
Víctor Sánchez-Girón ◽  
Laura Recuero ◽  
César Sáenz ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Primary Production ◽  
Eddy Covariance ◽  
Carbon Balance ◽  
Gross Primary Production ◽  
Meteorological Variables ◽  
Water Fluxes ◽  
Energy Fluxes ◽  
Global Carbon

Gross primary production (GPP) represents the carbon (C) uptake of ecosystems through photosynthesis and it is the largest flux of the global carbon balance. Our overall objective in this research is to identify and model GPP dynamics and its relationship with meteorological variables and energy fluxes based on time series analysis of eddy covariance (EC) data in two different agroecosystems, a Mediterranean rice crop in Spain and a rainfed cropland in Germany. Crops exerted an important influence on the energy and water fluxes dynamics existing a clear feedback between GPP, meteorological variables and energy fluxes in both type of crops.

Trade-offs between deep (magmatic) and shallow (hydrological) forcings on volcanic unrest at La Soufrière de Guadeloupe (Lesser Antilles)

2021 ◽  
Author(s):  
David Jessop ◽  
Roberto Moretti ◽  
Séverine Moune ◽  
Vincent Robert
Keyword(s):  
Time Series ◽  
Hydrothermal System ◽  
Temporal Variations ◽  
Temperature Record ◽  
Trade Offs ◽  
External Forcings ◽  
Seismic Swarms ◽  
Long Time ◽  
Deep Activity

<p>Fumarolic gas composition and temperature record deep processes that generate and transfer heat and mass towards the surface.  These processes are a result of the emplacement, degassing and cooling of magma and the overturning of the above hydrothermal system.  A reasonable expectation, and too often an unproved assumption, is that fumarole temperatures and the deep heat sources vary on similar timescales.  Yet signals from deep and shallow processes have vastly different temporal variations.  This indicates that signals arising from deep activity may be masked or modified by intervening hydrothermal processes, such as fluid-groundrock reactions in which secondary minerals play a major role.  Clearly, this complicates the interpretation of the signals such as the joint variation of fumarole vent temperature and geochemical ratios in terms of what is occurring at depth.  So what do the differences between the timescales governing deep and shallow processes tell us about the intervening transport mechanisms?</p><p>At the volcanic dome of La Soufrière de Guadeloupe, the Observatoire Volcanologique et Sismologique de la Guadeloupe has performed weekly-to-monthly in-situ vent gas sampling over many years.  These analyses reliably track several geochemical species ratios over time, which provide important information about the evolution of deep processes.  Vent temperature is measured as part of the in-situ sampling, giving a long time series of these measurements.  Here, we look to exploit the temporal variations in these data to establish the common processes, and also to determine why these signals differ.  By fitting sinusoids to the gas-ratio time series we find that several of the deep signals are strongly sinusoidal.  For example, the He/CH<sub>4</sub> and CO<sub>2</sub>/CH<sub>4</sub> ratios, which involve conservative components and mark the injection of deep and hot magmatic fluids, oscillate on a timescale close to 3 years. We also analyse the frequency content of the temperature measurements since 2011 and find that such long signals are not seen.  This may be due to internal buffering by the hydrothermal system, but other external forcings are also present.  From these data we build up a more informed model of the heat-and-mass supply chain from depth to the surface.  This will potentially allow us to predict future unrest (e.g. thermal crises, seismic swarms), and distinguish between sources of unrest.</p>

scholarly journals Passive microwave-derived spatial and temporal variations of summer melt on the Greenland ice sheet

1993 ◽  
Vol 17 ◽  
pp. 233-238 ◽  
Author(s):  
Thomas L. Mote ◽  
Mark R. Anderson ◽  
Karl C. Kuivinen ◽  
Clinton M. Rowe
Keyword(s):  
Time Series ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Late Summer ◽  
Temporal Variations ◽  
Early Summer ◽  
Passive Microwave ◽  
Brightness Temperatures ◽  
Surface Melt ◽  
Major Surface

Passive microwave-brightness temperatures over the Greenland ice sheet are examined during the melt season in order to develop a technique for determining surface-melt occurrences. Time series of Special Sensor Microwave/ Imager (SSM/I) data are examined for three locations on the ice sheet, two of which are known to experience melt. These two sites demonstrate a rapid increase in brightness temperatures in late spring to early summer, a prolonged period of elevated brightness temperatures during the summer, and a rapid decrease in brightness temperatures during late summer. This increase in brightness temperatures is associated with surface snow melting. An objective technique is developed to extract melt occurrences from the brightness-temperature time series. Of the two sites with summer melt, the site at the lower elevation had a longer period between the initial and final melt days and had more total days classified as melt during 1988 and 1989. The technique is then applied to the entire Greenland ice sheet for the first major surface-melt event of 1989. The melt-zone signal is mapped from late May to early June to demonstrate the advance and subsequent retreat of one “melt wave”. The use of such a technique to determine melt duration and extent for multiple years may provide an indication of climate change.

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