Tendencies of long-term variations in ozone content and UV radiation by observation data at different latitudes

2021 ◽  
Author(s):  
Sergey Mayboroda ◽  
Sergey I. Kazakov ◽  
Vitaliya Metik-Diyunova ◽  
Alexander Boguslavsky
Keyword(s):  
Uv Radiation ◽  
Ozone Content ◽  
Observation Data ◽  
Long Term Variations

scholarly journals Long-term variations of the UV-B radiation over Central Europe as derived from the reconstructed UV time series

2004 ◽  
Vol 22 (5) ◽  
pp. 1473-1485 ◽  
Author(s):  
J. W. Krzyscin ◽  
K. Eerme ◽  
M. Janouch
Keyword(s):  
Central Europe ◽  
Uv Radiation ◽  
Total Ozone ◽  
Multivariate Adaptive Regression Splines ◽  
Transfer Model ◽  
Model Calculations ◽  
Radiative Processes ◽  
Long Term Changes ◽  
Long Term Variations

Abstract. The daily doses of the erythemally weighted UV radiation are reconstructed for three sites in Central Europe: Belsk-Poland (1966–2001), Hradec Kralove-Czech Republic (1964–2001), and Tõravere-Estonia (1967–2001) to discuss the UV climatology and the long-term changes of the UV-B radiation since the mid 1960s. Various reconstruction models are examined: a purely statistical model based on the Multivariate Adaptive Regression Splines (MARS) methodology, and a hybrid model combining radiative transfer model calculations with empirical estimates of the cloud effects on the UV radiation. Modeled long-term variations of the surface UV doses appear to be in a reasonable agreement with the observed ones. A simple quality control procedure is proposed to check the homogeneity of the biometer and pyranometer data. The models are verified using the results of UV observations carried out at Belsk since 1976. MARS provides the best estimates of the UV doses, giving a mean difference between the modeled and observed monthly means equal to 0.6±2.5%. The basic findings are: similar climatological forcing by clouds for all considered stations (~30% reduction in the surface UV), long-term variations in UV monthly doses having the same temporal pattern for all stations with extreme low monthly values (~5% below overall mean level) at the end of the 1970s and extreme high monthly values (~5% above overall mean level) in the mid 1990s, regional peculiarities in the cloud long-term forcing sometimes leading to extended periods with elevated UV doses, recent stabilization of the ozone induced UV long-term changes being a response to a trendless tendency of total ozone since the mid 1990s. In the case of the slowdown of the total ozone trend over Northern Hemisphere mid-latitudes it seems that clouds will appear as the most important modulator of the UV radiation both in long- and short-time scales over next decades. Key words. Atmospheric composition and structure (biospheric-atmosphere interaction) – Meteorology and atmospheric dynamics (climatology; radiative processes)

scholarly journals A global association between Covid-19 cases and airborne particulate matter at regional level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Angelo Solimini ◽  
F. Filipponi ◽  
D. Alunni Fegatelli ◽  
B. Caputo ◽  
C. M. De Marco ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Negative Binomial ◽  
Numerical Models ◽  
Regional Level ◽  
Pollution Level ◽  
Observation Data ◽  
Cumulative Number ◽  
Mixed Effect

AbstractEvidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM10, PM2.5), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m3 increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM2.5 and PM10 respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19.

scholarly journals Evaluations of Surface PM10 Concentration and Chemical Compositions in MERRA-2 Aerosol Reanalysis over Central and Eastern China

2021 ◽  
Vol 13 (7) ◽  
pp. 1317
Author(s):  
Xiaodan Ma ◽  
Peng Yan ◽  
Tianliang Zhao ◽  
Xiaofang Jia ◽  
Jian Jiao ◽  
...  
Keyword(s):  
Eastern China ◽  
Mainland China ◽  
Chemical Components ◽  
Chemical Compositions ◽  
Observation Data ◽  
Causative Factors ◽  
Routine Sampling ◽  
Aerosol Compositions ◽  
Modern Era

The chemical composition dataset of Aerosol Reanalysis of NASA’s Modern-Era Retrospective Analysis for Research and Application, version 2 (MERRAero) has not been thoroughly evaluated with observation data in mainland China due to the lack of long-term chemical components data. Using the 5-year data of PM10 mass concentrations and chemical compositions obtained from the routine sampling measurements at the World Meteorological Organization the Global Atmosphere Watch Programme regional background stations, Jing Sha (JS) and Lin’An (LA), in central and eastern China, we comprehensively evaluate the surface PM10 concentrations and chemical compositions such as sulfate (SO42−), organic carbon (OC) and black carbon (BC) derived from MERRAero. Overall, the concentrations of PM10, SO42−, OC and BC from the MERRAero agreed well with the measurements, despite a slight and consistent overestimation of BC concentrations and a moderate and persistent underestimation of PM10 concentrations throughout the study period. The MERRAero reanalysis of aerosol compositions performs better during the summertime than wintertime. By considering the nitrate particles in PM10 reconstruction, MERRAero performance can be significantly improved. The unreasonable seasonal variations of PM10 chemical compositions at station LA by MERRAero could be causative factors for the larger MERRAero discrepancies during 2016–2017 than the period of 2011–2013.

Fluvial magnetic susceptibility as a proxy for long‐term variations of mountain permafrost development in the Alp‐Carpathian region

Boreas ◽  
2021 ◽  
Author(s):  
Zoltán Püspöki ◽  
Philip Leonard Gibbard ◽  
Annamária Nádor ◽  
Edit Thamó‐Bozsó ◽  
Pál Sümegi ◽  
...  
Keyword(s):  
Magnetic Susceptibility ◽  
Carpathian Region ◽  
Mountain Permafrost ◽  
Long Term Variations

Long-term variations of C1–C5 alkyl nitrates and their sources in Hong Kong

2021 ◽  
Vol 270 ◽  
pp. 116285
Author(s):  
Lewei Zeng ◽  
Hai Guo ◽  
Xiaopu Lyu ◽  
Beining Zhou ◽  
Zhenhao Ling ◽  
...  
Keyword(s):  
Hong Kong ◽  
Alkyl Nitrates ◽  
Long Term Variations

Application of singular spectrum analysis in reconstruction of the annual signal from GRACE

2020 ◽  
Vol 14 (3) ◽  
pp. 295-302
Author(s):  
Chuandong Zhu ◽  
Wei Zhan ◽  
Jinzhao Liu ◽  
Ming Chen
Keyword(s):  
Time Series ◽  
Spectrum Analysis ◽  
Singular Spectrum Analysis ◽  
Mixture Effect ◽  
Singular Spectrum ◽  
Grace Data ◽  
Terrestrial Water ◽  
Annual Signal ◽  
Long Term Variations

AbstractThe mixture effect of the long-term variations is a main challenge in single channel singular spectrum analysis (SSA) for the reconstruction of the annual signal from GRACE data. In this paper, a nonlinear long-term variations deduction method is used to improve the accuracy of annual signal reconstructed from GRACE data using SSA. Our method can identify and eliminate the nonlinear long-term variations of the equivalent water height time series recovered from GRACE. Therefore the mixture effect of the long-term variations can be avoided in the annual modes of SSA. For the global terrestrial water recovered from GRACE, the peak to peak value of the annual signal is between 1.4 cm and 126.9 cm, with an average of 11.7 cm. After the long-term and the annual term have been deducted, the standard deviation of residual time series is between 0.9 cm and 9.9 cm, with an average of 2.1 cm. Compared with the traditional least squares fitting method, our method can reflect the dynamic change of the annual signal in global terrestrial water, more accurately with an uncertainty of between 0.3 cm and 2.9 cm.

scholarly journals Long term variations measurement of electromagnetic field exposures in Alcalá de Henares (Spain)

2017 ◽  
Vol 598 ◽  
pp. 657-668 ◽  
Author(s):  
R. Sánchez-Montero ◽  
C. Alén-Cordero ◽  
P.L. López-Espí ◽  
J.M. Rigelsford ◽  
F. Aguilera-Benavente ◽  
...  
Keyword(s):  
Electromagnetic Field ◽  
Long Term Variations

scholarly journals Long-Term Observations of Beach Variability at Hasaki, Japan

2020 ◽  
Vol 8 (11) ◽  
pp. 871
Author(s):  
Masayuki Banno ◽  
Satoshi Nakamura ◽  
Taichi Kosako ◽  
Yasuyuki Nakagawa ◽  
Shin-ichi Yanagishima ◽  
...  
Keyword(s):  
Morphological Change ◽  
High Frequency ◽  
Climate Changes ◽  
Wave Climate ◽  
Time Interval ◽  
Observation Data ◽  
Beach Profile ◽  
Water Level Variations ◽  
Monthly Variations

Long-term beach observation data for several decades are essential to validate beach morphodynamic models that are used to predict coastal responses to sea-level rise and wave climate changes. At the Hasaki coast, Japan, the beach profile has been measured for 34 years at a daily to weekly time interval. This beach morphological dataset is one of the longest and most high-frequency measurements of the beach morphological change worldwide. The profile data, with more than 6800 records, reflect short- to long-term beach morphological change, showing coastal dune development, foreshore morphological change and longshore bar movement. We investigated the temporal beach variability from the decadal and monthly variations in elevation. Extremely high waves and tidal anomalies from an extratropical cyclone caused a significant change in the long-term bar behavior and foreshore slope. The berm and bar variability were also affected by seasonal wave and water level variations. The variabilities identified here from the long-term observations contribute to our understanding of various coastal phenomena.

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