Monitoring promieniotwórczości przyziemnej warstwy powietrza w Polsce jest prowadzony przez Centralne Laboratorium Ochrony Radiologicznej, które do tego celu wykorzystuje system sieci wysokoczułych stacji wczesnego ostrzegania ASS-500. Pobór i pomiar aerozoli powietrza wykonywany jest w sposób ciągły w Warszawie od lat siedemdziesiątych, a od 1992 r. w 12 stacjach w całym kraju. Stacje monitorują m.in. stężenie berylu-7 o czasie połowiczego rozpadu 53 dni, który powstaje w wyniku reakcji promieniowania kosmicznego (GCR oraz SEP) z azotem i tlenem w górnych warstwach stratosfery i troposfery. W pracy przedstawiono wyniki pomiarów Be-7 w Warszawie, Katowicach oraz Gdyni w okresie 2002-2004, gdzie największa sezonowa depozycja Be-7 pojawia się cyklicznie w okresie wiosennym, co jest spowodowane m.in procesami mieszania się mas powietrza w troposferze i stratosferze. Przedstawiono również wyniki pomiarów stężenia Be-7 z okresu 2000-2009, w którym została zaobserwowana anomalia aktywności Słońca w postaci wystąpienia tzw. podwójnego maksimum w cyklu 11 -letnim.
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Sun is the primary source of energy in space. It generates a magnetic feld which released in solar fares or coronal mass ejections for 11-year solar cycle that causes the occurrence of space weather. Diferent researchers in diferent parts of the world indicated that space weather highly afects agriculture production. However, in Ethiopia context especially Chokie mountain basin the infuence of space weather on agriculture was not documented. Hence, this paper was aimed at investigating the impact of space weather on agriculture products over Chokie mountain basin. Assessment of space weather impacts on agriculture product is quite useful to balance energy and food security over developing countries like Ethiopia. Space weather (sunspot number), precipitation, temperature, and agriculture data were used for this study. Descriptive quantitative design method was applied on the data of agriculture products and climate variables. Furthermore, regression models with the help of MATLAB software were applied for data analysis. The relation between crop yield (tef, wheat, and maize) with sunspot number, temperature, and precipitation were analyzed in each agro-ecological zones using 31 years (1990–2019) data over Chokie mountain basin. The results showed that correlation coefcients between sunspot number with annual average value of temperature, precipitation, maize, tef, and wheat were found 0.11,−0.32,−0.47,−0.52, and−0.59, respectively. Sunspot had highly negatively correlated with annual spatial average value of tef and wheat. Generally, the occurrence of space weather (sunspot) leads to reduction of wheat and tef over the study area. Hence, shifting cultivation strategy is needed for local community during the occurrence of 11-year solar cycles frequency.
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Models belonging to the ionosphere that is directly affected by factors such as solar activity, geomagnetic storm, earthquake, seasonal changes, and geographical location need to be considered altogether. In this sense, the cause of the ionospheric anomalies should be meticulously distinguished from each other. Ionospheric anomalies that occur before or (and) after an earthquake have a serious place in earthquake prediction studies. Total electron content (TEC) is one of the significant parameters to be able to discuss the anomalies of the ionosphere. This essay investigates ionospheric anomalies before and after the Mw 6.5 Samar, Philippines (12.025° N, 125.416° E and November 18, 2003, at 17:14 UT) earthquake. The paper analyzes anomalies with the aid of the TEC (TECU) map. In the paper, the time-domain TEC variables are transferred to the frequency-domain for observing some clues-peaks by short-term Fourier transformation spectral analysis. The discussion handles the effect of the solar activity with the F10.7 (sfu) index and the effect of geomagnetic storms with Bz (nT), v (km/s), P (nPa), E (mV/m), Kp (nT), and Dst (nT) parameters (index). The lower and upper boundaries of the TEC map obtained from the International Reference Ionosphere (IRI-2016) are calculated with the help of median and standard deviation. The boundary-setting process is named statistical analysis. TEC data exceeding the boundaries are marked as anomaly data. According to the paper, 11-day anomalies (9-day of which belong to pre-earthquake) are detected. Probably, the anomalies observed on November 6, 7, and 12 belong to the Samar earthquake.
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