Long-term trends in solar activity. Variations of solar indices in the last 40 years

We analyze long-term variations of several solar activity indices(AIs) that have been measured over the last 40 years. With this goal, we study the AIs that characterize the fluxes from different areas in the solar atmosphere. Our consideration of mutual correlations between the solar indices is based on the study of relationships between them in the period from 1950 to 1990. This period of time, covering activity cycles 19–22, is characterized by relatively stable relations between the indices. We investigate the normalized variations of these indices in recent time in relation to their values which were calculated by considering radiation from the Sun in the radio range at a wavelength of 10.7 cm(F10.7) in 1950–1990.The analysis of time series, representing variations of the normalized AI(AIFF) in solar cycles 23–24,shows different trends exist for different indices in terms of their long-term behavior. We assume that variations of normalized International Sunspot Number(SSN), F530.3 and Flare Index, which have shown sharp decreases in the last 40 years, are possibly associated with a decrease in the intensity of large-scale magnetic fields in the photosphere(SSN) and in the corona(the coronal index and the Flare Index).     

AMSR-E sea surface temperature (SST) charts enhancement

Microwave satellite images used for retrieving sea surface temperatures often have such distortions as noise and blurring of the thermal fronts. An image processing approach based on the Mumford-Shah model of optimal image approximation is considered for the solution to this problem. We divide images into flat areas and frontal zones, and then process these areas separately. Image fragmentation is based on automatic detection of the thermal front lines. SST enhancement in frontal zones is achieved by using image deconvolution methods. It has been shown that SST errors in high gradient areas reach 1–3 °C. The proposed approach can decrease this discrepancy.     

Field survey of the 1994 Mindoro Island,Philippines tsunami

This is a report of the field survey of the November 15, 1994 Mindoro Island, Philippines, tsunami generated by an earthquake (M=7.0) with a strike-slip motion. We will report runup heights from 54 locations on Luzon, Mindoro and other smaller islands in the Cape Verde passage between Mindoro and Luzon. Most of the damage was concentrated along the northern coast of Mindoro. Runup height distribution ranged 3–4 m at the most severely damaged areas and 2–4 in neighboring areas. The tsunami-affected area was limited to within 10 km of the epicenter. The largest recorded runup value of 7.3 m was measured on the southwestern coast of Baco Island while a runup of 6.1 m was detected on its northern coastline. The earthquake and tsunami killed 62 people, injured 248 and destroyed 800 houses. As observed in other recent tsunami disasters, most of the casualties were children. Nearly all eyewitnesses interviewed described the first wave as a leading-depression wave. Eyewitnesses reported that the main direction of tsunami propagation was SW in Subaang Bay, SE in Wawa and Calapan, NE on Baco Island and N on Verde Island, suggesting that the tsunami source area was in the southern Pass of Verde Island and that the wave propagated rapidly in all directions. The fault plane extended offshore to the N of Mindoro Island, with its rupture originating S of Verde Island and propagating almost directly south to the inland of Mindoro, thereby accounting for the relatively limited damage area observed on the N of Mindoro.     

Sumatra tsunami: lessons from modeling

The need for the combination of seismic data with real-time wave height information for an effective prediction of tsunami impact is emphasized in the paper. A preliminary, but comprehensive study of arrival times, wave heights and run-up values at a number of locations and tide gage stations throughout the Indian Ocean seaboard is presented. Open ocean wave height data from satellite observations are analyzed and used in the reconstruction of a tsunami source mechanism for the December 26, 2004 event. The reconstructed source is then used to numerically estimate tsunami impact along the Indian Ocean seaboard, including wave height, and arrival times at 12 tide gage stations, and inundation at 3 locations on the coast of India. The December 2004, as well as the March 28, 2005 tsunamis are investigated and their differences in terms of tsunami generation are analyzed and presented as a clear example of the need for both, seismic and real-time tsunami data for a reliable tsunami warning system in the Indian Ocean.     

M TSU : Recovering Seismic Moments from Tsunameter Records

We define a new magnitude scale, M_TSU, allowing the quantification of the seismic moment M₀ of an earthquake based on recordings of its tsunami in the far field by ocean-bottom pressure sensors (``tsunameters') deployed in ocean basins, far from continental or island shores which are known to affect profoundly and in a nonlinear fashion the amplitude of the tsunami wave. The formula for M_TSU, M_TSU = log₁₀ M₀ − 20 = log₁₀ X (ω) + C_D^TSU + C_S^TSU + C₀, where X (ω) is the spectral amplitude of the tsunami, C_D^TSU a distance correction and C_S^TSU a source correction, is directly adapted from the mantle magnitude M_m introduced for seismic surface waves by Okal and Talandier. Like M_m, its corrections are fully justified theoretically based on the representation of a tsunami wave as a branch of the Earth's normal modes. Even the locking constant C₀, which may depend on the nature of the recording (surface amplitude of the tsunami or overpressure at the ocean floor) and its units, is predicted theoretically. M_TSU combines the power of a theoretically developed algorithm, with the robustness of a magnitude measurement that does not take into account such parameters as focal geometry and exact depth, which may not be available under operational conditions in the framework of tsunami warning. We verify the performance of the concept on simulations of the great 1946 Aleutian tsunami at two virtual gauges, and then apply the algorithm to 24 records of 7 tsunamis at DART tsunameters during the years 1994–2003. We find that M_TSU generally recovers the seismic moment M₀ within 0.2 logarithmic units, even under unfavorable conditions such as excessive focal depth and refraction of the tsunami wave around continental masses. Finally, we apply the algorithm to the JASON satellite trace obtained over the Bay of Bengal during the 2004 Sumatra tsunami, after transforming the trace into a time series through a simple ad hoc procedure. Results are surprisingly good, with most estimates of the moment being over 10²⁹ dyn-cm, and thus identifying the source as an exceptionally large earthquake.     

Temporal and spatial patterns of modern climatic warming: case study of Northern Eurasia

Century-scale near-surface air temperature data from 744 weather stations in Russia and neighboring countries indicate that the temperature variations have distinct temporal patterns. Two periods, near the beginning and at the end of the 20th century, experienced the largest warming rates. Temperature changes in both periods were not uniform in time or space. We used statistical criteria and applied them to data at the weather stations to define a “tipping point” corresponding to the beginning of the modern climatic period. Results indicate that the position of this point depends on location, and in most cases falls into the interval from the early 1970s through the late 1980s. By means of spatial correlation analysis we delineated regions with coherent air temperature changes and calculated the region-specific rates and magnitudes of changes. We compared the distribution of regional tipping points in time and over space with large-scale atmospheric circulation patterns over northern Eurasia. We analyzed the 20th—early 21st century changes in the relative frequencies of the three circulation forms defined by Vangengheim-Girs classification, and found their qualitative correspondence with the spatial temperature patterns and spread of the tipping points in time. These results improve our knowledge about the regional structure and drivers of modern climate change in northern Eurasia, which is likely to hold the fingerprint of the anthropogenic signal. Findings of this study can be used to obtain insight into regional climatic changes in northern Eurasia over the next few decades.