Global climate change is expected to alter seasonal patterns and rates of evapotranspiration in dry regions. Although climate change will involve elevated CO 2 and increased temperatures, independently, these factors may have different impacts on actual evapotranspiration (AET) due to their opposing effects on transpiration. We used canopy gas exchange chambers to quantify AET in a semiarid grassland experimentally altered by elevated CO 2 and warming over 3 years with contrasting ambient precipitation. Seasonal and interannual variations in AET due to background climate variability were larger than the effects of climate manipulation treatments. However, in a year with average precipitation, cumulative growing season AET was suppressed by warming by 23%. Across years, warming increased AET early in the growing season and suppressed it later in the growing season. By contrast, elevated CO 2 suppressed AET early in the growing season and enhanced it later, but only in years with average or above-average precipitation. Vegetation greenness (a proxy for photosynthetically active leaf area) was consistently the strongest predictor of AET, whereas soil moisture and vapor pressure deficit were secondary drivers. Our research demonstrates that effects of increased atmospheric CO 2 and temperature on AET will be mediated by plant phenological development and seasonal climatic conditions.
Analysis of the long-period changes of the surface thermal characteristics in the Japan Sea, including the ice cover of Peter the Great Bay, was carried on the basis of the regional databases formed from open sources. The relationship of the observed changes with large-scale processes characterized by well-known climatic indices was investigated. It was revealed that surface temperature changes in the Japan Sea, its Northern part and in Peter the Great Bay in winter and summer occur synchronously. In the new century (2001–2017), the growth rate of the sea surface temperature slowed down in comparison with the last 25 years of the 20th century. The most influential in these areas were the large-scale processes, which are characterized by the index of the Siberian anticyclone and the West Pacific index. We also analyzed the sustainability of the statistical relationships between regional thermal characteristics and large-scale climate indices. Special attention was paid to the change in the character of the relationships at different time periods. The pronounced rearrangements of the linkages accompanied by a change in the sign of the correlation coefficients corresponded to the well known climatic regime shifts in most of the cases under study. The most notable restructuring occurred in 1988/89.
Previously published results of the study [Khen et al., 2019b] are continued. Long-term changes of the sea surface temperature (SST) in the Far-Eastern Seas and North-West Pacific (NWP) are described for 1950–2019 and their relationship with large-scale climate processes described by climatic indices (AO, Nino 3.4, PDO, ALPI, NPI, PNA, SHI, and WP) is analyzed. SST has increased in all seasons, with higher rate in winter and autumn and less significant trend in summer. A prominent shift to warmer regime occurred in the Bering Sea in 1977 that coincided with a sharp change in dynamics of PDO, ALPI, NPI, and PNA indices. Such shifts were observed in the Okhotsk Sea in 1981 and in the Japan Sea in 1990, one year after the shifts in the time-series of AO, PDO, and PNA indices. Smaller shifts to warming happened in NWP in 2008 and 2018. Pacific Decadal Oscillation is the main contributor to temperature variability in the Bering Sea in all seasons, though the contribution of ALPI and PNA variation is considerable in winter and spring. Arctic Oscillation is the most important for the Okhotsk Sea. Variations of AO, SHI and WP are significant for the SST variability in the Japan Sea. Any single climatic index does not determine the SST variability in NWP, in all seasons. The set of climatic indices can be divided into two categories: western and eastern ones, according to their contribution to SST variability in certain regions. The western group includes AO, SHI, and WP, which contribute mostly to the variations in the western regions, westward from the longitude of Kamchatka. The most important indices in the eastern group are PDO, PNA and ALPI.
The study is continuing, which first results were published in 2019 [Khen et al., 2019]. The main patterns of long-term variability are considered for selected climate indices in the North Pacific and links between them are identified on the common methodological basis. The following indices are analyzed: AO (Arctic Oscillation), PDO (Pacific Decadal Oscillation), Nino 3.4 (index of El-Nino — South Oscillation), ALPI (Aleutian Low Pressure index), NPI (North Pacific index), PNA (Pacific/North American index), SHI (Siberian High index), and WP (West Pacific index). Their time-series are provided on websites of the world climate centers, with exception of the Siberian High index that was calculated from the reanalysis data on the sea level pressure provided by the USA National Center for Environmental Prediction (NCEP) — National Center for Atmospheric Research (NCAR) for 1950–2018. Data were analysed using standard statistical methods. Regime shifts are detected using Rodionov’s method of sequential regime shift detection including the regime shift index (RSI) and tools of automatic detection of the regime shifts with improved performance at the ends of time series. Variations of all indices since the middle 20th century correspond to warming that is not monotonous but combines phases of quick transition from one climatic regime to another — climate shifts and periods of relatively stable state between them. The most important climate shifts happened in 1977 and 1989 and they were noted for majority of the considered indices. Values of the indices heightened in the former shift and slightly lowered in the latter one, except of NPI that had opposite changes. PDO, WP and NPI had another positive shift in the recent years (2015–2017) that allows to assume transition to a new climate regime which will be warmer than the previous one in the last two decades. Long-term periodicity coincided with the 19-year cycle of lunar declination is revealed for PDO, ALPI, NPI and PNA; its spectral power amplifies considerably after removing of high-frequency variability by running 5-year averaging of the time series. Nino 3.4 showed a prominent 11-year cycle, possibly associated with the solar activity. SHI, AO and WP changed with periods about two decades: the main frequency is 26 years for SHI, 20 years for AO, and 17 years for WP, but the peaks of spectral power for the two latter indices is low, i.e. non-periodic oscillations dominate for them. Secondary peaks of spectral power are much lower than the main ones, they correspond to cycles of 7–8 years for AO and PDO, 11 years for WP, and 15 years for SHI. The indices of the North Pacific quartette (PDO, ALPI, NPI and PNA) are closely related between each other with high correlation coefficients (0.67–0.96). The Nino 3.4 index is also linked with them, but with lower correlation (0.45–0.56). SHI has statistically significant relationship with AO only, and WP correlates with Nino 3.4. Contribution of the large-scale climate processes to environmental variability in the Far-Eastern Seas of Russia and the Northwestern Pacific will be considered in the next issue.
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