Oxygen and Carbon Isotope Study of Calcite and Dolomite in the Disseminated Au-Ag Telluride Bulawan Deposit, Negros Island, Philippines

Abstract: The disseminated Au‐Ag telluride Bulawan deposit, Negros island, Philippines, is hosted by dacite porphyry breccia pipes which formed in a Middle Miocene dacite porphyry stock. Electrum and Au‐Ag tellurides occur mostly as grains intergrown with or filling voids between sphalerite, pyrite, chalcopyrite, galena and tennantite. Calcite, quartz and rare dolomite are the principal gangue minerals. Four types of alteration were recognized in the deposit, namely; propylitic, K‐feldspar‐sericitic, sericitic and carbonate alteration. Carbonate alteration is correlatable to the gold deposition stage and occurs mostly along fault zones. The δ¹⁸O and δ¹³C compositions of calcite and dolomite in propylite zone and ore‐stage dacite porphyry breccia were determined. The δ¹⁸O values of calcite in propylitized andesite range from +12.2 to +14.7%, and their δ¹³C values range from ‐6.1 to ‐1.0%. The δ¹⁸O values of calcite and dolomite in sericite‐ and carbonate‐altered, mineralized dacite porphyry breccia and dacite porphyry rocks range from +15.1 to +23.1%, and the δ¹³C values of calcite and dolomite range from ‐3.9 to +0.9%. The δ¹⁸O and δ¹³C values of the hydrothermal fluids were estimated from inferred temperatures of formation on the basis of fluid inclusion microthermometry. The δ¹⁸O values of hydrothermal fluid for the propylitic alteration were calculated to be +8.5 ‐ +9.5%, assuming 375°C. On the other hand, the δ¹⁸O values of ore solutions for base metal and Au mineralization were computed to be +13.6 ‐ +14.6%, assuming 270°C. The hydrothermal fluids that formed the Bulawan deposit are dilute and ¹⁸O‐enriched fluids which reacted with ¹⁸O‐ and ¹³C‐rich wallrocks such as limestone.     

Late Pleistocene and Holocene vegetation and climate records from Lake Kotokel, central Baikal region

Climatically driven Late Pleistocene and Holocene vegetation changes were reconstructed based on pollen records from the sediments of Lake Kotokel and Cheremushka Bog, located on the eastern shore of Lake Baikal. The described paleoenvironmental record has higher resolution than records collected from Lake Baikal and unites individual events identified in prior studies of bottom and onshore cores. Remarkable shifts in landscapes and expansions of index plants are as follows. Forest tundra and/or forest steppe landscape with birch, spruce, Artemisia, and Poaceae prevailed at ca. 50–25 ¹⁴C kyr BP. Tundra and/or steppe vegetation dominated by Artemisia and Poaceae was typical for the Last Glacial Maximum. The expansion of shrub birch and willow occurred at ca. 15.5 ¹⁴C kyr BP. Two peaks of spruce expansion at ca. 47.5–42.4 ¹⁴C kyr BP (Karginian time) and at ca. 14.5–13 ka (Bølling-Allerød warm intervals) suggest that the condition were more humid than today. A slight increase in Artemisia at ca. 11–10.5 ¹⁴C kyr BP (13–12 ka) was indicative of the Younger Dryas event. An expansion of birch forests with fir at ca. 12–6.4 ka suggests higher humidity. The currently dominant Scots and Siberian pine forests with birch expanded since 6.4 ka.     

Subsurface Water Masses in the Central North Pacific Transition Region: The Repeat Section along the 18° Meridian

A repeat hydrographic section has been maintained over two decades along the 180° meridian across the subarctic-subtropical transition region. The section is naturally divided into at least three distinct zones. In the Subarctic Zone north of 46°N, the permanent halocline dominates the density stratification, supporting a subsurface temperature minimum (STM). The Subarctic Frontal Zone (SFZ) between 42°–46°N is the region where the subarctic halocline outcrops. To the south is the Subtropical Zone, where the permanent thermocline dominates the density stratification, containing a pycnostad of North Pacific Central Mode Water (CMW). The STM water colder than 4°C in the Subarctic Zone is originated in the winter mixed layer of the Bering Sea. The temporal variation of its core temperature lags 12–16 months behind the variations of both the winter sea surface temperature (SST) and the summer STM temperature in the Bering Sea, suggesting that the thermal anomalies imposed on the STM water by wintertime air-sea interaction in the Bering Sea spread over the western subarctic gyre, reaching the 180° meridian within a year or so. The CMW in this section originates in the winter mixed layer near the northern edge of the Subtropical Zone between 160°E and 180°. The CMW properties changed abruptly from 1988 to 1989; its temperature and salinity increased and its potential density decreased. It is argued that these changes were caused by the climate regime shift in 1988/1989 characterized by weakening of the Aleutian Low and the westerlies and increase in the SST in the subarctic-subtropical transition region. This revised version was published online in August 2006 with corrections to the Cover Date.     

Long-term precipitation and stream discharge records at seven forested experimental watersheds along a latitudinal transect in Japan: Jozankei,Kamabuchi, Takaragawa,Tsukuba, Tatsunokuchi-yama,Kahoku and Sarukawa

This data note introduces a database of long-term daily total precipitation and stream discharge data for seven forested watersheds in Japan that have been continuously monitored by the Forestry and Forest Products Research Institute. Three of the watersheds started data collection in the 1930s. Forest cover across the sites ranges from cool to warm temperate regions with the latitude spanning from 31 to 44° N and annual precipitation ranging from 1200 to 3000 mm yr⁻¹. The effects of vegetation change via clearcutting, thinning and forest fire (among other stressors) on stream discharge can be analysed from the long-term observation sites. Moreover, this multi-site dataset allows for inter- and intra-site comparisons of annual water loss (difference of annual precipitation and stream discharge). These long-term datasets can provide comprehensive insights into the effects of climate change and other stressors on forested ecosystems, not only in Japan but across a spectrum of forest types, if combined with other long-term records from other forested watersheds across the world.     

Impacts of Indian Ocean SST biases on the Indian Monsoon: as simulated in a global coupled model

In this study, the impact of the ocean–atmosphere coupling on the atmospheric mean state over the Indian Ocean and the Indian Summer Monsoon (ISM) is examined in the framework of the SINTEX-F2 coupled model through forced and coupled control simulations and several sensitivity coupled experiments. During boreal winter and spring, most of the Indian Ocean biases are common in forced and coupled simulations, suggesting that the errors originate from the atmospheric model, especially a dry islands bias in the Maritime Continent. During boreal summer, the air-sea coupling decreases the ISM rainfall over South India and the monsoon strength to realistic amplitude, but at the expense of important degradations of the rainfall and Sea Surface Temperature (SST) mean states in the Indian Ocean. Strong SST biases of opposite sign are observed over the western (WIO) and eastern (EIO) tropical Indian Ocean. Rainfall amounts over the ocean (land) are systematically higher (lower) in the northern hemisphere and the south equatorial Indian Ocean rainfall band is missing in the control coupled simulation. During boreal fall, positive dipole-like errors emerge in the mean state of the coupled model, with warm and wet (cold and dry) biases in the WIO (EIO), suggesting again a significant impact of the SST errors. The exact contributions and the distinct roles of these SST errors in the seasonal mean atmospheric state of the coupled model have been further assessed with two sensitivity coupled experiments, in which the SST biases are replaced by observed climatology either in the WIO (warm bias) or EIO (cold bias). The correction of the WIO warm bias leads to a global decrease of rainfall in the monsoon region, which confirms that the WIO is an important source of moisture for the ISM. On the other hand, the correction of the EIO cold bias leads to a global improvement of precipitation and circulation mean state during summer and fall. Nevertheless, all these improvements due to SST corrections seem drastically limited by the atmosphere intrinsic biases, including prominently the unimodal oceanic position of the ITCZ (Inter Tropical Convergence Zone) during summer and the enhanced westward wind stress along the equator during fall.     

Current status of ENSO prediction skill in coupled ocean–atmosphere models

The overall skill of ENSO prediction in retrospective forecasts made with ten different coupled GCMs is investigated. The coupled GCM datasets of the APCC/CliPAS and DEMETER projects are used for four seasons in the common 22 years from 1980 to 2001. As a baseline, a dynamic-statistical SST forecast and persistence are compared. Our study focuses on the tropical Pacific SST, especially by analyzing the NINO34 index. In coupled models, the accuracy of the simulated variability is related to the accuracy of the simulated mean state. Almost all models have problems in simulating the mean and mean annual cycle of SST, in spite of the positive influence of realistic initial conditions. As a result, the simulation of the interannual SST variability is also far from perfect in most coupled models. With increasing lead time, this discrepancy gets worse. As one measure of forecast skill, the tier-1 multi-model ensemble (MME) forecasts of NINO3.4 SST have an anomaly correlation coefficient of 0.86 at the month 6. This is higher than that of any individual model as well as both forecasts based on persistence and those made with the dynamic-statistical model. The forecast skill of individual models and the MME depends strongly on season, ENSO phase, and ENSO intensity. A stronger El Niño is better predicted. The growth phases of both the warm and cold events are better predicted than the corresponding decaying phases. ENSO-neutral periods are far worse predicted than warm or cold events. The skill of forecasts that start in February or May drops faster than that of forecasts that start in August or November. This behavior, often termed the spring predictability barrier, is in part because predictions starting from February or May contain more events in the decaying phase of ENSO.     

Annual ENSO simulated in a coupled ocean–atmosphere model

Using an output from 200-year integration of the Scale Interaction Experiment of EU project-F1 model (SINTEX-F1), the annual ENSO reproduced in the coupled general circulation model is investigated, suggesting the importance of reproducing an annual cycle in realistically simulating ENSO events. Although many features of the annual ENSO are reproduced, the northward expansion of sea surface temperature anomaly (SSTA) in the eastern tropical Pacific stays south of the equator. It is suggested that this model bias is due to the excitation of the too strong Rossby waves in the southeastern tropical Pacific, which reflect at the western boundary and intrude into the eastern equatorial Pacific. The zonal wind stress anomaly along the equator also plays an important role in generating the equatorial Kelvin waves. The amplitude of SSTA for the annual ENSO mode is reproduced, but its variance is only 20% of the observation; this is again due to the lack of northward migration of seasonal SSTA in the equatorial region and weaker coastal Kelvin waves along South America. Remedies for the model bias are discussed.     

IOD and ENSO impacts on the extreme stream-flows of Citarum river in Indonesia

Extreme stream-flow events of Citarum River are derived from the daily stream-flows at the Nanjung gauge station. Those events are identified based on their persistently extreme flows for 6 or more days during boreal fall when the seasonal mean stream-flow starts peaking-up from the lowest seasonal flows of June–August. Most of the extreme events of high-streamflows were related to La Ni?a conditions of tropical Pacific. A few of them were also associated with the negative phases of IOD and the newly identified El Ni?o Modoki. Unlike the cases of extreme high streamflows, extreme low streamflow events are seen to be associated with the positive IODs. Nevertheless, it was also found that the low-stream-flow events related to positive IOD events were also associated with El Ni?o events except for one independent event of 1977. Because the occurrence season coincides the peak season of IOD, not only the picked extreme events are seen to fall under the IOD seasons but also there exists a statistically significant correlation of 0.51 between the seasonal IOD index and the seasonal streamflows. There also exists a significant lag correlation when IOD of June–August season leads the streamflows of September–November. A significant but lower correlation coefficient (0.39) is also found between the seasonal streamflow and El Ni?o for September–November season only.