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Primary production in the Sea of Okhotsk is largely supported by dissolved iron (dFe) transported by the Amur river, indicating the importance of dFe discharge from terrestrial environments. However, little is known about the mechanisms of dFe discharge into the Amur river, especially in terms of long-term change in dFe concentration. In the Amur river, extreme increase in dFe concentration was observed between 1995 and 1997, the cause of which remains unclear. As a cause of this iron anomaly, we considered the impact of permafrost degradation. To link the permafrost degradation to long-term variation in dFe concentration, we examined the changes in annual air temperature (Ta), accumulated temperature (AT), and net precipitation for three regions (northeast, south, and northwest) of the basin between 1960 and 2006. Ta and AT were relatively high in one out of every few years, and were especially high during 1988–1990 continuously. Net precipitation in late summer (July to September) has increased since 1977 and has stayed positive until 2006 throughout the basin. Most importantly, we found significant correlations between Ta and late summer dFe concentration with a 7-year lag (r = 0.54–0.69, p < 0.01), which indicate a close relationship between high Ta in year Y and increased late summer dFe concentration in year Y + 7. This correlation was the strongest in northeastern Amur basin where permafrost coverage is the highest. Similar 7-year lag correlation was also found between AT in the northeastern basin and late summer dFe concentration (r = 0.51, p < 0.01). Based on our findings, we propose the following hypothesis as a cause of iron anomaly. (1) Increased net precipitation since 1977 has increased soil moisture, which created suitable conditions for microbial dFe generation; (2) permafrost degradation during the warm years of 1988–1990 promoted iron bioavailability and led to the intensive dFe generation in the deeper part of the active layer; and (3) dFe took approximately 7 years to reach the rivers and extremely increased dFe concentration during 1995–1997. This is the first study to suggest the time-lagged impact of permafrost degradation on iron biogeochemistry in the Amur river basin. [ABSTRACT FROM AUTHOR]

Snow is the most important component of the Arctic climatic and hydrological system and is directly vulnerable to climate change. In recent decades, observations have indicated significant decreases in the Arctic snow cover and snowfall rate, whereas water discharge from circumpolar Arctic river basins into the Arctic Ocean has increased. To evaluate the contribution, not well quantified, of snow to the river discharge increase, we conducted sensitivity simulations with surface air temperature and precipitation as climatic treatment variables, combining a land surface model and a distributed discharge model. Variables were treated assuming higher climate variations in the Arctic cold season in 1979–2018. The surface and subsurface runoffs simulated by the land surface model were set as inflows in the discharge model to estimate river discharge. Snowmelt mostly converted to surface runoff, accounting for 73.6% of the anomalous surface runoff increase and inducing the simulated peak discharge in spring and early summer. This relationship was enhanced by the winter precipitation increase. Snow loss induced by higher air temperature contributed to the decrease in the peak and annual discharges, but caused the peak discharge to occur earlier. Additionally, warmer temperature increased the proportion of rainfall in the partitioning of precipitation, causing more subsurface runoff, particularly in autumn and winter. These results provide a first separate evaluation of factors influencing Arctic water discharge, including seasonal hydrographs, and illustrate the influence of climate warming-induced snowfall and rainfall variations on the circumpolar Arctic river discharge. [ABSTRACT FROM AUTHOR]

As a result of climate change, the pan-Arctic region has seen greater temperature increases than other geographical regions on the Earth's surface. This has led to substantial changes in terrestrial ecosystems and the hydrological cycle, which have affected the distribution of vegetation and the patterns of water flow and accumulation. Various remote sensing techniques, including optical and microwave satellite observations, are useful for monitoring these terrestrial water and vegetation dynamics. In the present study, satellite and reanalysis datasets were used to produce water and vegetation maps with a high temporal resolution (daily) and moderate spatial resolution (500 m) at a continental scale over Siberia in the period 2003–2017. The multiple data sources were integrated by pixel-based machine learning (random forest), which generated a normalized difference water index (NDWI), normalized difference vegetation index (NDVI), and water fraction without any gaps, even for areas where optical data were missing (e.g., cloud cover). For the convenience of users handling the data, an aggregated product is provided, formatted using a 0.1° grid in latitude/longitude projection. When validated using the original optical images, the NDWI and NDVI images showed small systematic biases, with a root mean squared error of approximately 0.1 over the study area. The product was used for both time-series trend analysis of the indices from 2003 to 2017 and phenological feature extraction based on seasonal NDVI patterns. The former analysis was used to identify areas where the NDVI is decreasing and the NDWI is increasing, and hotspots where the NDWI at lakesides and coastal regions is decreasing. The latter analysis, which employed double-sigmoid fitting to assess changes in five phenological parameters (i.e., start and end of spring and fall, and peak NDVI values) at two larch forest sites, highlighted a tendency for recent lengthening of the growing period. Further applications, including model integration and contribution to land cover mapping, will be developed in the future. [ABSTRACT FROM AUTHOR]

Rapid Arctic warming has altered the regional hydrological cycle through reduction in Arctic sea ice. Observational and modeling efforts provided evidence that the enhanced evaporation from the Arctic Ocean could increase snowfall over high latitude terrestrial zones. However, questions remain regarding the amount of equatorward moisture transport and its change over the decadal timescale. Here we show that the transport of atmospheric moisture to Siberia that originated from Arctic Ocean evaporation has increased significantly in autumn to early winter during 1981–2019 when substantial sea ice retreat was observed. The enhanced Arctic moisture content is found in western Siberia in September, consistent with the observed increase in snow cover investigated in earlier studies. Meanwhile, the annual maximum daily amount of Arctic moisture shows a sharp increase in eastern Siberia during October–December associated with cyclonic activities along coastal regions. Our results suggest the importance of monitoring equatorward moisture transport during snow accumulation seasons because it could enhance local snowstorms as evaporation from the Arctic Ocean increases in the near future. [ABSTRACT FROM AUTHOR]

We present the power spectra of wind velocity and the cospectra of momentum and heat fluxes observed for different wind directions over flat terrain and a large valley on the Loess Plateau. The power spectra of longitudinal ( u) and lateral ( v) wind speeds satisfy the −5/3 power law in the inertial subrange, but do not vary as observed in previous studies within the low frequency range. The u spectrum measured at 32 m height for flow from the valley shows a power deficit at intermediate frequencies, while the v spectrum at 32 m downwind of the valley reaches another peak in the low frequency range at the same frequency as the u spectrum. The corresponding peak wavelength is consistent with the observed length scale of the convective outer layer at the site. The v spectrum for flat terrain shows a spectral gap at mid frequencies while obeying inner layer scaling in its inertial subrange, suggesting two sources of turbulence in the surface layer. All the spectra and cospectra from the valley direction show a height dependency over the three levels. [ABSTRACT FROM AUTHOR]

Assessing the quality of groundwater is important to ensure sustainable safe use of these resources. However, describing the overall water quality condition is difficult due to the spatial variability of multiple contaminants and the wide range of indicators (chemical, physical and biological) that could be measured. This contribution proposes a GIS-based groundwater quality index (GQI) which synthesizes different available water quality data (e.g., Cl-, Na+, Ca2+) by indexing them numerically relative to the World Health Organization (WHO) standards. Also, introduces an objective procedure to select the optimum parameters to compute the GQI, incorporates the aspect of temporal variation to address the degree of water use sustainability and tests the sensitivity of the proposed model. The GQI indicated that the groundwater quality in the Nasuno basin, Tochigi Prefecture, Japan, is generally high (GQI >90). It has also displayed the natural (depth to groundwater table, geomorphologic structures) and/or anthropogenic (land-use and population density) controls over the spatial variability of groundwater quality in the basin. Temporally, groundwater quality is more variable in the upper and lower parts of the basin (variation, V, 15-30%) compared to the middle part (V,<15%) probably attributed to the seasonality of precipitation and irrigation of rice. In the lower southeastern part of the Nasuno basin and the vicinity of the Naka and Houki rivers the sustainable use of groundwater is constrained by the relatively low and variable groundwater quality. The model sensitivity analysis indicated that parameters which reflect relatively lower water quality (high mean rank value) and those of significant spatial variability imply larger impacts on the GQI and must be carefully and accurately mapped. Optimum index factor technique allows the selection of the best combination of parameters dictating the variability of groundwater quality and enables an objective and fair representation of the overall groundwater quality. [ABSTRACT FROM AUTHOR]

Spectral analysis was performed on aircraft observations of a convective boundary layer (CBL) that developed over a thermally inhomogeneous, well-marked mesoscale land surface. The observations, part of the GAME-Siberia experiment, were recorded between April and June 2000 over the Lena River near Yakutsk City. A special integral parameter termed the ‘reduced depth of the CBL’ was used to scale the height of the mixed layer with variable depth. Analysis of wavelet cospectra and spectra facilitated the separation of fluxes and other variables into small-scale turbulent fluctuations (with scales less than the reduced depth of the CBL, approximately 2 km) and mesoscale fluctuations (up to 20 km). This separation approach allows for independent exploration of the scales. Analyses showed that vertical distributions obeyed different laws for small-scale fluxes and mesoscale fluxes (of sensible heat, water vapour, momentum and carbon dioxide) and for other variables (wind speed and air temperature fluctuations, coherence and degree of anisotropy). Vertical profiles of small-scale turbulent fluxes showed a strong decay that differed from generally accepted similarity models for the CBL. Vertical profiles of mesoscale fluxes and other variables clearly showed sharp inflections at the same relative (with respect to the reduced depth of the CBL) height of approximately 0.55 in the CBL. Conventional similarity models for sensible heat fluxes describe both small-scale turbulent and mesoscale flows. The present results suggest that mesoscale motions that reach up to the relative level of 0.55 could be initiated by thermal surface heterogeneity. Entrainment between the upper part of the CBL and the free atmosphere may cause mesoscale motions in that region of the CBL. [ABSTRACT FROM AUTHOR]

This study investigates the convective boundary layer (CBL) that develops over a non-homogeneous surface under different thermal and dynamic conditions. Analyses are based on data obtained from a Russian research aircraft equipped with turbulent sensors during the GAME-Siberia experiment over Yakutsk in Siberia, from April to June 2000. Mesoscale thermal internal boundary layers (MTIBLs) that radically modified CBL development were observed under unstable atmospheric conditions. It was found that MTIBLs strongly influenced the vertical and horizontal structures of virtual potential temperature, specific humidity and, most notably, the vertical sensible and latent heat fluxes. MTIBLs in the vicinity of the Lena River lowlands were confirmed by cloud distributions in satellite pictures. MTIBLs spread through the entire CBL and radically modify its structure if the CBL is unstable, and strong thermal features on the underlying surface have horizontal scales exceeding 10 km. MTIBL detection is facilitated through the use of special parameters linking shear stress and convective motion. The turbulent structure of the CBL with and without MTIBLs was scaled using the mosaic or flux aggregate approach. A non-dimensional parameter LRau/Lhetero (where LRau is Raupach's length and Lhetero is the horizontal scale of the surface heterogeneity) estimates the application limit of similarity and local similarity scaling models for the mosaic parts over the surface. Normalized vertical profiles of wind speed, air temperature, turbulent sensible and latent heat fluxes for the mosaic parts with LRauLhetero < 1 could be estimated by typical scaling curves for the homogeneous CBL. Traditional similarity scaling models for the CBL could not be applied for the mosaic parts with LRau/L hetero > 1. For some horizontally non-homogeneous CBLs, horizontal sensible heat fluxes were comparable with the vertical fluxes. The largest horizontal sensible heat fluxes occurred at the top of the surface layer and below the top of the CBL. [ABSTRACT FROM AUTHOR]