A compact form for the analytic description of temperature dependence of saturation vapor pressure over plane surfaces of water and ice

A possibility is studied of extending the range of action of the simple three-parameter formula (ITS-90 scale) proposed in the previous work of the author [2] for the dependence of saturation vapor pressure E on temperature T within the range of 250 to 490 K. The results demonstrated that the dependence ln[E(T)/E(T _bas)] = (T - T _bas)[A - B(T - T _bas) + C(T - T _bas)²]/T with four sets of coefficients A, B, and C obtained using one base temperature Tbas equal to the temperature of triple point of water T _t = 273.16 K and two additional base values T _bas2 = 473.16 K and T _bas3 = 623.16 K makes it possible to approximate rather accurately the initial experimental and computed data in the temperature range from the point of homogeneous freezing of 235 K to the critical temperature of 647 K for liquid water and from 193 K to T _t for ice. A procedure used for obtaining the inverse function T(E) by solving the third-degree algebraic equation is validated. A hypothesis is proposed for the physical substantiation of additional base points in the form of “a noticeable appearance of dimers at the point T _bas2 and their 100% concentration at the temperature T _bas3.”     

Drivers of the Severity of the Extreme Hot Summer of 2015 in Western China

Western China experienced an extreme hot summer in 2015, breaking a number of temperature records. The summer mean surface air temperature (SAT) anomaly was twice the interannual variability. The hottest daytime temperature (T_Xx) and warmest night-time temperature (T_Nx) were the highest in China since 1964. This extreme hot summer occurred in the context of steadily increasing temperatures in recent decades. We carried out a set of experiments to evaluate the extent to which the changes in sea surface temperature (SST)/sea ice extent (SIE) and anthropogenic forcing drove the severity of the extreme summer of 2015 in western China. Our results indicate that about 65%–72% of the observed changes in the seasonal mean SAT and the daily maximum (T_max) and daily minimum (T_min) temperatures over western China resulted from changes in boundary forcings, including the SST/SIE and anthropogenic forcing. For the relative role of individual forcing, the direct impact of changes in anthropogenic forcing explain about 42% of the SAT warming and 60% (40%) of the increase in T_Nx and Tmin (T_Xx and T_max) in the model response. The changes in SST/SIE contributed to the remaining surface warming and the increase in hot extremes, which are mainly the result of changes in the SST over the Pacific Ocean, where a super El Niño event occurred. Our study indicates a prominent role for the direct impact of anthropogenic forcing in the severity of the extreme hot summer in western China in 2015, although the changes in SST/SIE, as well as the internal variability of the atmosphere, also made a contribution.     

Multivariate drought frequency estimation using copula method in Southwest China

This study reveals the impacts of climatic variable trends on drought severity in Xinjiang, China. Four drought indices, including the self-calibrating Palmer drought severity index (sc-PDSI), Erinç’s index (I _m), Sahin’s index (I _sh), and UNEP aridity index (AI), were used to compare drought severity. The ensemble empirical mode decomposition and the modified Mann-Kendall trend test were applied to analyze the nonlinear components and trends of the climatic variable and drought indices. Four and six climatic scenarios were generated in sc-PDSI, I _m, I _sh, and AI with different combinations of the observed and detrended climatic variables, respectively. In Xinjiang, generally increasing trends in minimal, average, and maximal air temperature (T _min, T _ave, T _max) and precipitation (P) were found, whereas a decreasing trend in wind speed at 2 m height (U ₂) was observed. There were significantly increasing trends in all of the four studied drought indices. Drought relief was more obvious in northern Xinjiang than in southern Xinjiang. The strong influences of increased P on drought relief and the weak influences of increased T _min, T _ave, and T _max on drought aggravation were shown by comparing four drought indices under different climate scenarios. Decreased U ₂ had a weak influence on drought, as shown by the AI in different climate scenarios. The weak influences of T and U ₂ were considered to be masked by the strong influences of P on droughts. Droughts were expected to be more severe if P did not increase, but were likely milder without an increase in air temperature and with a decrease in U ₂.     

Relationship Between Fine-Particle Pollution and the Urban Heat Island in Beijing,China: Observational Evidence

Urbanization has led to a significant urban heat island (UHI) effect in Beijing in recent years. At the same time, air pollution caused by a large number of fine particles significantly influences the atmospheric environment, urban climate, and human health. The distribution of fine particulate matter (PM_2.5) concentration and its relationship with the UHI effect in the Beijing area are analyzed based on station-observed hourly data from 2012 to 2016. We conclude that, (1) in the last five years, the surface concentrations of PM_2.5 averaged for urban and rural sites in and around Beijing are 63.2 and 40.7 µg m^?3, respectively, with significant differences between urban and rural sites (ΔPM_2.5) at the seasonal, monthly and daily scales observed; (2) there is a large correlation between ΔPM_2.5 and the UHI intensity defined as the differences in the mean (ΔT_ave), minimum (ΔT_min), and maximum (ΔT_max) temperatures between urban and rural sites. The correlation between ΔPM_2.5 and ΔT_min (ΔT_max) is the highest (lowest); (3) a Granger causality analysis further shows that ΔPM_2.5 and ΔT_min are most correlated for a lag of 1–2 days, while the correlation between ΔPM_2.5 and ΔT_ave is lower; there is no causal relationship between ΔPM_2.5 and ΔT_max; (4) a case analysis shows that downwards shortwave radiation at the surface decreases with an increase in PM_2.5 concentration, leading to a weaker UHI intensity during the daytime. During the night, the outgoing longwave radiation from the surface decreases due to the presence of daytime pollutants, the net effect of which is a slower cooling rate during the night in cities than in the suburbs, leading to a larger ΔT_min.     

Effects of optimized root water uptake parameterization schemes on water and heat flux simulation in a maize agroecosystem

As root water uptake (RWU) is an important link in the water and heat exchange between plants and ambient air, improving its parameterization is key to enhancing the performance of land surface model simulations. Although different types of RWU functions have been adopted in land surface models, there is no evidence as to which scheme most applicable to maize farmland ecosystems. Based on the 2007–09 data collected at the farmland ecosystem field station in Jinzhou, the RWU function in the Common Land Model (CoLM) was optimized with scheme options in light of factors determining whether roots absorb water from a certain soil layer (W_x) and whether the baseline cumulative root efficiency required for maximum plant transpiration (W_c) is reached. The sensibility of the parameters of the optimization scheme was investigated, and then the effects of the optimized RWU function on water and heat flux simulation were evaluated. The results indicate that the model simulation was not sensitive to W_x but was significantly impacted by W_c. With the original model, soil humidity was somewhat underestimated for precipitation-free days; soil temperature was simulated with obvious interannual and seasonal differences and remarkable underestimations for the maize late-growth stage; and sensible and latent heat fluxes were overestimated and underestimated, respectively, for years with relatively less precipitation, and both were simulated with high accuracy for years with relatively more precipitation. The optimized RWU process resulted in a significant improvement of CoLM’s performance in simulating soil humidity, temperature, sensible heat, and latent heat, for dry years. In conclusion, the optimized RWU scheme available for the CoLM model is applicable to the simulation of water and heat flux for maize farmland ecosystems in arid areas.     

Formulation of stability-dependent empirical relations for turbulent intensities from surface layer turbulence measurements for dispersion parameterization in a lagrangian particle dispersion model

Season- and stability-dependent turbulence intensity (σ _u /u _*, σ _v /u _*, σ _w /u _*) relationships are derived from experimental turbulence measurements following surface layer scaling and local stability at the tropical coastal site Kalpakkam, India for atmospheric dispersion parameterization. Turbulence wind components (u′, v′, w′) measured with fast response UltraSonic Anemometers during an intense observation campaign for wind field modeling called Round Robin Exercise are used to formulate the flux–profile relationships using surface layer similarity theory and Fast Fourier Transform technique. The new relationships (modified Hanna scheme) are incorporated in a Lagrangian Particle Dispersion model FLEXPART-WRF and tested by conducting simulations for a field tracer dispersion experiment at Kalpakkam. Plume dispersion analysis of a ground level hypothetical release indicated that the new turbulent intensity formulations provide slightly higher diffusivity across the plume relative to the original Hanna scheme. The new formulations for σ _u , σ _v , σ _w are found to give better agreement with observed turbulent intensities during both stable and unstable conditions under various seasonal meteorological conditions. The simulated concentrations using the two methods are compared with those obtained from a classical Gaussian model and the observed SF₆ concentration. It has been found that the new relationships provide comparatively higher diffusion across the plume relative to the model default Hanna scheme and provide downwind concentration results in better agreement with observations.     

Comprehensive modeling of monthly mean soil temperature using multivariate adaptive regression splines and support vector machine

Soil temperature (T _s) and its thermal regime are the most important factors in plant growth, biological activities, and water movement in soil. Due to scarcity of the T _s data, estimation of soil temperature is an important issue in different fields of sciences. The main objective of the present study is to investigate the accuracy of multivariate adaptive regression splines (MARS) and support vector machine (SVM) methods for estimating the T _s. For this aim, the monthly mean data of the T _s (at depths of 5, 10, 50, and 100 cm) and meteorological parameters of 30 synoptic stations in Iran were utilized. To develop the MARS and SVM models, various combinations of minimum, maximum, and mean air temperatures (T _min, T _max, T); actual and maximum possible sunshine duration; sunshine duration ratio (n, N, n/N); actual, net, and extraterrestrial solar radiation data (R _s, R _n, R _a); precipitation (P); relative humidity (RH); wind speed at 2 m height (u ₂); and water vapor pressure (V_p) were used as input variables. Three error statistics including root-mean-square-error (RMSE), mean absolute error (MAE), and determination coefficient (R ²) were used to check the performance of MARS and SVM models. The results indicated that the MARS was superior to the SVM at different depths. In the test and validation phases, the most accurate estimations for the MARS were obtained at the depth of 10 cm for T _max, T _min, T inputs (RMSE = 0.71 °C, MAE = 0.54 °C, and R ² = 0.995) and for RH, V _p, P, and u ₂ inputs (RMSE = 0.80 °C, MAE = 0.61 °C, and R ² = 0.996), respectively.     

Characteristics of the precipitation recycling ratio and its relationship with regional precipitation in China

A dynamic recycling model (DRM) with an analytical moisture trajectory tracking method, together with Japan Meteorological Agency 25-year reanalysis data, is used to study the regional precipitation recycling process across China, by calculating the regional recycling ratio (ρ _r ) at the daily time scale during 1979–2010. The distribution of ρ _r shows that, in western China, especially the Tibetan Plateau and its surrounding areas, precipitation is strongly dependent on the recycling process associated with regional evaporation. In Southeast China, however, the contribution from the recycling processes is much smaller due to the influence of the summer monsoon. A precipitation threshold value of about 4 mm/day is obtained from detailed analysis of both extreme and all-range ρ _r years. According to this threshold, China is classified into three types of sub-regions: low-precipitation sub-regions (mainly in the northwest), high-precipitation sub-regions (mainly in the south), and medium-precipitation sub-regions (mainly in the northeast). It is found that ρ _r correlates positively with precipitation, as well as convective precipitation (P _CP) and large-scale precipitation (P _LP) in the low-precipitation sub-regions. However, negative ρ _r ?～?P _LP correlations are found in the high-precipitation sub-regions and nonsignificant correlations exist in the medium-precipitation sub-regions. As P _CP is mainly locally generated due to mid-latitude mesoscale systems and the cumulus parameterization used in producing the reanalysis, the recycling ratio positively correlates to the ratio P _CP/P _LP in almost all sub-regions, particularly in the Tibetan Plateau and its surrounding areas. The correlation between radiation flux and ρ _r suggests more net radiation supports more evaporation and higher ρ _r , especially in the high-precipitation sub-regions. The influence of clouds on shortwave radiation is crucial, since evaporation is suppressed when the amount of cloudiness increases, especially in the high-precipitation sub-regions. Together with the consideration of soil moisture, it can be inferred that limited soil moisture inhibits evaporation in the low-precipitation sub-regions, while the energy or radiation is the dominant factor controlling evaporation in the high-precipitation sub-regions.     

Field Experiments and Numerical Modeling of Wind Speed and Surface Waves in Medium-size Inland Reservoirs

An attempt is made to apply the modern methods of surface wave simulation developed for oceanic conditions to the modeling of waves in medium-size inland reservoirs (10–100 km). The results of field measurements of wind speed and waves are described, and on their basis the parameterization C _D (U ₁₀) is proposed. WAVEWATCH III spectral wave model was adapted to the conditions of a medium-size inl and reservoir. The simulated data are compared with the field data. The use of the new parameterization C _D (U ₁₀) allowed reducing the values of the wind wave growth rate that improved consistency in data from the field experiment and numerical modeling concerning the height of significant waves. Further steps towards improving the quality of prediction of the adapted WAVEWATCH III model are discussed.     

Simulation of leaf blast infection in tropical rice agro-ecology under climate change scenario

Assessing disease risk has become an important component in the development of climate change adaptation strategies. Here, the infection ability of leaf blast (Magnaporthe oryzae) was modeled based on the epidemiological parameters of minimum (T _min), optimum (T _opt), and maximum (T _max) temperatures for sporulation and lesion development. An infection ability response curve was used to assess the impact of rising temperature on the disease. The simulated spatial pattern of the infection ability index (IAI) corresponded with observed leaf blast occurrence in Indo-Gangetic plains (IGP). The IAI for leaf blast is projected to increase during the winter season (December–March) in 2020 (2010–2039) and 2050 (2040–2069) climate scenarios due to temperature rise, particularly in lower latitudes. However, during monsoon season (July–October), the IAI is projected to remain unchanged or even reduce across the IGP. The results show that the response curve may be successfully used to assess the impact of climate change on leaf blast in rice. The model could be further extended with a crop model to assess yield loss.     

Modeling monthly meteorological and agronomic frost days,based on minimum air temperature,in Center-Southern Brazil

Although Brazil is predominantly a tropical country, frosts are observed with relative high frequency in the Center-Southern states of the country, affecting mainly agriculture, forestry, and human activities. Therefore, information about the frost climatology is of high importance for planning of these activities. Based on that, the aims of the present study were to develop monthly meteorological (F _MET) and agronomic (F _AGR) frost day models, based on minimum shelter air temperature (T _MN), in order to characterize the temporal and spatial frost days variability in Center-Southern Brazil. Daily minimum air temperature data from 244 weather stations distributed across the study area were used, being 195 for developing the models and 49 for validating them. Multivariate regression models were obtained to estimate the monthly T _MN, once the frost day models were based on this variable. All T _MN regression models were statistically significant (p < 0.001), presenting adjusted R ² between 0.69 and 0.90. Center-Southern Brazil is mainly hit by frosts from mid-fall (April) to mid-spring (October). The period from November to March is considered as frost-free, being very rare a frost day within that period. Monthly F _MET and F _AGR presented significant sigmoidal relationships with T _MN (p < 0.0001), with adjusted R ² above of 0.82. The residuals of the frost day models were random, which means that the sigmoidal models performed quite well for interpreting the frost day variability throughout the study area. The highlands of Santa Catarina, Rio Grande do Sul, São Paulo, and Minas Gerais had in average more than 25 and 13 frosts per year, respectively, for F _MET and F _AGR. The F _MET and F _AGR maps developed in this study for Center-Southern Brazil is a useful tool for farmers, foresters, and researchers, since they contribute to reduce frost spatial and temporal uncertainty, helping in planning project for strategic purposes. Furthermore, the monthly F _MET and F _AGR maps for this Brazilian region are the first zoning of these variables for the country.     

Uncertainty of global summer precipitation in the CMIP5 models: a comparison between high-resolution and low-resolution models

Worldwide, the majority of rapidly growing neighborhoods are found in the Global South. They often exhibit different building construction and development patterns than the Global North, and urban climate research in many such neighborhoods has to date been sparse. This study presents local-scale observations of net radiation (Q _* ) and sensible heat flux (Q _H ) from a lightweight low-rise neighborhood in the desert climate of Andacollo, Chile, and compares observations with results from a process-based urban energy-balance model (TUF3D) and a local-scale empirical model (LUMPS) for a 14-day period in autumn 2009. This is a unique neighborhood-climate combination in the urban energy-balance literature, and results show good agreement between observations and models for Q _* and Q _H . The unmeasured latent heat flux (Q _E ) is modeled with an updated version of TUF3D and two versions of LUMPS (a forward and inverse application). Both LUMPS implementations predict slightly higher Q _E than TUF3D, which may indicate a bias in LUMPS parameters towards mid-latitude, non-desert climates. Overall, the energy balance is dominated by sensible and storage heat fluxes with mean daytime Bowen ratios of 2.57 (observed Q _H /LUMPS Q _E )–3.46 (TUF3D). Storage heat flux (ΔQ _S ) is modeled with TUF3D, the empirical objective hysteresis model (OHM), and the inverse LUMPS implementation. Agreement between models is generally good; the OHM-predicted diurnal cycle deviates somewhat relative to the other two models, likely because OHM coefficients are not specified for the roof and wall construction materials found in this neighborhood. New facet-scale and local-scale OHM coefficients are developed based on modeled ΔQ _S and observed Q _* . Coefficients in the empirical models OHM and LUMPS are derived from observations in primarily non-desert climates in European/North American neighborhoods and must be updated as measurements in lightweight low-rise (and other) neighborhoods in various climates become available.     

Improving Representation of Tropical Cloud Overlap in GCMs Based on Cloud-Resolving Model Data

The decorrelation length (L_cf) has been widely used to describe the behavior of vertical overlap of clouds in general circulation models (GCMs); however, it has been a challenge to associate L_cf with the large-scale meteorological conditions during cloud evolution. This study explored the relationship between L_cf and the strength of atmospheric convection in the tropics based on output from a global cloud-resolving model. L_cf tends to increase with vertical velocity in the mid-troposphere (w₅₀₀) at locations of ascent, but shows little or no dependency on w₅₀₀ at locations of descent. A representation of L_cf as a function of vertical velocity is obtained, with a linear regression in ascending regions and a constant value in descending regions. This simple and dynamic-related representation of L_cf leads to a significant improvement in simulation of both cloud cover and radiation fields compared with traditional overlap treatments. This work presents a physically justifiable approach to depicting cloud overlap in the tropics in GCMs.     

Correlation between temperature and salinity variations as a characteristic of the North Atlantic waters

Based on the data of deep-ocean ship observations of temperature T and salinity S, analysis is carried out of the fields of pair correlation coefficients between T and S at different depths as an additional characteristic of water masses in the layer 0–1000 m in the North Atlantic. As a result of analysis, surface, subsurface, and the upper part of North Atlantic intermediate waters are classified according to a degree of correlation between temperature and salinity. The emphasis was given to regions with low correlations, because they indicate the prevalence of the interaction processes that differ most from the typical mixing of two water masses with entirely different characteristics.     

High-stability algorithm for the three-pattern decomposition of global atmospheric circulation

The study investigates the reliable computation time (RCT, termed as T _c) by applying a double-precision computation of a variable parameters logistic map (VPLM). Firstly, by using the proposed method, we obtain the reliable solutions for the logistic map. Secondly, we construct 10,000 samples of reliable experiments from a time-dependent non-stationary parameters VPLM and then calculate the mean T _c. The results indicate that, for each different initial value, the T _cs of the VPLM are generally different. However, the mean T _c trends to a constant value when the sample number is large enough. The maximum, minimum, and probable distribution functions of T _c are also obtained, which can help us to identify the robustness of applying a nonlinear time series theory to forecasting by using the VPLM output. In addition, the T _c of the fixed parameter experiments of the logistic map is obtained, and the results suggest that this T _c matches the theoretical formula-predicted value.     

Cold air outbreaks along a non-frozen sea channel: effects of wind on snow bands

Wintertime cold air outbreaks along a non-frozen sea channel or a long lake can become destructive if the related bands of heavy snowfall hit onto land. The forcing for such bands is studied with a 2D numerical model set across an east–west sea channel at 60^oN (‘Gulf of Finland’), varying the basic geostrophic wind V _g. Without any V _g opposite coastal land breezes emerge with convergence. This results in a quasi-steady rising motion w _max ~ 7.5 cm/s at 600 m in the middle of the gulf, which can force a snow band. During weak V _g, the rising motion is reduced but least so for winds from 60^o to 80^o (~ENE), when modest alongshore bands could exist near the downstream (Estonian) coast. During V _g of 4–6 m/s from any direction, the land breezes and rising motions are reduced more effectively, so snow bands are not expected during moderate basic flow. In contrast, during a strong V _g of 20–25 m/s from 110^o to 120^o (~ESE) the land breeze perturbations are intense with w _max up to 15–18 cm/s. The induced alongshore bands of heavy snowfall are located in these cases at the sea but quite close to the downstream (Finnish) coast. They can suddenly make a landfall if the basic wind turns clockwise.     

Long-term variation of rainfall erosivity in Calabria (Southern Italy)

The changes in rainfall erosivity have been investigated using the rainfall erosivity factor (R) proposed for USLE by Wischmeier and Smith (R _W-S ) and some simplified indexes (the Fournier index modified by Arnoldus, F, a regional index spatial independent, R _Fr , and a regional index spatial dependent, R _Fs ) estimated by indirect approaches. The analysis has been carried out over 48 rainfall stations located in Calabria (Southern Italy) using data collected in the period 1936–2012 and divided in three sub-periods. The series of the erosivity indexes and of some precipitation variables have been analyzed for evidence of trends using standard methods. The simplified indexes suggested a general underestimation of the rainfall erosivity with respect to R _W-S . The mean underestimation ranged between 23 and 54 % for R _Fr and from 10 to 15 % for R _Fs . Both the sign and the magnitude of the trends were different for the different stations depending on the variable and sub-period considered. In general, the erosivity increased during the period 1936–1955 (1^st sub-period) and during the more recent sub-period (1992–2012, 3^rd sub-period), whereas it decreased during 1958–1977 (2^nd sub-period). The evidence of trends was generally higher for R _W-S than for R _Fr and R _Fs . Focusing on the most recent sub-period (3^rd sub-period), all the variables analyzed showed mainly increasing trends but with different magnitude. More particularly, R _W-S showed a mean increment of 29 %; F, R _Fr and R _Fs increased by 11, 15 and 18 %, respectively; the maximum intensity of 0.5-h precipitation increased by 5 %; and the annual precipitation increased by 22 %. Consequently, it remains difficult to define which precipitation variable plays the dominant role in the temporal variation of rainfall erosivity in the region. However, the overall results suggest that the indexes estimated by indirect procedures (F, R _Fr , and R _Fs ) should be used with caution for climate change analysis, despite they are used for practical purposes considering they are based on easily available information.     

Trend analysis of rainfall time series for Sindh river basin in India

The main goal of this paper is to estimate a set of optimal seasonal, daily, and hourly values of atmospheric turbidity and surface radiative parameters Ångström’s turbidity coefficient (β), Ångström’s wavelength exponent (α), aerosol single scattering albedo (ω_o), forward scatterance (F_c) and average surface albedo (ρ_g), using the Brute Force multidimensional minimization method to minimize the difference between measured and simulated solar irradiance components, expressed as cost functions. In order to simulate the components of short-wave solar irradiance (direct, diffuse and global) for clear sky conditions, incidents on a horizontal surface in the Metropolitan Area of Rio de Janeiro (MARJ), Brazil (22° 51′ 27″ S, 43° 13′ 58″ W), we use two parameterized broadband solar irradiance models, called CPCR2 and Iqbal C, based on synoptic information. The meteorological variables such as precipitable water (u_w) and ozone concentration (u_o) required by the broadband solar models were obtained from moderate-resolution imaging spectroradiometer (MODIS) sensor on Terra and Aqua NASA platforms. For the implementation and validation processes, we use global and diffuse solar irradiance data measured by the radiometric platform of LabMiM, located in the north area of the MARJ. The data were measured between the years 2010 and 2012 at 1-min intervals. The performance of solar irradiance models using optimal parameters was evaluated with several quantitative statistical indicators and a subset of measured solar irradiance data. Some daily results for Ångström’s wavelength exponent α were compared with Ångström’s parameter (440–870 nm) values obtained by aerosol robotic network (AERONET) for 11 days, showing an acceptable level of agreement. Results for Ångström’s turbidity coefficient β, associated with the amount of aerosols in the atmosphere, show a seasonal pattern according with increased precipitation during summer months (December–February) in the MARJ.     

Seasonal and interannual variability of oceanographic conditions in the southwestern part of the Sea of Okhotsk

The seasonal variability of oceanographic conditions in the southern part of the Sea of Okhotsk is described based on long-term mean temperature T and salinity S from observations along a standard oceanographic section Cape Aniva-Cape Dokuchaev (May–November). It is shown that the Soya Current is relatively weak in spring, with low temperature and salinity gradients along the section. The Sea of Okhotsk low-salinity water mass is observed in the upper layer. It was formed as a result of melting of a large amount of ice brought here with the East Sakhalin Current from the northwestern part of the Sea of Okhotsk. A cold intermediate layer (CIL) at depths of 50–150 m extends along the entire section. The cold intermediate layer core with a temperature at the edge of the Sakhalin shelf of about ?1.3°C is retained during a period of maximum warming in August; however, in October–November the intensified flow of the East Sakhalin Current (up to 50 cm/s) results in a situation when relatively warm low-salinity waters, connected with the Amur River runoff, dissipate CIL. The results of 12 surveys conducted by the Sakhalin Research Institute for Fisheries and Oceanography in 1998–2004 show significant deviations of T and S [10] in different years from the calculated values. Generally, maximum anomalies (ΔT > 4°C and ΔS > 0.55‰) are observed in the surface layer. Their values and statistical significance decrease with depth. However, the situation is opposite in some cases. The maximum deviation from normal was observed in June 1999, when warm and salt waters were located much further seaward from the Kunashir shelf, which is most likely connected with the Soya Current meandering.     

Effects of climate change and agronomic practice on changes in wheat phenology

Phenological changes in crops affect efficient agricultural production and can be used as important biological indicators of local and regional climate change. Although crop phenological changes and their responses to climate change, especially temperature, have been investigated, the impact of agronomic practice such as cultivar shifts and planted date changes on crop phenology remains unclear. Here, we used a long-term dataset (1981–2010) of wheat phenology and associated local weather data from 48 agro-meteorological stations in four temperature zones in China to analyze phenological changes of spring and winter wheat. Trend analysis method was used to estimate changes in the date of growth stages and the duration of growth phases, while sensitivity analysis method was used to qualify the response of growth phase duration to mean temperature (T_mean), total precipitation (PRE), and total sunshine duration (SSD). Using the Crop Environment Resource Synthesis-wheat model, we isolated the impacts of climate change, cultivar selection, and sowing date on phenological change of wheat. Results show that phenological changes were greatest in the warm-temperate zone. Sensitivity analysis indicates that growth phase duration was generally negatively related to T_mean and positively related to PRE and SSD. The positive sensitivity response to T_mean occurred in the tillering to jointing and sowing to maturity growth periods in the warmer temperature zones, suggesting that warmer temperatures during the overwintering period hampered effective vernalization in winter wheat. Modeling results further indicate that reductions in wheat growth duration caused by climate change could be offset by the introduction of new cultivars with high thermal requirements and accelerated with delayed sowing date.