Transition Dates Research Articles

Submission to Senate Finance Committee - Taxation of Accumulated Deferred Foreign Income

International tax reform proposals all suggest some transition from the present deferral system to some other system. As an integral part of that transition, it is expected as well that there will be some taxation on all “accumulated deferred foreign income” existing as of the transition date. This submission suggests two administratively workable mechanisms by which a favorable lower-then-35% tax rate can be appropriately applied to accumulated deferred foreign income that was earned through real business activities conducted outside the U.S., consistent with the Congressional intent of the current deferral tax system. On the other hand, any such accumulated deferred foreign income that has resulted from profit shifting activities should be taxed at the full 35%, including an interest charge.

Estimation of plant area index and phenological transition dates from digital repeat photography and radiometric approaches in a hardwood forest in the Northeastern United States

Long-term, continuous digital camera imagery and tower-based radiometric monitoring were conducted at a representative hardwood forest site in the Northeastern United States, part of the AmeriFlux network. In this study, the phenological metrics of the leaf area index (LAI), plant area index (PAI) and associated transition dates (e.g., timing of the onset of leaf expansion and the cessation of leaf fall) were compared using 4-year of data from Bartlett Experimental Forest. We used digital repeat photography (DRP) imagery collected using two different methods (“canopy cover” and “phenocam” approaches), together with above- and below-canopy measurements of photosynthetically active radiation (PAR). The growth-period LAI estimated from canopy cover images (LAICANOPY) and the above and below canopy PAR measurements (LAIfPARt) were within approximately the same range, in term of magnitude, as previous results for multiple comparative methods, although growing-season LAICANOPY was slightly lower (3.11m2m−2 to 3.35m2m−2) than LAIfPARt (3.19m2m−2 to 3.67m2m−2). In addition, we derived phenological transition dates from PAICANOPY, PAIfPARt, and color-based metrics calculated from the phenocam imagery (green (GCC) and red (RCC) chromatic coordinates). The transition dates in both spring and autumn differed somewhat according to method, presumably due to the vegetation status detection abilities of each vegetation metric. We found that LAI estimation from canopy cover images may be influenced by automatic exposure settings, which limits the ability to detect subtle changes in phenology during the transition phases in both spring and autumn. Particularly in autumn, the color-based metrics calculated from the phenocam imagery are decoupled from leaf area dynamics and thus PAI. While above and below canopy PAR measurements could yield the better indicators for estimating LAI, its seasonal dynamics, and associated phenological transition dates in long-term monitoring, we argue that there are obvious benefits to the multi-sensor approach used here.

On the relationship between continuous measures of canopy greenness derived using near-surface remote sensing and satellite-derived vegetation products

Over the last two decades, satellite-derived estimates of biophysical variables have been increasingly used in operational services, requiring quantification of their accuracy and uncertainty. Evaluating satellite-derived vegetation products is challenging due to their moderate spatial resolution, the heterogeneity of the terrestrial landscape, and difficulties in adequately characterising spatial and temporal vegetation dynamics. In recent years, near-surface remote sensing has emerged as a potential source of data against which satellite-derived vegetation products can be evaluated. Several studies have focussed on the evaluation of satellite-derived phenological transition dates, however in most cases the shape and magnitude of the underlying time-series are neglected. In this paper, we investigated the relationship between the green chromatic coordinate (GCC) derived using near-surface remote sensing and a range of vegetation products derived from the Medium Resolution Imaging Spectrometer (MERIS) throughout the growing season. Moderate to strong relationships between the GCC and vegetation products derived from MERIS were observed at deciduous forest sites. Weak relationships were observed over evergreen forest sites as a result of their subtle seasonality, which is likely masked by atmospheric, bidirectional reflectance distribution function (BRDF), and shadowing effects. Temporal inconsistencies were attributed to the oblique viewing geometry of the digital cameras and differences in the incorporated spectral bands. In addition, the commonly observed summer decline in GCC values was found to be primarily associated with seasonal variations in brown pigment concentration, and to a lesser extent illumination geometry. At deciduous sites, increased sensitivity to initial increases in canopy greenness was demonstrated by the GCC, making it particularly well-suited to identifying the start of season when compared to satellite-derived vegetation products. Nevertheless, in some cases, the relationship between the GCC and vegetation products derived from MERIS was found to saturate asymptotically. This limits the potential of the approach for evaluation of the vegetation products that underlie satellite-derived phenological transition dates, and for the continuous monitoring of vegetation during the growing season, particularly at medium to high biomass study sites.

Comparisons of global land surface seasonality and phenology derived from AVHRR, MODIS, and VIIRS data

AbstractLand surface seasonality has been widely investigated from satellite observations for monitoring the dynamics of terrestrial ecosystems in response to climate change. A great deal of efforts has focused on the characterization of interannual variation and long‐term trends of vegetation phenological metrics derived from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data across regional and global scales. Recently, Visible Infrared Imaging Radiometer Suite (VIIRS) data have become available for the detections of global land surface phenology. These data sets provide us a potential opportunity to generate a consistent long‐term climate data record of land surface phenology. However, to bridge the multiple‐sensor‐based phenology measurements, we need to understand their consistency and discrepancy across various geographical and ecological regions. To this end, we collected daily AVHRR, MODIS, and VIIRS data (~5 km) globally, compared their temporal trajectories of two band enhanced vegetation index (EVI2) during 2013 and 2014, examined their discrepancy of phenology retrievals, and explored the influence of EVI2 data quality from the three satellite sensors on phenology detections. The results revealed the similarity and discrepancy of EVI2 time series and land surface phenology retrievals globally. Specifically, EVI2 time series from VIIRS and MODIS observations were similar with some discrepancies mainly arising from unsystematic impact factors. In contrast, VIIRS EVI2 was systematically higher than AVHRR EVI2, in which their differences could be greatly reduced by intersensor calibration. Further, the quality of EVI2 time series among AVHRR, MODIS, and VIIRS varied largely across the globe, which was generally better in Northern Hemisphere than in Southern Hemisphere. Their differences in EVI2 data quality led to the inconsistencies in the detections of phenological dates. On average, the absolute difference of phenological transition dates among the three products was larger than 10 days in about 30% of pixels in Northern Hemisphere and more than 40% in Southern Hemisphere.

Assessing the thermal dissipation sap flux density method for monitoring cold season water transport in seasonally snow-covered forests.

Productivity of conifers in seasonally snow-covered forests is high before and during snowmelt when environmental conditions are optimal for photosynthesis. Climate change is altering the timing of spring in many locations, and changes in the date of transition from winter dormancy can have large impacts on annual productivity. Sap flow methods provide a promising approach to monitor tree activity during the cold season and the winter-spring and fall-winter transitions. Although sap flow techniques have been widely used, cold season results are generally not reported. Here we examine the feasibility of using the Granier thermal dissipation (TD) sap flux density method to monitor transpiration and dormancy of evergreen conifers during the cold season. We conducted a laboratory experiment which demonstrated that the TD method reliably detects xylem water transport (when it occurs) both at near freezing temperature and at low flow rate, and that the sensors can withstand repeated freeze-thaw events. However, the dependence between sensor output and water transport rate in these experiments differed from the established TD relation. In field experiments, sensors installed in two Abies forests lasted through two winters and a summer with low failure. The baseline (no-flow) sensor output varied considerably with temperature during the cold season, and a new baseline algorithm was developed to accommodate this variation. The Abies forests differed in elevation (2070 and 2620 m), and there was a clear difference in timing of initiation and cessation of transpiration between them. We conclude that the TD method can be reliably used to examine water transport during cold periods with associated low flow conditions.

George (Gogu) Constantinescu

George (Gogu) Constantinescu (October 4, 1891 - December 11, 1965) was a Romanian scientist and engineer, often considered to be one of the most important Romanian engineers. He was responsible for creating a new field of mechanics, called "sonicity," which describes the transmission of energy through vibrations in fluid or solid bodies. He applied the new theory to numerous inventions: sonic, sonic hammer, sonic pomp and others. Among other achievements, there is also a pulling device among the propeller blades regardless of its speed and the first automatic gearshift. He has actively participated in the construction of English aircraft, the Bristol type, while he lived in England. He was the first to use reinforced concrete in the construction of buildings in Romania (among the buildings he built, we can mention: the Patriarchal Palace, the Athenee Palace Hotel and the Great Mosque in Constanta). Gogu Constantinescu was one of those brilliant minds, whose ideas have long outstripped his physical existence, but which today preserves its topicality, surprising by its accuracy, inventiveness and applicability. Gogu Constantinescu's account includes over 317 patents patented in the USA, Denmark, Switzerland, Austria, Germany, Great Britain, France, Romania, etc., as well as others that have never been published. A small calculation shows that since the first invention (1907), until the date of transition to eternity (1965), on average every 4 months a patent was made and if we count only the most prolific years, it results in invention per month. We can say that what Tesla did in electronics, Constantinescu succeeded in mechanics. If Nicolae Tesla invented and transmitted electromagnetic waves (electromagnetic oscillations) through the atmosphere, George Constantinescu invented mechanical sonic oscillations with which he transmitted sonic waves only through continuous media (tubes or pipes, water, oil, various liquids, air, gas, or full bars). Both transmit the waves (produced by oscillations), as well as the energy and power included in these waves, thus managing to transmit energy and power at small, medium, large, even very large distances, controlling and controlling the phenomena and processes from a distance or a large distance.

An evaluation of the breast cancer Well Follow-up Care Initiative using administrative databases: A new model of analysis.

1 Background: Cancer Care Ontario (CCO) implemented the Well Follow-up Care Initiative (WFCI) to transition low-risk breast cancer (BC) survivors from oncologist to primary care providers. The objective of this work was to compare both the health system resources utilized and their associated costs, among women in the WFCI (cases) and women who were not transitioned (controls). Methods: Cases were linked to provincial administrative databases and matched to a control group based on year of diagnosis, cancer stage, age, comorbidity, income, geographic area of residence, and prior health system use. Health system resource utilization (physician, hospitalization, diagnostics, medication, and homecare) was ascertained per group. The annual mean and median costs (CAD 2014) per patient were determined. Annualized incremental costs between cases and controls were estimated using generalized estimating equations, accounting for matched pairs. Results: Results are based on 2,324 cases and 2,324 controls (mean age 64.4 and 64.9 years, respectively). During an average of 2.5 years of follow-up since the transition date, there were significant differences between the two groups for mean annual visits per patient with a medical oncologist (0.4 vs. 1.3, p<0.001) and radiation oncologist (0.2 vs. 0.4, p<0.001). There was no significant difference in mean annual family physician visits per patient (7.4 vs. 7.9, p=0.082). The intervention group had fewer inpatient hospitalizations (75.6% vs. 79.9%) and cancer clinic visits (84.9% vs. 94.0%). While there was a higher number of mammograms for cases compared to controls, other diagnostic tests (bone scan, CT, MRI, ultrasound, and x-rays) were done less frequently. The model was associated with a 39.3% reduction in mean annual costs ($6,575 among cases and $10,832 among controls) and a 22.1% reduction in median annual costs ($2,261 among cases and $2,903 among controls). Conclusions: Transitioning BC survivors to primary care was associated with fewer health system resources and had a lower annual mean cost per patient than women who were not transitioned.

Spatially detailed retrievals of spring phenology from single-season high-resolution image time series

Vegetation indices derived from satellite image time series have been extensively used to estimate the timing of phenological events like season onset. Medium spatial resolution (≥250m) satellite sensors with daily revisit capability are typically employed for this purpose. In recent years, phenology is being retrieved at higher resolution (≤30m) in response to increasing availability of high-resolution satellite data. To overcome the reduced acquisition frequency of such data, previous attempts involved fusion between high- and medium-resolution data, or combinations of multi-year acquisitions in a single phenological reconstruction. The objectives of this study are to demonstrate that phenological parameters can now be retrieved from single-season high-resolution time series, and to compare these retrievals against those derived from multi-year high-resolution and single-season medium-resolution satellite data. The study focuses on the island of Schiermonnikoog, the Netherlands, which comprises a highly-dynamic saltmarsh, dune vegetation, and agricultural land. Combining NDVI series derived from atmospherically-corrected images from RapidEye (5m-resolution) and the SPOT5 Take5 experiment (10m-resolution) acquired between March and August 2015, phenological parameters were estimated using a function fitting approach. We then compared results with phenology retrieved from four years of 30m Landsat 8 OLI data, and single-year 100m Proba-V and 250m MODIS temporal composites of the same period. Retrieved phenological parameters from combined RapidEye/SPOT5 displayed spatially consistent results and a large spatial variability, providing complementary information to existing vegetation community maps. Retrievals that combined four years of Landsat observations into a single synthetic year were affected by the inclusion of years with warmer spring temperatures, whereas adjustment of the average phenology to 2015 observations was only feasible for a few pixels due to cloud cover around phenological transition dates. The Proba-V and MODIS phenology retrievals scaled poorly relative to their high-resolution equivalents, indicating that medium-resolution phenology retrievals need to be interpreted with care, particularly in landscapes with fine-scale land cover variability.

Using data from Landsat, MODIS, VIIRS and PhenoCams to monitor the phenology of California oak/grass savanna and open grassland across spatial scales

The Mediterranean-type oak/grass savanna of California is composed of widely spaced oak trees with understory grasses. These savanna regions are interspersed with large areas of more open grasslands. The ability of remotely sensed data (with various spatial resolutions) to monitor the phenology in these water-limited oak/grass savannas and open grasslands is explored over the 2012–2015 timeframe using data from Landsat (30m), the MODerate resolution Imaging Spectroradiometer (MODIS – gridded 500m), and the Visible Infrared Imaging Radiometer Suite (VIIRS – gridded 500m) data. Vegetation phenology detected from near-ground level, webcam based PhenoCam imagery from two sites in the Ameriflux Network (long-term flux measurement network of the Americas) (Tonzi Ranch and Vaira Ranch) is upscaled, using a National Agriculture Imagery Program (NAIP) aerial image (1m), to evaluate the detection of vegetation phenology of these savannas and grasslands with the satellite data. Results show that the Normalized Difference Vegetation Index (NDVI) time series observed from the satellite sensors are all strongly correlated with the PhenoCam NDVI values from Tonzi Ranch (R2>0.67) and Vaira Ranch (R2>0.81). However, the different viewing geometries and spatial coverage of the PhenoCams and the various satellite sensors may cause differences in the absolute phenological transition dates. Analysis of frequency histograms of phenological dates illustrate that the phenological dates in the relatively homogeneous open grasslands are consistent across the different spatial resolutions, in contrast, the relatively heterogeneous oak/grass savannas display has somewhat later greenup, maturity, and dormancy dates at 30m resolution than at 500m scale due to the different phenological cycles exhibited by the overstory trees and the understory grasses. In addition, phenologies derived from the MODIS view angle corrected reflectance (Nadir BRDF-Adjusted Reflectance – NBAR) and the newly developed VIIRS NBAR are shown to provide comparable phenological dates (majority absolute bias ≤2days) in this area.

Phenology from Landsat when data is scarce: Using MODIS and Dynamic Time-Warping to combine multi-year Landsat imagery to derive annual phenology curves

Green-leaf phenology describes the development of vegetation throughout a growing season and greatly affects the interaction between climate and the biosphere. Remote sensing is a valuable tool to characterize phenology over large areas but doing at fine- to medium resolution (e.g., with Landsat data) is difficult because of low numbers of cloud-free images in a single year. One way to overcome data availability limitations is to merge multi-year imagery into one time series, but this requires accounting for phenological differences among years. Here we present a new approach that employed a time series of a MODIS vegetation index data to quantify interannual differences in phenology, and Dynamic Time Warping (DTW) to re-align multi-year Landsat images to a common phenology that eliminates year-to-year phenological differences. This allowed us to estimate annual phenology curves from Landsat between 2002 and 2012 from which we extracted key phenological dates in a Monte-Carlo simulation design, including green-up (GU), start-of-season (SoS), maturity (Mat), senescence (Sen), end-of-season (EoS) and dormancy (Dorm). We tested our approach in eight locations across the United States that represented forests of different types and without signs of recent forest disturbance. We compared Landsat-based phenological transition dates to those derived from MODIS and ground-based camera data from the PhenoCam-network. The Landsat and MODIS comparison showed strong agreement. Dates of green-up, start-of-season and maturity were highly correlated (r 0.86-0.95), as were senescence and end-of-season dates (r>0.85) and dormancy (r>0.75). Agreement between the Landsat and PhenoCam was generally lower, but correlation coefficients still exceeded 0.8 for all dates. In addition, because of the high data density in the new Landsat time series, the confidence intervals of the estimated keydates were substantially lower than in case of MODIS and PhenoCam. Our study thus suggests that by exploiting multi-year Landsat imagery and calibrating it with MODIS data it is possible to describe green-leaf phenology at much finer spatial resolution than previously possible, highlighting the potential for fine scale phenology maps using the rich Landsat data archive over large areas.

Season Spotter: Using Citizen Science to Validate and Scale Plant Phenology from Near-Surface Remote Sensing

The impact of a rapidly changing climate on the biosphere is an urgent area of research for mitigation policy and management. Plant phenology is a sensitive indicator of climate change and regulates the seasonality of carbon, water, and energy fluxes between the land surface and the climate system, making it an important tool for studying biosphere–atmosphere interactions. To monitor plant phenology at regional and continental scales, automated near-surface cameras are being increasingly used to supplement phenology data derived from satellite imagery and data from ground-based human observers. We used imagery from a network of phenology cameras in a citizen science project called Season Spotter to investigate whether information could be derived from these images beyond standard, color-based vegetation indices. We found that engaging citizen science volunteers resulted in useful science knowledge in three ways: first, volunteers were able to detect some, but not all, reproductive phenology events, connecting landscape-level measures with field-based measures. Second, volunteers successfully demarcated individual trees in landscape imagery, facilitating scaling of vegetation indices from organism to ecosystem. And third, volunteers’ data were used to validate phenology transition dates calculated from vegetation indices and to identify potential improvements to existing algorithms to enable better biological interpretation. As a result, the use of citizen science in combination with near-surface remote sensing of phenology can be used to link ground-based phenology observations to satellite sensor data for scaling and validation. Well-designed citizen science projects targeting improved data processing and validation of remote sensing imagery hold promise for providing the data needed to address grand challenges in environmental science and Earth observation.

Currency Amounts in the SDR Basket - Proposed Changes to the Rounding Methodology

Currency amounts are used to determine the daily value of the SDR. Currency amounts are the number of units of each currency in the SDR basket. The value of the SDR (in U.S. dollars) is the sum of these amounts, valued at daily exchange rates of the currencies against the U.S. dollar. These currency amounts are determined on the last business day before the new SDR basket becomes effective (transition date) such that they correspond to the currency weights determined by the IMF Executive Board in the context of the SDR Review, and remain fixed over the SDR valuation period. To facilitate SDR users in adjusting their portfolios to the new basket, the IMF publishes illustrative currency amounts in the lead up to the transition date.

Analyzing Relationship between Satellite-Based Plant Phenology and Temperature

Climate change are known to have had enormous impacts on plant phenology and thus to have damage on other species which are interacted within ecosystem. In Korea, however, it is difficult to analyze the relationship between climate and phenology due to the limitation of measurement data of plant phenological records. In this study, to be effective analysis of SOG(start of growing season), we used phenological transition dates by using satellite data. Then, we identified the most influential variable in variation of SOG throughout the relationship between SOG and temperature factors. As a result, there is a strong correlation between the SOG and April temperature, TSOGmin(, 12days). This study is expected to be used for predicting plant phenological change using climate change scenario data.

Projections of the shifting envelope of Water cycle variability

The time of departure of water cycle variables from historical climatic conditions is quantified from multi-model suites of climate change simulations. Two thresholds are examined: the historical (1860–2005) mean and the range of variability during that same period. The metric is the year when the future range of variability in RCP4.5 and RCP8.5 moves permanently above or below the historical mean for seasonal average values of precipitation, runoff and surface soil moisture. There is a large range of inter-model variability, so both multi-model means of the year of departure and the fraction of models exceeding thresholds by the end of the 21st century are calculated. There is a strong tendency for transition to wetter winter conditions at high northern latitudes for precipitation, but a predominance of dry departures in JJA, with a slight tendency for positive departures in precipitation when considered globally across the year. For runoff there are approximately equal areas of permanently wetter and drier conditions, but runoff is the most sensitive term with the largest areas of departure early in the 21st century, and the greatest propensity to move outside the historical range of variability. Soil moisture trends are predominantly negative with large regions shifting to permanently drier conditions. For all three variables there is a clear increase over time in the total area becoming permanently wetter or drier than the historical mean. The termination of many models’ simulations at 2100, often before permanent transitions are reached, affects the calculations, leading to earlier transition dates than if simulations are extended.

Imaging phenology; scaling from camera plots to landscapes

Abstract Information on the spatial and temporal patterns of plant phenology is important to develop a more comprehensive understanding of food availability and habitat for many animal species. The combination of broad scale, regional climatic, and more localized, site-level drivers presents a challenge when upscaling phenology from the plot to the region. Likewise, developing relationships between ground- or camera-based estimates and satellite imagery remains difficult due to the trade-off between temporal and spatial resolution. Landsat imagery, with its 16 day temporal resolution, is often thought of as being insufficient for timely observation of changes in vegetation throughout the year. However the free availability of the Landsat archive has enabled a major shift in the way Landsat imagery is processed moving towards pixel, rather than scene, based analyses. In this paper we build on previous research by examining the applicability and accuracy of Landsat derived phenology curves beyond deciduous stands into more mixed stands and conifer dominated forest types in the Rocky Mountains and foothills in Alberta, Canada. In addition, we discuss the application of these Landsat phenology curves to phenology of understorey species which are linked to habitat selection for free roaming wildlife, in particular grizzly bears. The agreement between Landsat- and camera-derived estimates of key phenological events was stronger for green-up (RMSE = 7 days) than for senescence (RMSE = 14 days). Our results show that yearly adjustment of green-up and senescence dates using available Landsat observations improved the agreement with camera-derived estimates when compared to average annual curves. Seasonal phenology transition dates accepted as valid ranged from 25% for alpine herbaceous pixels to 75% for closed deciduous, demonstrating the variable success of this approach across land cover types. Season transition dates were rejected if pixels lacked a strong enough green-up signal in Landsat spectral indices or if the estimated dates fell outside of the valid range. We conclude by investigating the spatial patterns of seasonal phenology at the Landsat scale, and assess the relative importance of regional vs. microsite conditions as well as the utility of these data for resource and wildlife management.

Multi-criteria evaluation of the suitability of growth functions for modeling remotely sensed phenology

Reliable information related to vegetation phenology is required to improve understanding of land–atmosphere coupling and the biosphere's response and feedbacks to climate change. The logistic function is commonly used to model bounded growth and decay and extract phenological information from remotely sensed vegetation indices. However, several other growth functions can also model bounded growth and decay and may have more desirable properties than the logistic function for capturing deciduous forest phenology. We employed three complimentary criteria and evaluated the suitability of the Gompertz, logistic, mirror-Gompertz, and Richards functions to reliably capture remotely sensed phenology of deciduous forests. Our analyses showed that although all the four growth functions fit remotely sensed data equally well, their ability to capture rapidly changing phenology early in spring and late in fall differs significantly. Using 10 years of field measurements from two deciduous forest sites in the northeastern United States, we showed that dynamics in the fraction of absorbed photosynthetically active radiation (FAPAR) phenology is asymmetric in both spring and fall. It develops more rapidly early in spring and decays more rapidly late in fall. A flexible function that can capture these asymmetric dynamics is likely to capture the phenological development and the transition dates better. Comparison with field measurements of start-of-season (SOS), end-of-season (EOS), and growing period length (GPL) confirmed this. Mean differences between modeled and observed GPL was 13.5 and 18.5 days for the Richards and logistic function, respectively, at Harvard Forest and 2.6 and 7.1 days, respectively at Hubbard Brook Forest. Our analyses also showed that FAPAR and normalized difference vegetation index have a strong linear relationship in spring, but correlate poorly in fall. Our results suggest that a flexible function line Richards is likely to be more reliable for modeling phenology and retrieving information of transitions events from remotely sensed NDVI.

An Analysis of the Spring-to-Summer Transition in the West Central Plains for Application to Long Range Forecasting

The spring-to-summer transition is of special importance in long range forecasting, as the general circulation transitions to a less energetic regime. This affects the Midwestern United States in a profound way, since agriculture is very sensitive to the variability of weather and climate. Beginning at the local scale, surface temperature observations are used from a representative station in the West Central Missouri Plains region in order to identify the shift from late spring to early summer. Using upper-air re-analyses as a supplement, the 500-mb height observations are examined to find a spring-to-summer transition date by tracking the location of a representative contour. Each of these is used to identify spring-to-summer transition date and then statistical analysis is performed on this long-term data set. Finally, teleconnections, specifically the influence of El Ni?o Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO), and blocking are examined in order to quantify interannual variability. It was found that examining these criteria, developed in an earlier study that covered a much shorter time period, produced similar statistics to this 68-year study of spring-to-summer transitions. It was also found that the onset of La Ni?a was associated with hotter summers in the region, a result first found in the earlier study, but this association was much stronger here.

Смена технологических укладов в экономике Канады

The paper analyzes how the dates of transition of technological modes are formed, based on the Kondratieff cycles. The study comprises the historical period of 1870–2008. For the mentioned period it is possible to identify the dates of transition to the next technological mode with clear reference to the concrete data, concerning the third, the fourth, the fifth and the sixth technological modes. As the study shows, the use of Kondratieff cycles makes it is possible to clarify exact dates of technological modes shifts for certain time periods. This, in turn, makes it possible to construct predictive models to identify how much time will it take for the next technological mode to origin and also the terms of shift to the next mode, with reference to the exact dates.

Impact of advection loss due to wind and estuarine circulation on the timing of the spring phytoplankton bloom in a fjord

AbstractA coupled biophysical model is used to explore the physical controls involved in the timing of the spring phytoplankton bloom in fjords. Observations from Rivers Inlet, British Columbia, are used to force and evaluate the model. It is found that the interannual variation in timing is due primarily to variations in retention, in particular, to variations in horizontal advection out of the fjord. The two dominant processes are (i) strong outflow winds rapidly advecting the surface layer and thus the phytoplankton population out of the fjord and (ii) losses due to high river flux increasing the estuarine circulation. Both processes delay the timing of spring bloom. Smaller effects on the interannual variation are due to increased wind mixing which deepens the mixing layer and reduces light to phytoplankton, and increased river flow which increases the stratification and decreases the mixing layer depth. Observed interannual variations in cloudiness were small. Strong outflow winds are common in winter along the British Columbia coast, but generally cease after the spring wind transition. Thus, observed interdecadal variations in the spring transition date probably imply strong variations in the timing of spring phytoplankton blooms in British Columbia fjords.

Influence of the QBO and solar activity on interannual variability of the spring-time transition of stratosphere circulation

In this paper the influence of solar activity on variability of the springtime transition dates of stratospheric circulation is investigated. To detect the influence, the springtime transition and solar activity datasets were grouped according to the phases of the Quasi-Biennial Oscillation (QBO). It was obtained that there is a dependence of spring transition dates on solar activity. In case of dividing data on early and later spring transition, the stronger influence of solar signal is revealed at late spring transition. It was also shown that under high solar activity conditions, the relation between spring transition dates and solar activity is stronger than at low one.