Transient Earth system responses to cumulative carbon dioxide emissions: linearities, uncertainties, and probabilities in an observation-constrained model ensemble

Information on the relationship between cumulative fossil CO2 emissions and multiple climate targets is essential to design emission mitigation and climate adaptation strategies. In this study, the transient response of a climate or environmental variable per trillion tonnes of CO2 emissions, termed TRE, is quantified for a set of impact-relevant climate variables and from a large set of multi-forcing scenarios extended to year 2300 towards stabilization. An  ∼ 1000-member ensemble of the Bern3D-LPJ carbon–climate model is applied and model outcomes are constrained by 26 physical and biogeochemical observational data sets in a Bayesian, Monte Carlo-type framework. Uncertainties in TRE estimates include both scenario uncertainty and model response uncertainty. Cumulative fossil emissions of 1000 Gt C result in a global mean surface air temperature change of 1.9 °C (68 % confidence interval (c.i.): 1.3 to 2.7 °C), a decrease in surface ocean pH of 0.19 (0.18 to 0.22), and a steric sea level rise of 20 cm (13 to 27 cm until 2300). Linearity between cumulative emissions and transient response is high for pH and reasonably high for surface air and sea surface temperatures, but less pronounced for changes in Atlantic meridional overturning, Southern Ocean and tropical surface water saturation with respect to biogenic structures of calcium carbonate, and carbon stocks in soils. The constrained model ensemble is also applied to determine the response to a pulse-like emission and in idealized CO2-only simulations. The transient climate response is constrained, primarily by long-term ocean heat observations, to 1.7 °C (68 % c.i.: 1.3 to 2.2 °C) and the equilibrium climate sensitivity to 2.9 °C (2.0 to 4.2 °C). This is consistent with results by CMIP5 models but inconsistent with recent studies that relied on short-term air temperature data affected by natural climate variability.

Environmental correlates of species rank − abundance distributions in global drylands

Theoretical models predict lognormal species abundance distributions (SADs) in stable and productive environments, with log-series SADs in less stable, dispersal driven communities. We studied patterns of relative species abundances of perennial vascular plants in global dryland communities to: (i) assess the influence of climatic and soil characteristics on the observed SADs, (ii) infer how environmental variability influences relative abundances, and (iii) evaluate how colonisation dynamics and environmental filters shape abundance distributions. We fitted lognormal and log-series SADs to 91 sites containing at least 15 species of perennial vascular plants. The dependence of species relative abundances on soil and climate variables was assessed using general linear models. Irrespective of habitat type and latitude, the majority of the SADs (70.3%) were best described by a lognormal distribution. Lognormal SADs were associated with low annual precipitation, higher aridity, high soil carbon content, and higher variability of climate variables and soil nitrate. Our results do not corroborate models predicting the prevalence of log-series SADs in dryland communities. As lognormal SADs were particularly associated with sites with drier conditions and a higher environmental variability, we reject models linking lognormality to environmental stability and high productivity conditions. Instead our results point to the prevalence of lognormal SADs in heterogeneous environments, allowing for more evenly distributed plant communities, or in stressful ecosystems, which are generally shaped by strong habitat filters and limited colonisation. This suggests that drylands may be resilient to environmental changes because the many species with intermediate relative abundances could take over ecosystem functioning if the environment becomes suboptimal for dominant species.

A STUDY OF INFLUENZA AND OF STATISTICAL METHODS USED TO REPORT INFLUENZA

This paper defines and compares several models for describing excess influenza pneumonia mortality in Houston. First, the methodology used by the Center for Disease Control is examined and several variations of this methodology are studied. All of the models examined emphasize the difficulty of omitting epidemic weeks.^ In an attempt to find a better method of describing expected and epidemic mortality, time series methods are examined. Grouping in four-week periods, truncating the data series to adjust epidemic periods, and seasonally-adjusting the series y(,t), by:^ (DIAGRAM, TABLE OR GRAPHIC OMITTED...PLEASE SEE DAI)^ is the best method examined. This new series w(,t) is stationary and a moving average model MA(1) gives a good fit for forecasting influenza and pneumonia mortality in Houston.^ Influenza morbidity, other causes of death, sex, race, age, climate variables, environmental factors, and school absenteeism are all examined in terms of their relationship to influenza and pneumonia mortality. Both influenza morbidity and ischemic heart disease mortality show a very high relationship that remains when seasonal trends are removed from the data. However, when jointly modeling the three series it is obvious that the simple time series MA(1) model of truncated, seasonally-adjusted four-week data gives a better forecast.^

Stable isotope ratios and chemistry on corals from the Caribbean Sea

Instrumental climate data are limited in length and only available with low spatial coverage before the middle of the 20th century. This is too short to reliably determine and interpret decadal and longer scale climate variability and to understand the underlying mechanisms with sufficient accuracy. A proper knowledge of past variability of the climate system is needed to assess the anthropogenic impact on climate and ecosystems, and also important with regard to long-range climate forecasting. Highly-resolved records of past climate variations that extend beyond pre-industrial times can significantly help to understand long-term climate changes and trends. Indirect information on past environmental and climatic conditions can be deduced from climate-sensitive proxies. Large colonies of massive growing tropical reef corals have been proven to sensitively monitor changes in ambient seawater. Rapid skeletal growth, typically ranging between several millimeters to centimeters per year, allows the development of proxy records at sub-seasonal resolution. Stable oxygen isotopic composition and trace elemental ratios incorporated in the aragonitic coral skeleton can reveal a detailed history of past environmental conditions, e.g., sea surface temperature (SST). In general, coral-based reconstructions from the tropical Atlantic region have lagged behind the extensive work published using coral records from the Indian and Pacific Oceans. Difficulties in the analysis of previously utilized coral archives from the Atlantic, typically corals of the genera Montastrea and Siderastrea, have so far exacerbated the production of long-term high-resolution proxy records. The objective of this study is the evaluation of massive fast-growing corals of the species Diploria strigosa as a new marine archive for climate reconstructions from the tropical Atlantic region. For this purpose, coral records from two study sites in the eastern Caribbean Sea (Guadeloupe, Lesser Antilles; and Archipelago Los Roques, Venezuela) were examined. At Guadeloupe, a century-long monthly resolved multi-proxy coral record was generated. Results present the first d18O (Sr/Ca)-SST calibration equations for the Atlantic braincoral Diploria strigosa, that are robust and consistent with previously published values using other coral species from different regions. Both proxies reflect local variability of SST on a sub-seasonal scale, which is a precondition for studying seasonally phase-locked climate variations, as well as track variability on a larger spatial scale (i.e., in the Caribbean and tropical North Atlantic). Coral Sr/Ca reliably records local annual to interannual temperature variations and is higher correlated to in-situ air temperature than to grid-SST. The warming calculated from coral Sr/Ca is concurrent with the strong surface temperature increase at the study site during the past decades. Proxy data show a close relationship to major climate signals from the tropical Pacific and North Atlantic (the El Niño Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO)) affecting the seasonal cycle of SST in the North Tropical Atlantic (NTA). Coral oxygen isotopes are also influenced by seawater d18O (d18Osw) which is linked to the hydrological cycle, and capture large-scale climate variability in the NTA region better than Sr/Ca. Results from a quantitative comparison between extreme events in the two most prominent modes of external forcing, namely the ENSO and NAO, and respective events recorded in seasonal coral d18O imply that SST variability at the study site is highly linked to Pacific and North Atlantic variability, by this means supporting the assumptions of observational- and model-based studies which suggest a strong impact of ENSO and NAO forcings onto the NTA region through a modulation of trade wind strength in winter. Results from different spectral analysis tools suggest that interannual climate variability recorded by the coral proxies is II largely dictated by Pacific ENSO forcing, whereas at decadal and longer timescales the influence of the NAO is dominan. tThe Archipelago Los Roques is situated in the southeastern Caribbean Sea, north of the Venezuelan coast. Year-to-year variations in monthly resolved coral d18O of a nearcentury- long Diploria strigosa record are significantly correlated with SST and show pronounced multidecadal variations. About half of the variance in coral d18O can be explained by variations in seawater d18O, which can be estimated by calculating the d18Oresidual via subtracting the SST component from measured coral d18O. The d18Oresidual and a regional precipitation index are highly correlated at low frequencies, suggesting that d18Osw variations are primarily atmospheric-driven. Warmer SSTs at Los Roques broadly coincide with higher precipitation in the southeastern Caribbean at multidecadal time scales, effectively strengthening the climate signal in the coral d18O record. The Los Roques coral d18O record displays a strong and statistically significant relationship to different indices of hurricane activity during the peak of the Atlantic hurricane season in boreal summer and is a particularly good indicator of decadal-multidecadal swings in the latter indices. In general, the detection of long-term changes and trends in Atlantic hurricane activity is hampered due to the limited length of the reliable instrumental record and the known inhomogeneity in the observational databases which result from changes in observing practice and technology over the years. The results suggest that coral-derived proxy data from Los Roques can be used to infer changes in past hurricane activity on timescales that extend well beyond the reliable record. In addition, the coral record exhibits a clear negative trend superimposed on the decadal to multidecadal cycles, indicating a significant warming and freshening of surface waters in the genesis region of tropical cyclones during the past decades. The presented coral d18O time series provides the first and, so far, longest continuous coral-based record of hurricane activity. It appears that the combination of both signals (SST and d18Osw) in coral d18O leads to an amplification of large-scale climate signals in the record, and makes coral d18O even a better proxy for hurricane activity than SST alone. Atlantic hurricane activity naturally exhibits strong multidecadal variations that are associated with the Atlantic Multidecadal Oscillation (AMO), the major mode of lowfrequency variability in the North Atlantic Ocean. However, the mechanisms underlying this multidecadal variability remain controversial, primarily because of the limited instrumental record. The Los Roques coral d18O displays strong multidecadal variability with a period of approximately 60 years that is closely related to the AMO, making the Archipelago Los Roques a very sensitive location for studying low-frequency climate variability in the Atlantic Ocean. In summary, the coral records presented in this thesis capture different key climate variables in the north tropical Atlantic region very well, indicating that fast-growing Diploria strigosa corals represent a promising marine archive for further proxy-based reconstructions of past climate variability on a range of time scales.

Downwelling solar irradiance, upwelling solar radiance, sky leaving radiance, and cloud cover observed during ARCHEMHAB study (on Maria S. Merian Leg MSM21/3) from 2012-07-26 to 2012-08-10

The need to obtain ocean color essential climate variables (OC-ECVs) using hyperspectral technology has gained increased interest in recent years. Assessing ocean color on a large scale in high latitude environments using satellite remote sensing is constrained by polar environmental conditions. Nevertheless, on a small scale we can assess ocean color using above-water and in-water remote sensing. Unfortunately, above-water remote sensing can only determine apparent optical properties leaving the sea surface and is susceptible to near surface environmental conditions for example sky and sunglint. Consequently, we have to rely on accurate in-water remote sensing as it can provide both synoptic inherent and apparent optical properties of seawater. We use normalized water leaving radiance LWN or the equivalent remote sensing reflectance RRS from 27 stations to compare the differences in above-water and in-water OC-ECVs. Analysis of above-water and in-water RRS spectra provided very good match-ups (R2 > 0.97, MSE<1.8*10**-7) for all stations. The unbiased percent differences (UPD) between above-water and in-water approaches were determined at common OC-ECVs spectral bands (410, 440, 490, 510 and 555) nm and the classic band ratio (490/555) nm. The spectral average UPD ranged (5 - 110) % and band ratio UPD ranged (0 - 12) %, the latter showing that the 5% uncertainty threshold for ocean color radiometric products is attainable. UPD analysis of these stations West of Greenland, Labrador Sea, Denmark Strait and West of Iceland also suggests that the differences observed are likely a result of environmental and instrumental perturbations.

30 years of synoptic observations from Neumayer Station with links to datasets

High temporal resolution (three hours) records of temperature, wind speed and sea level pressure recorded at Antarctic research station Neumayer (70°S, 8°W) during 1982-2011 are analysed to identify oscillations from daily to intraseasonal timescales. The diurnal cycle dominates the three-hourly time series of temperature during the Antarctic summer and is almost absent during winter. In contrast, the three-hourly time series of wind speed and sea level pressure show a weak diurnal cycle. The dominant pattern of the intraseasonal variability of these quantities, which captures the out-of-phase variation of temperature and wind speed with sea level pressure, shows enhanced variability at timescales of ~ 40 days and ~ 80 days, respectively. Correlation and composite analysis reveal that these oscillations may be related to tropical intraseasonal oscillations via large-scale eastward propagating atmospheric circulation wave-trains. The second pattern of intraseasonal variability, which captures in-phase variations of temperature, wind and sea level pressure, shows enhanced variability at timescales of ~ 35, ~ 60 and ~ 120 days. These oscillations are attributed to the Southern Annular Mode/Antarctic Oscillation (SAM/AAO) which shows enhanced variability at these timescales. We argue that intraseasonal oscillations of tropical climate and SAM/AAO are related to distinct patterns of climate variables measured at Neumayer.

Consumers mediate the effects of experimental ocean acidification and warming on primary producers

It is well known that ocean acidification can have profound impacts on marine organisms. However, we know little about the direct and indirect effects of ocean acidification and also how these effects interact with other features of environmental change such as warming and declining consumer pressure. In this study, we tested whether the presence of consumers (invertebrate mesograzers) influenced the interactive effects of ocean acidification and warming on benthic microalgae in a seagrass community mesocosm experiment. Net effects of acidification and warming on benthic microalgal biomass and production, as assessed by analysis of variance, were relatively weak regardless of grazer presence. However, partitioning these net effects into direct and indirect effects using structural equation modeling revealed several strong relationships. In the absence of grazers, benthic microalgae were negatively and indirectly affected by sediment-associated microalgal grazers and macroalgal shading, but directly and positively affected by acidification and warming. Combining indirect and direct effects yielded no or weak net effects. In the presence of grazers, almost all direct and indirect climate effects were nonsignificant. Our analyses highlight that (i) indirect effects of climate change may be at least as strong as direct effects, (ii) grazers are crucial in mediating these effects, and (iii) effects of ocean acidification may be apparent only through indirect effects and in combination with other variables (e.g., warming). These findings highlight the importance of experimental designs and statistical analyses that allow us to separate and quantify the direct and indirect effects of multiple climate variables on natural communities.

Modelling the spatio-temporal pattern of primary dispersal in stone pine (Pinus pinea L.) stands in the Northern Plateau (Spain)

Natural regeneration in stone pine (Pinus pinea L.) managed forests in the Spanish Northern Plateau is not achieved successfully under current silviculture practices, constituting a main concern for forest managers. We modelled spatio-temporal features of primary dispersal to test whether (a) present low stand densities constrain natural regeneration success and (b) seed release is a climate-controlled process. The present study is based on data collected from a 6 years seed trap experiment considering different regeneration felling intensities. From a spatial perspective, we attempted alternate established kernels under different data distribution assumptions to fit a spatial model able to predict P. pinea seed rain. Due to P. pinea umbrella-like crown, models were adapted to account for crown effect through correction of distances between potential seed arrival locations and seed sources. In addition, individual tree fecundity was assessed independently from existing models, improving parameter estimation stability. Seed rain simulation enabled to calculate seed dispersal indexes for diverse silvicultural regeneration treatments. The selected spatial model of best fit (Weibull, Poisson assumption) predicted a highly clumped dispersal pattern that resulted in a proportion of gaps where no seed arrival is expected (dispersal limitation) between 0.25 and 0.30 for intermediate intensity regeneration fellings and over 0.50 for intense fellings. To describe the temporal pattern, the proportion of seeds released during monthly intervals was modelled as a function of climate variables – rainfall events – through a linear model that considered temporal autocorrelation, whereas cone opening took place over a temperature threshold. Our findings suggest the application of less intensive regeneration fellings, to be carried out after years of successful seedling establishment and, seasonally, subsequent to the main rainfall period (late fall). This schedule would avoid dispersal limitation and would allow for a complete seed release. These modifications in present silviculture practices would produce a more efficient seed shadow in managed stands.

A silviculture-oriented spatio-temporal model for germination in Pinus pinea L. in the Spanish Northern Plateau based on a direct seeding experiment

Natural regeneration in Pinus pinea stands commonly fails throughout the Spanish Northern Plateau under current intensive regeneration treatments. As a result, extensive direct seeding is commonly conducted to guarantee regeneration occurrence. In a period of rationalization of the resources devoted to forest management, this kind of techniques may become unaffordable. Given that the climatic and stand factors driving germination remain unknown, tools are required to understand the process and temper the use of direct seeding. In this study, the spatio-temporal pattern of germination of P. pinea was modelled with those purposes. The resulting findings will allow us to (1) determine the main ecological variables involved in germination in the species and (2) infer adequate silvicultural alternatives. The modelling approach focuses on covariates which are readily available to forest managers. A two-step nonlinear mixed model was fitted to predict germination occurrence and abundance in P. pinea under varying climatic, environmental and stand conditions, based on a germination data set covering a 5-year period. The results obtained reveal that the process is primarily driven by climate variables. Favourable conditions for germination commonly occur in fall although the optimum window is often narrow and may not occur at all in some years. At spatial level, it would appear that germination is facilitated by high stand densities, suggesting that current felling intensity should be reduced. In accordance with other studies on P. pinea dispersal, it seems that denser stands during the regeneration period will reduce the present dependence on direct seeding.

Remote Sensing of Vegetation Change Across a Latitudinal Gradient in the Canadian Arctic

Global air surface temperatures and precipitation have increased over the last several decades resulting in a trend of greening across the Circumpolar Arctic. The spatial variability of warming and the inherent effects on plant communities has not proven to be uniform or homogeneous on global or local scales. We can apply remote sensing vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to map and monitor vegetation change (e.g., phenology, greening, percent cover, and biomass) over time. It is important to document how Arctic vegetation is changing, as it will have large implications related to global carbon and surface energy budgets. The research reported here examined vegetation greening across different spatial and temporal scales at two disparate Arctic sites: Apex River Watershed (ARW), Baffin Island, and Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU. To characterize the vegetation in the ARW, high spatial resolution WorldView-2 data were processed to create a supervised land-cover classification and model percent vegetation cover (PVC) (a similar process had been completed in a previous study for the CBAWO). Meanwhile, NDVI data spanning the past 30 years were derived from intermediate resolution Landsat data at the two Arctic sites. The land-cover classifications at both sites were used to examine the Landsat NDVI time series by vegetation class. Climate variables (i.e., temperature, precipitation and growing season length (GSL) were examined to explore the potential relationships of NDVI to climate warming. PVC was successfully modeled using high resolution data in the ARW. PVC and plant communities appear to reside along a moisture and altitudinal gradient. The NDVI time series demonstrated an overall significant increase in greening at the CBAWO (High Arctic site), specifically in the dry and mesic vegetation type. However, similar overall greening was not observed for the ARW (Low Arctic site). The overall increase in NDVI at the CBAWO was attributed to a significant increase in July temperatures, precipitation and GSL.

Miocene palaeoclimate reconstrutions from 11 sites in the Ukraine

Miocene deposits (marine and terrestrial) distributed throughout the whole territory of Ukraine contain numerous palaeontological remains including plant macro- and microfossils. The Miocene strata of Ukraine belong to the Central and the Eastern Paratethys and deposits from these regions have been studied palynologically. For the reconstruction of the vegetation of lowland and mountain areas in Ukraine palynological data have been complemented with data obtained from carpological and foliar studies. To obtain quantitative palaeoclimate data to reconstruct the Miocene climate evolution in the Carpathian realm and the Ukrainian Plain a total of 17 microfloral records combined from pollen counts of numerous samples are analyzed with respect to 7 climate variables using the Coexistence Approach.

Characteristics of soil profiles from the Ouémé Upper Catchment (HVO), Térou, Benin

Soil degradation threatens agricultural production and food security in Sub-Saharan Africa. In the coming decades, soil degradation, in particular soil erosion, will become worse through the expansion of agriculture into savannah and forest and changes in climate. This study aims to improve the understanding of how land use and climate change affect the hydrological cycle and soil erosion rates at the catchment scale. We used the semi-distributed, time-continuous erosion model SWAT (Soil Water Assessment Tool) to quantify runoff processes and sheet and rill erosion in the Upper Ouémé River catchment (14500 km**2, Central Benin) for the period 1998-2005. We could then evaluate a range of land use and climate change scenarios with the SWAT model for the period 2001-2050 using spatial data from the land use model CLUE-S and the regional climate model REMO. Field investigations were performed to parameterise a soil map, to measure suspended sediment concentrations for model calibration and validation and to characterise erosion forms, degraded agricultural fields and soil conservation practices. Modelling results reveal current "hotspots" of soil erosion in the north-western, eastern and north-eastern parts of the Upper Ouémé catchment. As a consequence of rapid expansion of agricultural areas triggered by high population growth (partially caused by migration) and resulting increases in surface runoff and topsoil erosion, the mean sediment yield in the Upper Ouémé River outlet is expected to increase by 42 to 95% by 2025, depending on the land use scenario. In contrast, changes in climate variables led to decreases in sediment yield of 5 to 14% in 2001-2025 and 17 to 24% in 2026-2050. Combined scenarios showed the dominance of land use change leading to changes in mean sediment yield of -2 to +31% in 2001-2025. Scenario results vary considerably within the catchment. Current "hotspots" of soil erosion will aggravate, and a new "hotspot" will appear in the southern part of the catchment. Although only small parts of the Upper Ouémé catchment belong to the most degraded zones in the country, sustainable soil and plant management practices should be promoted in the entire catchment. The results of this study can support planning of soil conservation activities in Benin.

Modeled monthly local topographic lapse rates, Pacific Northwest, USA

An emerging approach to downscaling the projections from General Circulation Models (GCMs) to scales relevant for basin hydrology is to use output of GCMs to force higher-resolution Regional Climate Models (RCMs). With spatial resolution often in the tens of kilometers, however, even RCM output will likely fail to resolve local topography that may be climatically significant in high-relief basins. Here we develop and apply an approach for downscaling RCM output using local topographic lapse rates (empirically-estimated spatially and seasonally variable changes in climate variables with elevation). We calculate monthly local topographic lapse rates from the 800-m Parameter-elevation Regressions on Independent Slopes Model (PRISM) dataset, which is based on regressions of observed climate against topographic variables. We then use these lapse rates to elevationally correct two sources of regional climate-model output: (1) the North American Regional Reanalysis (NARR), a retrospective dataset produced from a regional forecasting model constrained by observations, and (2) a range of baseline climate scenarios from the North American Regional Climate Change Assessment Program (NARCCAP), which is produced by a series of RCMs driven by GCMs. By running a calibrated and validated hydrologic model, the Soil and Water Assessment Tool (SWAT), using observed station data and elevationally-adjusted NARR and NARCCAP output, we are able to estimate the sensitivity of hydrologic modeling to the source of the input climate data. Topographic correction of regional climate-model data is a promising method for modeling the hydrology of mountainous basins for which no weather station datasets are available or for simulating hydrology under past or future climates.

(Table 2) Lipid fluxes derived from sediment trap samples

Phytoplankton is a sentinel of marine ecosystem change. Composed by many species with different life-history strategies, it rapidly responds to environment changes. An analysis of the abundance of 54 phytoplankton species in Galicia (NW Spain) between 1989 and 2008 to determine the main components of temporal variability in relation to climate and upwelling showed that most of this variability was stochastic, as seasonality and long term trends contributed to relatively small fractions of the series. In general, trends appeared as non linear, and species clustered in 4 groups according to the trend pattern but there was no defined pattern for diatoms, dinoflagellates or other groups. While, in general, total abundance increased, no clear trend was found for 23 species, 14 species decreased, 4 species increased during the early 1990s, and only 13 species showed a general increase through the series. In contrast, series of local environmental conditions (temperature, stratification, nutrients) and climate-related variables (atmospheric pressure indices, upwelling winds) showed a high fraction of their variability in deterministic seasonality and trends. As a result, each species responded independently to environmental and climate variability, measured by generalized additive models. Most species showed a positive relationship with nutrient concentrations but only a few showed a direct relationship with stratification and upwelling. Climate variables had only measurable effects on some species but no common response emerged. Because its adaptation to frequent disturbances, phytoplankton communities in upwelling ecosystems appear less sensitive to changes in regional climate than other communities characterized by short and well defined productive periods.

Remote Sensing of Vegetation Change Across a Latitudinal Gradient in the Canadian Arctic

Global air surface temperatures and precipitation have increased over the last several decades resulting in a trend of greening across the Circumpolar Arctic. The spatial variability of warming and the inherent effects on plant communities has not proven to be uniform or homogeneous on global or local scales. We can apply remote sensing vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to map and monitor vegetation change (e.g., phenology, greening, percent cover, and biomass) over time. It is important to document how Arctic vegetation is changing, as it will have large implications related to global carbon and surface energy budgets. The research reported here examined vegetation greening across different spatial and temporal scales at two disparate Arctic sites: Apex River Watershed (ARW), Baffin Island, and Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU. To characterize the vegetation in the ARW, high spatial resolution WorldView-2 data were processed to create a supervised land-cover classification and model percent vegetation cover (PVC) (a similar process had been completed in a previous study for the CBAWO). Meanwhile, NDVI data spanning the past 30 years were derived from intermediate resolution Landsat data at the two Arctic sites. The land-cover classifications at both sites were used to examine the Landsat NDVI time series by vegetation class. Climate variables (i.e., temperature, precipitation and growing season length (GSL) were examined to explore the potential relationships of NDVI to climate warming. PVC was successfully modeled using high resolution data in the ARW. PVC and plant communities appear to reside along a moisture and altitudinal gradient. The NDVI time series demonstrated an overall significant increase in greening at the CBAWO (High Arctic site), specifically in the dry and mesic vegetation type. However, similar overall greening was not observed for the ARW (Low Arctic site). The overall increase in NDVI at the CBAWO was attributed to a significant increase in July temperatures, precipitation and GSL.