Monitoring the vegetation start of season (SOS) across the island of Ireland using the MERIS global vegetation index

The aim of this study was to develop a methodology, based on satellite remote sensing, to estimate the vegetation Start of Season (SOS) across the whole island of Ireland on an annual basis. This growing body of research is known as Land Surface Phenology (LSP) monitoring. The SOS was estimated for each year from a 7-year time series of 10-day composited, 1.2 km reduced resolution MERIS Global Vegetation Index (MGVI) data from 2003 to 2009, using the time series analysis software, TIMESAT. The selection of a 10-day composite period was guided by in-situ observations of leaf unfolding and cloud cover at representative point locations on the island. The MGVI time series was smoothed and the SOS metric extracted at a point corresponding to 20% of the seasonal MGVI amplitude. The SOS metric was extracted on a per pixel basis and gridded for national scale coverage. There were consistent spatial patterns in the SOS grids which were replicated on an annual basis and were qualitatively linked to variation in landcover. Analysis revealed that three statistically separable groups of CORINE Land Cover (CLC) classes could be derived from differences in the SOS, namely agricultural and forest land cover types, peat bogs, and natural and semi-natural vegetation types. These groups demonstrated that managed vegetation, e.g. pastures has a significantly earlier SOS than in unmanaged vegetation e.g. natural grasslands. There was also interannual spatio-temporal variability in the SOS. Such variability was highlighted in a series of anomaly grids showing variation from the 7-year mean SOS. An initial climate analysis indicated that an anomalously cold winter and spring in 2005/2006, linked to a negative North Atlantic Oscillation index value, delayed the 2006 SOS countrywide, while in other years the SOS anomalies showed more complex variation. A correlation study using air temperature as a climate variable revealed the spatial complexity of the air temperature-SOS relationship across the Republic of Ireland as the timing of maximum correlation varied from November to April depending on location. The SOS was found to occur earlier due to warmer winters in the Southeast while it was later with warmer winters in the Northwest. The inverse pattern emerged in the spatial patterns of the spring correlates. This contrasting pattern would appear to be linked to vegetation management as arable cropping is typically practiced in the southeast while there is mixed agriculture and mostly pastures to the west. Therefore, land use as well as air temperature appears to be an important determinant of national scale patterns in the SOS. The TIMESAT tool formed a crucial component of the estimation of SOS across the country in all seven years as it minimised the negative impact of noise and data dropouts in the MGVI time series by applying a smoothing algorithm. The extracted SOS metric was sensitive to temporal and spatial variation in land surface vegetation seasonality while the spatial patterns in the gridded SOS estimates aligned with those in landcover type. The methodology can be extended for a longer time series of FAPAR as MERIS will be replaced by the ESA Sentinel mission in 2013, while the availability of full resolution (300m) MERIS FAPAR and equivalent sensor products holds the possibility of monitoring finer scale seasonality variation. This study has shown the utility of the SOS metric as an indicator of spatiotemporal variability in vegetation phenology, as well as a correlate of other environmental variables such as air temperature. However, the satellite-based method is not seen as a replacement of ground-based observations, but rather as a complementary approach to studying vegetation phenology at the national scale. In future, the method can be extended to extract other metrics of the seasonal cycle in order to gain a more comprehensive view of seasonal vegetation development.

Is observed variability in the long-term results of the Continuous Plankton Recorder survey a response to climate change?

In the more than 50 years that the Continuous Plankton Recorder (CPR) survey has operated on a regular monthly basis in the north-east Atlantic and North Sea, large changes have been witnessed in the planktonic ecosystem. These changes have taken the form of long-term trends in abundance for certain species or stepwise changes for others, and in many cases are correlated with a mode of climatic variability in the North Atlantic, either: (1) the North Atlantic Oscillation (NAO), a basin-scale atmospheric alteration of the pressure field between the Azores high pressure cell and the Icelandic Low; or (2) the Gulf Stream Index (GSI), which measures the latitudinal position of the north wall of the Gulf Stream. Recent work has shown that the changes in the GSI are coupled with the NAO and Pacific Southern Oscillation with a 2 year lag. The plankton variability is also possibly linked to changes observed in the distribution and flux of water masses in the surface, intermediate and deep waters of the North Atlantic. For example, in the last two decades, the extent and location of the formation of North Atlantic Deep Water, Labrador Sea Intermediate Water and Norwegian Sea intermediate and upper-layer water has altered considerably. This paper discusses the extent to which observed changes in plankton abundance and distribution may be linked to this basin-scale variability in hydrodynamics. The results are also placed within the context of global climate warming and the possible effects of the observed melting of Arctic permafrost and sea ice on the subpolar North Atlantic.

North Atlantic climatic signals and the plankton of the European Continental Shelf

Climatic variability on the European Continental Shelf is dominated by events over the North Atlantic Ocean, and in particular by the North Atlantic Oscillation (NAO). The NAO is essentially a winter phenomenon, and its effects will be felt most strongly by populations for which winter conditions are critical. One example is the copepod Calanus finmarchicus, whose northern North Sea populations overwinter at depth in the North Atlantic. Its annual abundance in this region is strongly dependent on water transports at the end of the winter, and hence on the NAO index. Variations in the NAO give rise to changes in the circulation of the North Atlantic Ocean, with additional perturbations arising from El Ni (n) over tildeo - Southern Oscillation (ENSO) events in the Pacific, and these changes can be delayed by several years because of the adjustment time of the ocean circulation. One measure of the circulation is the latitude of the north wall of the Gulf Stream (GSNW index). Interannual variations in the plankton of the Shelf Seas show strong correlations with the fluctuations of the GSNW index, which are the result of Atlantic-wide atmospheric processes. These associations imply that the interannual variations are climatically induced rather than due to natural fluctuations of the marine ecosystem, and that the zooplankton populations have not been significantly affected by anthropogenic processes such as nutrient enrichment or fishing pressure. While the GSNW index represents a response to atmospheric changes over two or more years, the zooplankton populations correlated with it have generation times of a few weeks. The simplest explanation for the associations between the zooplankton and the GSNW index is that the plankton are responding to weather patterns propagating downstream from the Gulf Stream system. It seems that these meteorological processes operate in the spring. Although it has been suggested that there was a regime shift in the North Sea in the late 1980s, examination of the time-series by the cumulative sum (CUSUM) technique shows that any changes in the zooplankton of the central and northern North Sea are consistent with the background climatic variability. The abundance of total copepods increased during this period but this change does not represent a dramatic change in ecosystem processes. It is possible some change may have occurred at the end of the time-series in the years 1997 and 1998.

Coccolithophore surface distributions in the North Atlantic and their modulation of the air-sea flux of CO2 from 10 years of satellite Earth observation data

Coccolithophores are the primary oceanic phytoplankton responsible for the production of calcium carbonate (CaCO3). These climatically important plankton play a key role in the oceanic carbon cycle as a major contributor of carbon to the open ocean carbonate pump (similar to 50 %) and their calcification can affect the atmosphere-to-ocean (air-sea) uptake of carbon dioxide (CO2) through increasing the seawater partial pressure of CO2 (pCO(2)). Here we document variations in the areal extent of surface blooms of the globally important coccolithophore, Emiliania huxleyi, in the North Atlantic over a 10-year period (1998-2007), using Earth observation data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). We calculate the annual mean sea surface areal coverage of E. huxleyi in the North Atlantic to be 474 000 +/- 104 000 km(2), which results in a net CaCO3 carbon (CaCO3-C) production of 0.14-1.71 Tg CaCO3-C per year. However, this surface coverage (and, thus, net production) can fluctuate inter-annually by -54/+81% about the mean value and is strongly correlated with the El Nino/Southern Oscillation (ENSO) climate oscillation index (r = 0.75, p < 0.02). Our analysis evaluates the spatial extent over which the E. huxleyi blooms in the North Atlantic can increase the pCO(2) and, thus, decrease the localised air-sea flux of atmospheric CO2. In regions where the blooms are prevalent, the average reduction in the monthly air-sea CO2 flux can reach 55%. The maximum reduction of the monthly air-sea CO2 flux in the time series is 155 %. This work suggests that the high variability, frequency and distribution of these calcifying plankton and their impact on pCO(2) should be considered if we are to fully understand the variability of the North Atlantic air-to-sea flux of CO2. We estimate that these blooms can reduce the annual N. Atlantic net sink atmospheric CO2 by between 3-28 %.

Coccolithophore surface distributions in the North Atlantic and their modulation of the air-sea flux of CO2 from 10 years of satellite Earth observation data

Coccolithophores are the primary oceanic phytoplankton responsible for the production of calcium carbonate (CaCO3). These climatically important plankton play a key role in the oceanic carbon cycle as a major contributor of carbon to the open ocean 5 carbonate pump (�50%) and their formation can affect the atmosphere-to-ocean (airsea) uptake of carbon dioxide (CO2) through increasing the seawater partial pressure of CO2 (pCO2). Here we document variations in the areal extent of surface blooms of the globally important coccolithophore, Emiliania huxleyi, in the North Atlantic over a 10-year period (1998–2007), using Earth observation data from the Sea-viewing Wide 10 Field of view Sensor (SeaWiFS).We calculate the annual mean surface areal coverage of E. huxleyi in the North Atlantic to be 474 000±119 000km2 yr−1, which results in a net CaCO3 production of 0.62±0.15 Tg CaCO3 carbon per year. However, this surface coverage and net production can fluctuate by −54/+81% about these mean values and are strongly correlated with the El Ni˜no/Southern Oscillation (ENSO) climate os15 cillation index (r =0.75, p<0.02). Our analysis evaluates the spatial extent over which the E. huxleyi blooms in the North Atlantic can increase the pCO2 and thus decrease the localised sink of atmospheric CO2. In regions where the blooms are prevalent, the average reduction in the monthly CO2 sink can reach 12 %. The maximum reduction of the monthly CO2 sink in the time series is 32 %. This work suggests that the high 20 variability, frequency and distribution of these calcifying plankton and their impact on pCO2 should be considered within modelling studies of the North Atlantic if we are to fully understand the variability of its air-to-sea CO2 flux.

Identification of Putative Wintering Areas and Ecological Determinants of Population Dynamics of Common House-Martin (Delichon urbicum) and Common Swift (Apus apus) Breeding in Northern Italy

To identify the causes of population decline in migratory birds, researchers must determine the relative influence of environmental changes on population dynamics while the birds are on breeding grounds, wintering grounds, and en route between the two. This is problematic when the wintering areas of specific populations are unknown. Here, we first identified the putative wintering areas of Common House-Martin (Delichon urbicum) and Common Swift (Apus apus) populations breeding in northern Italy as those areas, within the wintering ranges of these species, where the winter Normalized Difference Vegetation Index (NDVI), which may affect winter survival, best predicted annual variation in population indices observed in the breeding grounds in 1992–2009. In these analyses, we controlled for the potentially confounding effects of rainfall in the breeding grounds during the previous year, which may affect reproductive success; the North Atlantic Oscillation Index (NAO), which may account for climatic conditions faced by birds during migration; and the linear and squared term of year, which account for nonlinear population trends. The areas thus identified ranged from Guinea to Nigeria for the Common House-Martin, and were located in southern Ghana for the Common Swift. We then regressed annual population indices on mean NDVI values in the putative wintering areas and on the other variables, and used Bayesian model averaging (BMA) and hierarchical partitioning (HP) of variance to assess their relative contribution to population dynamics. We re-ran all the analyses using NDVI values at different spatial scales, and consistently found that our population of Common House-Martin was primarily affected by spring rainfall (43%–47.7% explained variance) and NDVI (24%–26.9%), while the Common Swift population was primarily affected by the NDVI (22.7%–34.8%). Although these results must be further validated, currently they are the only hypotheses about the wintering grounds of the Italian populations of these species, as no Common House-Martin and Common Swift ringed in Italy have been recovered in their wintering ranges.

Effect of ENSO phase on large-scale snow water equivalent distribution in a GCM

Understanding links between the El Nino-Southern Oscillation (ENSO) and snow would be useful for seasonal forecasting, but also for understanding natural variability and interpreting climate change predictions. Here, a 545-year run of the general circulation model HadCM3, with prescribed external forcings and fixed greenhouse gas concentrations, is used to explore the impact of ENSO on snow water equivalent (SWE) anomalies. In North America, positive ENSO events reduce the mean SWE and skew the distribution towards lower values, and vice versa during negative ENSO events. This is associated with a dipole SWE anomaly structure, with anomalies of opposite sign centered in western Canada and the central United States. In Eurasia, warm episodes lead to a more positively skewed distribution and the mean SWE is raised. Again, the opposite effect is seen during cold episodes. In Eurasia the largest anomalies are concentrated in the Himalayas. These correlations with February SWE distribution are seen to exist from the previous June-July-August (JJA) ENSO index onwards, and are weakly detected in 50-year subsections of the control run, but only a shifted North American response can be detected in the anaylsis of 40 years of ERA40 reanalysis data. The ENSO signal in SWE from the long run could still contribute to regional predictions although it would be a weak indicator only

A new set of orthogonal patterns in weather and climate: Optimally interpolated patterns.

A new spectral-based approach is presented to find orthogonal patterns from gridded weather/climate data. The method is based on optimizing the interpolation error variance. The optimally interpolated patterns (OIP) are then given by the eigenvectors of the interpolation error covariance matrix, obtained using the cross-spectral matrix. The formulation of the approach is presented, and the application to low-dimension stochastic toy models and to various reanalyses datasets is performed. In particular, it is found that the lowest-frequency patterns correspond to largest eigenvalues, that is, variances, of the interpolation error matrix. The approach has been applied to the Northern Hemispheric (NH) and tropical sea level pressure (SLP) and to the Indian Ocean sea surface temperature (SST). Two main OIP patterns are found for the NH SLP representing respectively the North Atlantic Oscillation and the North Pacific pattern. The leading tropical SLP OIP represents the Southern Oscillation. For the Indian Ocean SST, the leading OIP pattern shows a tripole-like structure having one sign over the eastern and north- and southwestern parts and an opposite sign in the remaining parts of the basin. The pattern is also found to have a high lagged correlation with the Niño-3 index with 6-months lag.

On the long-term interannual variability of the east Asian winter monsoon

The East Asian Winter Monsoon (EAWM) and Siberian High (SH) are inherently related, based on prior studies of instrumental data available for recent decades (since 1958). Here we develop an extended instrumental EAWM index since 1871 that correlates significantly with the SH. These two indices show common modes of variation on the biennial (2-3 year) time scale. We also develop an index of the pressure gradient between the SH and the Aleutian Low, a gradient which critically impacts EAWM variability. This difference series, based on tree-ring reconstructions of the SH and the North Pacific Index (NPI) over the past 400 years, shows that the weakening of this gradient in recent decades has not been unusual in a long-term context. Correlations between the SH series and a tree-ring reconstruction of the El Nino-Southern Oscillation (ENSO) suggest a variable tropical-higher latitude teleconnection.

Northern hemisphere snow: measurement, modelling and predictability

Northern hemisphere snow water equivalent (SWE) distribution from remote sensing (SSM/I), the ERA40 reanalysis product and the HadCM3 general circulation model are compared. Large differences are seen in the February climatologies, particularly over Siberia. The SSM/I retrieval algorithm may be overestimating SWE in this region, while comparison with independent runoff estimates suggest that HadCM3 is underestimating SWE. Treatment of snow grain size and vegetation parameterizations are concerns with the remotely sensed data. For this reason, ERA40 is used as `truth' for the following experiments. Despite the climatology differences, HadCM3 is able to reproduce the distribution of ERA40 SWE anomalies when assimilating ERA40 anomaly fields of temperature, sea level pressure, atmospheric winds and ocean temperature and salinity. However when forecasts are released from these assimilated initial states, the SWE anomaly distribution diverges rapidly from that of ERA40. No predictability is seen from one season to another. Strong links between European SWE distribution and the North Atlantic Oscillation (NAO) are seen, but forecasts of this index by the assimilation scheme are poor. Longer term relationships between SWE and the NAO, and SWE and the El Ni\~no-Southern Oscillation (ENSO) are also investigated in a multi-century run of HadCM3. SWE is impacted by ENSO in the Himalayas and North America, while the NAO affects SWE in North America and Europe. While significant connections with the NAO index were only present in DJF (and to an extent SON), the link between ENSO and February SWE distribution was seen to exist from the previous JJA ENSO index onwards. This represents a long lead time for SWE prediction for hydrological applications such as flood and wildfire forecasting. Further work is required to develop reliable large scale observation-based SWE datasets with which to test these model-derived connections.

Potential role of the quasi-biennial oscillation in the stratosphere-troposphere exchange as found in water vapor in general circulation model experiments

The tropical tropopause is considered to be the main region of upward transport of tropospheric air carrying water vapor and other tracers to the tropical stratosphere. The lower tropical stratosphere is also the region where the quasi-biennial oscillation (QBO) in the zonal wind is observed. The QBO is positioned in the region where the upward transport of tropospheric tracers to the overworld takes place. Hence the QBO can in principle modulate these transports by its secondary meridional circulation. This modulation is investigated in this study by an analysis of general circulation model (GCM) experiments with an assimilated QBO. The experiments show, first, that the temperature signal of the QBO modifies the specific humidity in the air transported upward and, second, that the secondary meridional circulation modulates the velocity of the upward transport. Thus during the eastward phase of the QBO the upward moving air is moister and the upward velocity is less than during the westward phase of the QBO. It was further found that the QBO period is too short to allow an equilibration of the moisture in the QBO region. This causes a QBO signal of the moisture which is considerably smaller than what could be obtained in the limiting case of indefinitely long QBO phases. This also allows a high sensitivity of the mean moisture over a QBO cycle to the El Niño-Southern Oscillation (ENSO) phenomena or major tropical volcanic eruptions. The interplay of sporadic volcanic eruptions, ENSO, and QBO can produce low-frequency variability in the water vapor content of the tropical stratosphere, which renders the isolation of the QBO signal in observational data of water vapor in the equatorial lower stratosphere difficult.

Sea-surface temperature records of Termination 1 in the Gulf of California: Challenges for seasonal and interannual analogues of tropical Pacific climate change

Centennial-scale records of sea-surface temperature and opal composition spanning the Last Glacial Maximum and Termination 1 (circa 25–6 ka) are presented here from Guaymas Basin in the Gulf of California. Through the application of two organic geochemistry proxies, the U37K′ index and the TEX86H index, we present evidence for rapid, stepped changes in temperatures during deglaciation. These occur in both temperature proxies at 13 ka (∼3°C increase in 270 years), 10.0 ka (∼2°C decrease over ∼250 years) and at 8.2 ka (3°C increase in <200 years). An additional rapid warming step is also observed in TEX86H at 11.5 ka. In comparing the two temperature proxies and opal content, we consider the potential for upwelling intensity to be recorded and link this millennial-scale variability to shifting Intertropical Convergence Zone position and variations in the strength of the Subtropical High. The onset of the deglacial warming from 17 to 18 ka is comparable to a “southern hemisphere” signal, although the opal record mimics the ice-rafting events of the north Atlantic (Heinrich events). Neither the modern seasonal cycle nor El Niño/Southern Oscillation patterns provide valid analogues for the trends we observe in comparison with other regional records. Fully coupled climate model simulations confirm this result, and in combination we question whether the seasonal or interannual climate variations of the modern climate are valid analogues for the glacial and deglacial tropical Pacific.

High-latitude influence of the quasi-biennial oscillation

The interannual variability of the stratospheric winter polar vortex is correlated with the phase of the quasi-biennial oscillation (QBO) of tropical stratospheric winds. This dynamical coupling between high and low latitudes, often referred to as the Holton–Tan effect, has been the subject of numerous observational and modelling studies, yet important questions regarding its mechanism remain unanswered. In particular it remains unclear which vertical levels of the QBO exert the strongest influence on the winter polar vortex, and how QBO–vortex coupling interacts with the effects of other sources of atmospheric interannual variability such as the 11-year solar cycle or the El Nino Southern Oscillation. As stratosphere-resolving general circulation models begin to resolve the QBO and represent its teleconnections with other parts of the climate system, it seems timely to summarize what is currently known about the QBO’s high-latitude influence. In this review article, we offer a synthesis of the modelling and observational analyses of QBO–vortex coupling that have appeared in the literature, and update the observational record.

Cloud banding and winds in intense European cyclones: results from the DIAMET project

The DIAMET (DIAbatic influences on Mesoscale structures in ExTratropical storms) project aims to improve forecasts of high-impact weather in extratropical cyclones through field measurements, high-resolution numerical modeling, and improved design of ensemble forecasting and data assimilation systems. This article introduces DIAMET and presents some of the first results. Four field campaigns were conducted by the project, one of which, in late 2011, coincided with an exceptionally stormy period marked by an unusually strong, zonal North Atlantic jet stream and a succession of severe windstorms in northwest Europe. As a result, December 2011 had the highest monthly North Atlantic Oscillation index (2.52) of any December in the last 60 years. Detailed observations of several of these storms were gathered using the UK’s BAe146 research aircraft and extensive ground-based measurements. As an example of the results obtained during the campaign, observations are presented of cyclone Friedhelm on 8 December 2011, when surface winds with gusts exceeding 30 m s-1 crossed central Scotland, leading to widespread disruption to transportation and electricity supply. Friedhelm deepened 44 hPa in 24 hours and developed a pronounced bent-back front wrapping around the storm center. The strongest winds at 850 hPa and the surface occurred in the southern quadrant of the storm, and detailed measurements showed these to be most intense in clear air between bands of showers. High-resolution ensemble forecasts from the Met Office showed similar features, with the strongest winds aligned in linear swaths between the bands, suggesting that there is potential for improved skill in forecasts of damaging winds.

Modulation of equatorial Pacific westerly/easterly wind events by the Madden-Julian oscillation and convectively-coupled Rossby waves

Synoptic wind events in the equatorial Pacific strongly influence the El Niño/Southern Oscillation (ENSO) evolution. This paper characterizes the spatio-temporal distribution of Easterly (EWEs) and Westerly Wind Events (WWEs) and quantifies their relationship with intraseasonal and interannual large-scale climate variability. We unambiguously demonstrate that the Madden–Julian Oscillation (MJO) and Convectively-coupled Rossby Waves (CRW) modulate both WWEs and EWEs occurrence probability. 86 % of WWEs occur within convective MJO and/or CRW phases and 83 % of EWEs occur within the suppressed phase of MJO and/or CRW. 41 % of WWEs and 26 % of EWEs are in particular associated with the combined occurrence of a CRW/MJO, far more than what would be expected from a random distribution (3 %). Wind events embedded within MJO phases also have a stronger impact on the ocean, due to a tendency to have a larger amplitude, zonal extent and longer duration. These findings are robust irrespective of the wind events and MJO/CRW detection methods. While WWEs and EWEs behave rather symmetrically with respect to MJO/CRW activity, the impact of ENSO on wind events is asymmetrical. The WWEs occurrence probability indeed increases when the warm pool is displaced eastward during El Niño events, an increase that can partly be related to interannual modulation of the MJO/CRW activity in the western Pacific. On the other hand, the EWEs modulation by ENSO is less robust, and strongly depends on the wind event detection method. The consequences of these results for ENSO predictability are discussed.