M Rouault

B Pohl

P Penven

Coastal oceanic climate change and variability from 1982 to 2009 around South Africa

Keywords: Agulhas Current, Benguela upwelling, climate change, ENSO, Southern Annular Mode

Changes and fluctuations in sea surface temperature (SST) around the South African coast are analysed at a monthly scale from 1982 to 2009. There is a statistically significant negative trend of up to 0.5 °C per decade in the southern Benguela from January to August, and a cooling trend of lesser magnitude along the South Coast and in the Port Elizabeth/Port Alfred region from May to August. The cooling is due to an increase in upwellingfavourable south-easterly and easterly winds. There is a positive trend in SST of up to 0.55 °C per decade in most parts of the Agulhas Current system during all months of the year, except for KwaZulu-Natal where warming is in summer. The warming was attrib-uted to an intensification of the Agulhas Current in response to a poleward shift of westerly winds and an increase in trade winds in the South Indian Ocean at relevant latitudes. This intensification of the Agulhas Current could also have contributed to the coastal cooling in the Port Alfred dynamic upwelling region. The El Niño Southern Oscillation (ENSO) is significantly positively correlated at a 95% level with the southern Benguela and South Coast from February to May, and negatively correlated with the Agulhas Current system south of 36° S. The correlation with the Antarctic Annular Oscillation is weaker and less coherent. El Niño suppresses upwelling along the coast, whereas La Niña increases it. Although there does not seem to be a linear relationship between the strength of the ENSO and the magnitude of coastal SST perturbation, El Niño and La Niña appear to be linked to major warm and cool events, respectively, at a seasonal scale in summer in the southern Benguela and along the South Coast. However, care must be taken in interpreting lowresolution reanalysed climate data (ERA40 and NCEP) and optimally interpolated Reynolds SST, such as used here.

Introduction

The Intergovernmental Panel on Climate Change [START_REF] Ipcc | Climate change 2007. The physical science basis[END_REF] confirmed the anthropogenic footprint on global land and sea surface temperature (SST). Questions remain, though, about future climate at a regional scale in a world where CO 2 , methane and other gases continue to rise and to what extent anthropogenic climate change has already taken place at a regional scale. The subject is complicated because an anthropogenic effect is superimposed on natural climate variability. For instance, a change in the Pacific since the mid-1970s [START_REF] Trenberth | Recent observed interdecadal climate changes in the northern hemisphere[END_REF]) and a related global climate shift does not seem to have been stimulated by an anthropogenic effect, but it did have a huge impact on world climate. Interannual changes in Pacific Ocean SST modify the weather pattern worldwide and have a strong impact on southern African summer rainfall and associated atmospheric circulation [START_REF] Fauchereau | Rainfall variability and changes in southern Africa during the 20th century in the global warming context[END_REF], 2009, Pohl et al. 2009, 2010).

Regionally, the El Niño Southern Oscillation (ENSO) influences SST in the South Atlantic [START_REF] Colberg | South Atlantic response to ENSO induced climate variability in an OGCM[END_REF]).

The relationship between the ENSO and southern African rainfall is not linear, but the correlation between rainfall anomalies and SST in the Pacific is statistically significant [START_REF] Fauchereau | Rainfall variability and changes in southern Africa during the 20th century in the global warming context[END_REF], notably so since the 1970s [START_REF] Richard | Modification of the southern African rainfall variability/ENSO relationship since the late 1960s[END_REF][START_REF] Richard | 20th century droughts in southern Africa: spatial and temporal variability, teleconnections with oceanic and atmospheric conditions[END_REF]. Most of the severe droughts have happened during the mature phase of El Niño and the wettest summers during La Niña (Rouault andRichard 2003, 2005). At an interannual time-scale, the Antarctic Annular Oscillation (AAO) has an influence on South Africa's Western Cape rainfall in winter [START_REF] Reason | Links between the Antarctic Oscillation and winter rainfall over southwestern South Africa[END_REF]. The AAO, sometimes referred to as the Southern Annular Mode (SAM), is the leading mode of atmospheric variability in the Southern Hemisphere high latitudes (Thompson and Wallace 2000). Mid-latitude westerly winds and the subtropical high-level jet tend to be shifted towards or away from the pole during opposite phases of the AAO. Change in the AAO from austral spring to autumn was linked to significant change in Marion Island climate by Rouault et al. (2005) for the period 1960-2000 owing to a poleward shift of westerly wind. Although a lot of research has dealt with the impact of ENSO on southern African summer rainfall (see [START_REF] Reason | A review of South African research in atmospheric science and physical oceanography during 2000-2005[END_REF] for a review of recent work), less has been done to study the effect of ENSO on the coastal sea surface. Only [START_REF] Agenbag | Pacific ENSO events reflected in meteorological and oceanographic perturbations in the southern Benguela system[END_REF] mentioned a potential influence of the 1992 El Niño event on abnormal warming in SST around the Cape Peninsula. Here, we use 28 years of satellite remote sensing estimates of SST and in situ observations to address the issue, by reanalysing climate datasets to relate changes to corresponding atmospheric conditions, and presenting 1982-2009 trends in SST and time-series of monthly anomalies for five coastal regions around South Africa and the Agulhas Current system south of 36° S. The relationship between SST, ENSO and the AAO, i.e. two major modes of climate variability, is addressed. Observed changes in atmospheric condition are presented to explain the observed trends in SST. Finally, a word of caution is aired on the use of low resolution reanalysed climate and SST global data for regional analysis.

Data

We used 1° × 1° resolution optimally interpolated SST (Reynolds SST;[START_REF] Reynolds | An improved in situ and satellite SST analysis for climate[END_REF]. Reynolds SST is derived from daily merged, in situ, high-resolution (9 km) infrared satellite observations from the AVHRR (advanced very high resolution radiometer) instrument on board NOAA (National Oceanic and Atmospheric Administration) satellites. It has been used successfully in southern Africa to represent coastal SST, for instance in describing the 1999/2000 extreme oceanographic event in the southern Benguela [START_REF] Roy | Extreme oceanographic events recorded in the southern Benguela during the 1999-2000 summer season[END_REF]) and Benguela Niños (Rouault et al. 2003a). Those successes were attributable to the offshore and alongshore extent of those severe perturbations. Rouault and Lutjeharms (2003) and Rouault et al. (2003b) showed that even if the Reynolds SST does not represent accurately all features of the Agulhas Current system or coastal area because of the resolution of the data and the interpolation scheme, it can be used satisfactorily when averaged over a large domain. National Center for Environmental Prediction (NCEP) reanalysis data [START_REF] Kalnay | The NCEP/NCAR, 40-year reanalysis project[END_REF] are used to assess circulation changes associated with ENSO and linear trends. Here, we utilise the NCEP data with a monthly time-resolution and a spatial resolution of 2.5° latitude × 2.5° longitude. Note that the spatial resolution of these reanalysed data does not resolve the upwelling region. However, for the purpose of analysing large-scale circulation anomalies over the South Atlantic-Africa-South Indian Ocean region, NCEP resolution is adequate. We use the AVISO (Archiving, Validation and Interpretation of Satellite Oceanographic data) mean dynamic topography [START_REF] Rio | The estimation of the ocean Mean Dynamic Topography through the combination of altimetric data, in-situ measurements and GRACE geoid: from global to regional studies[END_REF] and associated data on mean geostrophic currents derived from altimetry, observations and a model. Rainfall was obtained from a 1° × 1° resolution GPCC (Global Precipitation Climatology Center; [START_REF] Schneider | Global precipitation analysis products of the GPCC[END_REF] dataset derived from land observations.

Results

Figure 1 shows the domain used for the time-series analyses. The regions we studied were: (1) West Coast, (2) South Coast,

(3) Port Elizabeth/Port Alfred, (4) Transkei and (5) KwaZulu-Natal. Each coastal time-series is derived by averaging data in a domain 3° wide along the coast and extending 1° offshore, so that they have approximately the same size. We also used a region (6) encompassing the Agulhas Current system averaged from 36° to 42° S and from 15° to 30° E. The Reynolds SST data use high-resolution morning and evening AVHRR satellite estimates and all available observations. Figure 2 shows the linear trend in SST using 1° × 1° resolution Reynolds SST from 1982 to 2007. Superimposed is the mean 1993-2007 absolute geostrophic current vector derived from merged altimetry [START_REF] Rio | The estimation of the ocean Mean Dynamic Topography through the combination of altimetric data, in-situ measurements and GRACE geoid: from global to regional studies[END_REF]. Figure 2 also shows the main features of the Agulhas Current system. The main loop is south of the continent, and the retroflection located in the domain delimited by the area 10°-20° E and 37°-42° S. Eddies shed from the Agulhas Current are usually formed in the retroflection area and move mostly in a north-west direction towards Brazil. The Agulhas Return Current flows eastwards and meanders. The Agulhas Current system has warmed by up to 1.5 °C since the 1980s, argued by [START_REF] Rouault | Warming of the Agulhas Current since the 1980s[END_REF] to have resulted from an intensification of the Agulhas Current system in response to an augmentation of wind-stress curl in the South Indian Ocean. The increase in the wind stress itself is attributable to an increase in trade winds and a poleward shift in the westerly wind at the relevant latitude.

A regional ocean model [START_REF] Penven | Madagascar: a pacemaker for the Agulhas Current system[END_REF]), able to reproduce the observed SST relatively well, was used to derive quantities such as transport, fluxes of heat and salt, and temperature trends at depth. It showed that the transport of the Agulhas Current system has increased since the 1980s, leading to the warming. Coastal cooling of up to 0.55 °C per decade is also apparent (Figure 2), mainly along South Africa's west coast. Changes have been of lesser magnitude along the South Coast (from Cape Agulhas to Cape St Francis), as well as in the dynamic upwelling cell around Port Elizabeth/Port Alfred. The cooling in the west of the country is continuous from Cape Agulhas to the Namibian (2009) showed that this cooling is actually as strong as West Coast upwelling and spreads into the Agulhas Current itself and to the west. They argue that this could be the result of an intensification of the Agulhas Current that could have increased the dynamic upwelling and advected colder upwelled water offshore, although an increase in coastal upwelling-favourable winds could also be a factor [START_REF] Rouault | The Agulhas Current Air-Sea Exchange Experiment[END_REF][START_REF] Rouault | Observations of the atmospheric boundary layer above the Agulhas Current during along current winds[END_REF]. Next, we looked at SST linear trends in the five coastal regions around South Africa and in the Agulhas Current system. Figure 3 shows the 1982-2009 trends for all months of the year in the six regions defined. Although a bit short to study a trend, this series still represents changes over a 28-year period. There is a negative trend of up to -0.55 °C per decade for the West Coast from January to August, up to -0.35 °C per decade for the South Coast from May to August, and up to -0.4 °C per decade for Port Elizabeth/ Port Alfred, mostly from May to August. There is no change for the months September-December for all three regions, and no change in summer for either the South Coast or Port Elizabeth/Port Alfred. A warming of up to 0.55 °C per decade is observed in the Transkei domain and for the Agulhas Current for all months of the year, but little change in the KwaZulu-Natal domain except for a statistically significant trend of up to 0.25 °C per decade from December to February. Change in the Agulhas Current system is more marked in the retroflection area itself, and decreases to the east (Figure 2). The winter change is the most robust signal across the region, with cooling for the West Coast, the South Coast and Port Elizabeth/Port Alfred, and warming for the Agulhas Current system to the south.

We then investigated interannual variability of the system using the monthly anomaly from the climatology. Monthly anomalies divided by the standard deviation for that month for the six regions are presented in Figure 4 for all regions to characterise abnormal events, as well as their strength and duration. Major events lasted a few months and started mainly in summer. There were major warm events in 1983, 1986, 1987, 1992, 1993, 1994, 2003 and 2007. Most of these were El Niño years. They were simultaneous in the West Coast, the South Coast and Port Elizabeth/Port Alfred, at various degrees of severity. Major cooling events were in 1989, 1996, 1997, 2000 and 2006, most We note too that there was no major rainfall or regional climate anomaly in summer 1997/1998, a strong El Niño year in South Africa (Rouault andRichard 2003, 2005).

The cross-correlation between monthly SST anomalies for the various regions is shown in Table 1. It confirms the common variability of the regions that was also present in SST trends and anomalies. Similar results are obtained with detrended data. SST anomalies at a monthly scale are positively and significantly correlated for the West Coast and the South Coast, the West Coast and Port Elizabeth/ Port Alfred, the South Coast and Port Elizabeth/Port Alfred, KwaZulu-Natal and Transkei, Transkei and the Agulhas Current system, and KwaZulu-Natal and the Agulhas Current system. The only adjacent regions not significantly correlated are Port Elizabeth/Port Alfred and Transkei but this could be due to the coarse resolution SST data used here. The Agulhas Current system and Transkei are negatively and significantly correlated with the West Coast. The correlation between the South Coast and the West Coast or between other adjacent domains can be attributed to a variety of factors, bearing in mind that all regions are dwarfed by the weather systems that affect them. Low-pressure systems move from west to east, generating north-westerly, westerly, and south-westerly winds, and connect all the regions. Likewise, high-pressure systems can influence several regions concurrently. For instance, during high-pressure conditions, strong south-easterly wind along the West Coast can occur concurrently with strong easterly wind along the South Coast or farther east. Prolonged periods with more or less of the above will suppress or favour upwelling, modify the net heat budget at the sea surface (i.e. latent and sensible heat fluxes and the radiative budget), and Ekman pumping. The latent and sensible heat fluxes are high in the Agulhas Current system, and the presence of clouds further reduces the short-wave radiative flux into the ocean [START_REF] Rouault | Observations of the atmospheric boundary layer above the Agulhas Current during along current winds[END_REF](Rouault et al. , 2003b)). Remote forcing of a South Coast upwelling event through Kelvin waves generated during a West Coast upwelling event [START_REF] Crépon | Transient upwelling generated by two-dimensional atmospheric forcing and variability in the coastline[END_REF] could also be a factor.

Correlation with the ENSO using the multivariate ENSO index (MEI; [START_REF] Wolter | Monitoring ENSO in COADS with a seasonally adjusted principal component index[END_REF] provided by the Climate Diagnostic Center (http://www.cdc.noaa.gov), along with SST anomalies of the six regions defined above, are presented for all months of the year in Figure 5 between ENSO strength and the strength of the climatic perturbation, and also that the ENSO sometimes does not affect the region. This actually reduces the value of the correlation between ENSO and SST or rainfall. The relationship between coastal wind and the ENSO is illustrated in Figure 7. are 1983, 1987, 1988, 1992[START_REF] Rouault | The Agulhas Current Air-Sea Exchange Experiment[END_REF], 2003and 2007, and La Niña years are 1985, 1989[START_REF] Agenbag | Pacific ENSO events reflected in meteorological and oceanographic perturbations in the southern Benguela system[END_REF]1999, 2000, 2006and 2008. Mean wind speed along the coasts of South Africa at that time of year is south-easterly along the West Coast and easterly along the South Coast. A north-westerly anomaly means that wind speed is weaker than normal and a southeasterly anomaly that the wind is stronger than normal. Although the resolution of the wind data is not totally able to describe coastal wind speed, weaker (stronger) upwellingfavourable wind is present during El Niño (La Niña), and this explains the SST anomaly during ENSO. This pattern is due to a change in large-scale atmospheric circulation during El Niño or La Niña [START_REF] Richard | Modification of the southern African rainfall variability/ENSO relationship since the late 1960s[END_REF], 2001[START_REF] Colberg | South Atlantic response to ENSO induced climate variability in an OGCM[END_REF], Fauchereau et al. 2003, 2009, Pohl et al. 2009). Figure 8 shows the correlation between the mean of March and April rainfall-normalised anomalies and the West Coast normalised SST from 1982 to 2007. Rainfall was obtained from the 1° × 1° resolution GPCC [START_REF] Schneider | Global precipitation analysis products of the GPCC[END_REF] dataset derived from land observations. The correlation between rainfall anomaly and SST anomaly is negative and plotted for values between 0.6 and 0.4. Cooler (warmer) than normal SST at the West Coast is recorded when rainfall is above (below) normal inland, and vice versa. When rainfall is greater than normal, this favours lower atmospheric pressure above the continent and increases the pressure gradient between the continent and the ocean, so increasing upwelling-favourable wind. The opposite happens when rainfall is lower than normal and higher than normal pressure is above the continent. This could add to the effect of largescale perturbation in atmospheric circulation associated with the ENSO.

1 0 -1 -2 2 1 0 -1 -2 2 1 0 -1 -2 2 1 0 -1 -2 2 1 0 -1 -2 2 1 0 -1 South Coast West Coast Port Elizabeth Transkei KwaZulu-Natal Agulhas Current system
Correlation between the AAO Index and SST anomalies for the six regions defined are presented for all months of the year in Figure 9. The AAO index is obtained as the leading principal component of an extended orthogonal function (EOF) analysis applied to the 700 hPa geopotential height anomaly field south of 20° S, after removal of the annual cycle, and for the period 1979-2006. Each grid point was previously scaled by the square root of the cosine of its latitude. A positive (negative) phase of the AAO index corresponds to above-(below-) average surface pressure over the Southern Ocean and below-(above-) average pressure over Antarctica. The correlations between the AAO and the SST time-series is less coherent than that found for the ENSO. The absence of coherent correlation between the AAO and the Agulhas Current system, especially in winter, questions the validity of the influence of the AAO on the region at an interannual scale. West Coast SST is correlated with a positive phase of the AAO in winter. The correlation is less significant for the South Coast and absent for Port Elizabeth/Port Alfred. The correlation in summer is to be recorded with caution. A recent study [START_REF] Pohl | Relationships between the Antarctic Oscillation, the Madden-Julian Oscillation and ENSO, and consequences for rainfall analysis[END_REF] shows that the significance of the teleconnections between South African rainfall in summer and the AAO is a statistical artefact and weaker once the influence of the ENSO is removed. Indeed, partial correlations between the AAO and SST anomalies with the ENSO effect removed for the six regions in a similar fashion as done by [START_REF] Pohl | Relationships between the Antarctic Oscillation, the Madden-Julian Oscillation and ENSO, and consequences for rainfall analysis[END_REF] further reduce the former correlation (data not shown).

Figure 10 shows the linear trend in NCEP surface wind speed in the region from 1982 to 2009. ERA40 data are only available up to 2001, but show similar trends (supplementary material in [START_REF] Rouault | Warming of the Agulhas Current since the 1980s[END_REF]) of surface wind speed increasing in the South Atlantic and Indian Ocean subtropics. It is a consequence of an increase in sea level pressure in both the South Atlantic and the South Indian oceans (supplementary material in [START_REF] Rouault | Warming of the Agulhas Current since the 1980s[END_REF]. The observed change in sea level pressure and wind speed is consistent with a poleward shift of the westerly wind in the Southern Hemisphere and an increase in the South Atlantic and South Indian Ocean high pressure systems described by others [START_REF] Thompson | Interpretation of recent southern hemisphere climate change[END_REF][START_REF] Gillett | Detection of human influence on sea-level pressure[END_REF][START_REF] Chen | Phase speed spectra and the recent poleward shift of Southern Hemisphere surface westerlies[END_REF][START_REF] Seidel | Widening of the tropical belt in a changing climate[END_REF].

Discussion and conclusions

Caution needs to be exercised when using ERA40 or NCEP data at a regional scale for calculating the trend. For instance, ERA40 data show a decrease in wind speed off Angola and Namibia (supplementary material in Rouault et al. 2009), whereas NCEP data show an increase (Figure 10). There is up to a 20% difference between climatological mean regional surface wind speed data between ERA40 and the NCEP for the same period of 1979-2001 (data not shown), for instance for Angola and for the Southern Ocean. Another caveat to interpretation is that small oceanic features are not present in the Reynolds SST because of its resolution, the interpolation scheme used and the utilisation of AVHRR not allowing sampling in cloudy conditions or in conditions of intense glare from the sun. The core of the Agulhas Current is not present (Rouault et al. 2003a), and The most obvious change in the region is the warming of the Agulhas Current system as a consequence of intensification of the Agulhas Current system. Warming is stronger to the west of the domain defined here. The West Coast and the South Coast show a wind-related cooling pattern from January to August that seems to be triggered by intensification of the high pressure system in the South Atlantic. There is also cooling in the Port Elizabeth/Port Alfred system that could be caused by a combination of increased upwelling-favourable wind and intensification of the Agulhas Current. Clearly, however, the ENSO appears to be an important driver of interannual variability in SST in austral summer and autumn.

Figure 1 :

 1 Figure 1: The domains used in the study. The Reynolds SST is averaged in each of the domains to construct monthly time-series,

Figure 2 :

 2 Figure 2: Linear trend of 1° × 1° resolution Reynolds SST, 1985-2009. Mean AVISO absolute geostrophic velocity vectors derived from the mean dynamic topography (Rio et al. 2005) are superimposed

Figure 4 :

 4 Figure 4: Detrended normalised anomaly from the monthly mean, 1982-2009, using the Reynolds SST for the West Coast, South Coast, Port Elizabeth/Port Alfred, Transkei, KwaZulu-Natal and Agulhas Current system (36°-42° S, 10°-35° E)

Figure 5 :Figure 6 :

 56 Figure 5: Correlation between the ENSO (MEI index) and the Reynolds SST normalised anomalies for the West Coast, South Coast, Port Elizabeth/Port Alfred, Transkei, KwaZulu-Natal and the Agulhas Current system (36°-42° S and from 10°-35° E). Statistically significant correlations are marked with dashed lines

Figure 7

 7 Figure 7 is a composite of surface wind speed vector anomalies during La Niña and El Niño in the austral summer. The composites were constructed by averaging the 2.5° × 2.5° resolution NCEP surface wind speed for seven El Niño and seven La Niña events in January, February and March, and subtracting the equivalent climatological mean at the same time of year from 1979 to 2008. El Niño yearsare 1983, 1987, 1988, 1992[START_REF] Rouault | The Agulhas Current Air-Sea Exchange Experiment[END_REF], 2003 and 2007, and La Niña years are 1985, 1989[START_REF] Agenbag | Pacific ENSO events reflected in meteorological and oceanographic perturbations in the southern Benguela system[END_REF] 1999, 2000, 2006 and 2008. Mean wind speed along the coasts of South Africa at that time of year is south-easterly along the West Coast and easterly along the South Coast. A north-westerly anomaly means that wind speed is weaker than normal and a southeasterly anomaly that the wind is stronger than normal. Although the resolution of the wind data is not totally able to describe coastal wind speed, weaker (stronger) upwellingfavourable wind is present during El Niño (La Niña), and this

Figure 8 :Figure 7 :

 87 Figure 8: Correlation between the late austral summer (mean of March and April) GPCC rainfall-normalised anomaly and the West Coast SST-normalised anomaly, 1982-2007

MONTHFigure 9 :

 9 Figure 9: Correlation between the AAO index and Reynolds SST normalised anomalies for the West Coast, South Coast, Port Elizabeth/Port Alfred, Transkei, KwaZulu-Natal and the Agulhas Current system (36°-42° S, 10°-35° E). Statistically significant correlations are marked with dashed lines

Figure 10 :

 10 Figure 10: NCEP 1982-2009 linear trend in surface wind speed superimposed with the climatological mean direction (arrows)

  . The MEI,

			West Coast			South Coast
		0.4 2
		0.2
		0.0 -2
		-0.2
		-0.4
	SST TREND (°C per decade) STANDARD DEVIATION	0.4 0.2 0.0 -0.4 -0.2	Port Elizabeth/Port Alfred KwaZulu-Natal			Transkei Agulhas Current
		0.4
		0.2
		0.0
		-0.2
		-0.4
			JFMAMJ	JA	SONDJFMAMJ	JA	SOND
						MONTH
		1983 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09
	Figure 3: Linear trend in temperature per decade for each month of the year derived using the Reynolds SST, 1982-2009, for the West YEAR
	Coast, South Coast, Port Elizabeth/Port Alfred, Transkei, KwaZulu-Natal and the Agulhas Current system domains. Asterisks denote
	statistically significant trends at the 95% level according to Spearman's rank correlation
	based on both atmospheric and oceanic fields, describes the	the same period of the year as for the West Coast and the
	coupled nature of the ENSO phenomenon. The index does	South Coast. There is also a coherent negative correlation
	not show any trend towards more of an El Niño or a La Niña	between the Agulhas Current system domain that is almost

state. Significant correlation at a 95% level according to a Bravais-Pearson test is indicated with a dashed line. The correlation is significantly positive (El Niños relate to warmerthan-normal SST, La Niña to cooler SST) mainly from February to May for the West Coast and the South Coast, but it could also be a factor in early summer. Correlation is not significant for Port Elizabeth/Port Alfred, but there are some indications of a modulation of SST by the ENSO during a mirror image of the correlation between the ENSO and the West Coast. There is no correlation for Transkei, and an opposite sign correlation in the KwaZulu-Natal domain.

In Figure

6

, anomalies from climatology for the means of February, March and April are plotted from 1982 to 2008 for the West Coast. There is a clear indication that most, but not all, warm events relate to El Niño and most cold ones to La Niña. Figure

6

indicates that there is no linear relationship

Table 1 :

 1 Correlation between normalised anomalies SST of the six regions. Significant correlation at the 95% level is shown emboldened

	Domain	West Coast	South Coast	PE/PA	Transkei	KZN	Agulhas
	West Coast South Coast	1.00	0.68 1.00	0.53 0.79	-0.38 -0.06	-0.04 0.21	-0.31 0.08
	Port Elizabeth/Port Alfred			1.00	0.10	0.36	0.08
	Transkei				1.00	0.80	0.67
	KwaZulu-Natal					1.00	0.31
	Agulhas Current system						1.00

Acknowledgements -Funding for this work was provided by WRC, ACCESS, NRF, IRD, Nansen-Tutu Center and CNRS (PICS PESOCA), and we thank Aviso, NOAA, UKMO, ECMWF and NCEP for data. This manuscript is a contribution to the SEACHANGE NRF programme, the ACCESS climate programme and the ACDI programme.


Alpha T N'diaye
email: ndiaye@ph2.uni-koeln.de

Timm Gerber

Carsten Busse

Josef Mysliveček

Johann Coraux

Thomas Michely

A versatile fabrication method for cluster superlattices

On the graphene moiré on Ir(111) a variety of highly perfect cluster superlattices can be grown as shown is for Ir, Pt, W, and Re. Even materials that do not form cluster superlattices upon room temperature deposition may be grown into such by low temperature deposition or the application of cluster seeding through Ir as shown for Au, AuIr, FeIr. Criteria for the suitability of a material to form a superlattice are given and largely confirmed. It is proven that at least Pt and Ir even form epitaxial cluster superlattices. The temperature stability of the cluster superlattices is investigated and understood on the basis of positional fluctuations of the clusters around their sites of minimum potential energy. The binding sites of Ir, Pt, W and Re cluster superlattices are determined and the ability to cover samples macroscopically with a variety of superlattices is demonstrated.

Introduction

Clusters are a distinct state of matter. Not only their structure, electronic, magnetic and optical properties change with size, but also new properties emerge as a result of quantization effects unknown in the atom and the bulk solid [START_REF]Quantum Phenomena in Clusters and Nanostructures[END_REF]. Well known examples for unique cluster properties are magic sizes in geometric and electronic structure, superparamagnetism, plasmon resonances or size dependent reactivity [START_REF] Haberland | Flüssigkeiten, Nanosysteme, Chapter:Cluster[END_REF][START_REF] Kreibig | Optical properties of metal clusters[END_REF][START_REF] Heiz | Nanocatalysis[END_REF]. Though cluster properties may be studied in their purest form for mass selected clusters in the free beam, a use of clusters requires a suitable support [START_REF]Metal clusters at surfaces[END_REF]. Ideally, a system of supported clusters is a regular array with equal sized, equally spaced clusters, each in an identical environment and of macroscopic array extension. The cluster bonding to the substrate should be strong enough to warrant their stability at the temperature of operation and weak enough not to destroy them as own entities. The substrate should be inert in a sense that it does not deteriorate under the condition of use but active to bestow new functionalities to the clusters without destroying them. Such arrays or cluster superlattices would allow one to address single clusters (as might e.g. be of interest for magnetic applications), to obtain a large amplitude of response resulting from the additive superposition of all single clusters and being characteristic for a cluster of well defined size in a specific environment (as e.g. needed in catalysis), or to obtain a collective coherent response characteristic of a large interacting ensemble of clusters (as e.g. in optics).

This vision triggered attempts to make use of self organization and/or templates for the creation of cluster superlattices and a few examples are given here (compare also [START_REF] Becker | Two-dimensional Templates[END_REF]). By making use of the regular arrangement of steps on vicinal Au(111) and its herringbone reconstruction crossing the steps at right angles a proper Co cluster superlattice could be realized [START_REF] Repain | Two-dimensional long-range-ordered growth of uniform cobalt nanostructures on a Au(111) vicinal template[END_REF], enabling the measurement of its temperature dependent magnetic properties including the distribution of cluster magnetic anisotropy energies [START_REF] Weiss | Uniform magnetic properties for an ultrahigh-density lattice of noninteracting co nanostructures[END_REF]. Also Fe could be grown regularly [START_REF] Rohart | Growth of iron on gold (788) vicinal surface: From nanodots to step flow[END_REF], but the method is limited by its low growth temperature and strong cluster substrate interaction giving rise to alloying. Alumina double layers on Ni 3 Al(111) exhibit a phase with a regular superlattice of sites for nucleation upon metal deposition [START_REF] Degen | Bimetallic Pd-Au nanocluster arrays grown on nanostructured alumina templates[END_REF], which are holes in the oxide [START_REF] Schmid | Nanotemplate with holes: Ultrathin alumina on Ni 3 Al(111)[END_REF]. Cluster superlattices were realized for a variety of metals at room temperature [START_REF] Degen | Bimetallic Pd-Au nanocluster arrays grown on nanostructured alumina templates[END_REF][START_REF] Hamm | Bimetallic Pd-Au nanocluster arrays grown on nanostructured alumina templates[END_REF][START_REF] Lehnert | Nucleation of ordered Fe islands on Al 2 O 3 /Ni 3 Al(111)[END_REF]] and a high perfection was achieved for Pd [START_REF] Degen | Bimetallic Pd-Au nanocluster arrays grown on nanostructured alumina templates[END_REF]. Though such cluster lattices appear to be suited as model catalysts, the preparation of the alumina layer is the result of a subtle procedure, comprises defects and at least two phases of alumina with limited domain sizes, of which only one is suitable as a template [START_REF] Schmid | Nanotemplate with holes: Ultrathin alumina on Ni 3 Al(111)[END_REF]. Recently Xe buffer layer assisted self assembly of Co on a BN-layer forming a moiré with Rh(111) was achieved [START_REF] Zhang | Ordered layers of Co clusters on BN template layers[END_REF]. Though the placement of the Co clusters is regular, the method hampers from the very low temperature of fabrication, the limited thermal stability and the only incomplete filling of the template cells. As a final example, on the W(110)/C-R(15×12) surface carbide arrangements of Au, Ag and Co clusters could be grown, the latter two with a high degree of order [START_REF] Varykhalov | Origin of Au nanostructures on tungsten surface carbides[END_REF][START_REF] Bachmann | Quasi-one-dimensional self-assembly of metal nanoclusters on C/W(110)[END_REF]. Though the thermal stability of the arrangements is rather good, no macroscopic extension of a superlattice is achieved due to the persistent existence of terraces without the surface carbide.

Graphene moirés with noble metal surfaces are a new and unique support for cluster superlattices. This was shown first for graphene moirés on Ir(111) allowing Ir cluster superlattice formation [START_REF] N'diaye | Two-dimensional Ir cluster lattices on a graphene moiré on Ir(111)[END_REF]. Though a special material system, the binding mechanism is versatile. Through metal deposition on the graphene layer -which is only weakly interacting with the metal substrate in the absence of metals deposits [START_REF] Pletikosić | Dirac cones and minigaps for graphene on Ir(111)[END_REF] -graphene locally rehybridizes from sp 2 to sp 3 carbon bonds at a specific location in the moiré unit cell and in between the substrate and deposit metal, thereby forming strong carbon metal bonds [START_REF] Feibelman | Pinning of graphene to Ir(111) by flat Ir dots[END_REF]. In between the substrate and deposit metal the sp 3 rehybridized graphene has tetrahedral bond angles and may thus be considered as diamondlike. Within each moiré unit cell rehybridization is possible where locally the carbon rings center around a threefold coordinated hcp-site or a threefold coordinated fcc-site (both having three C-atoms on atop substrate sites). These locations are named hcp region or fcc region, respectively. Experimentally and by DFT calculations we find that Ir clusters bind by far stronger to hcp regions [START_REF] N'diaye | Two-dimensional Ir cluster lattices on a graphene moiré on Ir(111)[END_REF][START_REF] Feibelman | Pinning of graphene to Ir(111) by flat Ir dots[END_REF][START_REF] N'diaye | Structure of epitaxial graphene on Ir(111)[END_REF].

Fig. 1a displays a cluster superlattice grown on a graphene flake formed by temperature programmed growth on Ir(111) [START_REF] Coraux | Growth of graphene on Ir(111)[END_REF]. With this method graphene covers the surface only partially, which is suitable for scanning probe investigations, as it retains the metal surface partially for calibration of cluster size through island coverage in the graphene free areas. Also direct comparison of the properties of clusters and those of the deposit islands on the metal is possible. Recently, we employed chemical vapor deposition at high temperatures to grow graphene fully covering the substrate and displaying hardly any defects [START_REF] Coraux | Growth of graphene on Ir(111)[END_REF][START_REF] Coraux | Structural coherency of graphene on Ir(111)[END_REF]. Using a dedicated combination of both methods [START_REF] Van Gastel | Selecting a single orientation for millimeter sized graphene sheets[END_REF], we are not only able to ensure full coverage but also the graphene and Ir dense packed atomic rows to be parallel, i.e. no traces of rotational variants are present [START_REF] Loginova | Rotational domains of graphene on Ir[END_REF].

In this manuscript we will show that graphene moirés as active templates are superior to other systems enabling the growth of two dimensional cluster superlattices on solid surfaces through a unique combination of properties: (i) the cluster binding mechanism is universal enabling growth of a large diversity of materials as superlattice; (ii) the superlattice order is extremely high with a completely filled lattice;(iii) if desired the superlattice extends macroscopically without uncovered substrate patches; (iv) fabrication is possible at room temperature; (v) the superlattices possess a reasonably high thermal stability and display absence of alloying and interdiffusion within a large temperature range; (vi) the cluster size is tunable and the size distribution is narrow.

To demonstrate the universality of our approach in view of superlattice forming materials we primarily focussed on cluster materials with potentially interesting structural, magnetic, catalytic or optical properties. As heuristic guidelines for the suitability of a material to form a superlattice we considered three factors: (i) A large cohesive strength of the material as an indicator for the ability to form strong bonds. (ii) A large extension of a localized valence orbital of the deposit material allows it to efficiently interact with the graphene π-bond and thus to initiate rehybridization to diamondlike carbon underneath the cluster. (iii) A certain match of the graphene unit cell repeat distance on Ir(111) of 2.452 Å [START_REF] N'diaye | Structure of epitaxial graphene on Ir(111)[END_REF] and the nearest neighbour distance of the deposit material is necessary to fit the first layer cluster atoms atop of every second C atom. As small clusters -which are the relevant sizes to start superlattice growth -have a smaller lattice parameter compared to bulk materials, and as Ir works perfectly as a cluster material [START_REF] N'diaye | Two-dimensional Ir cluster lattices on a graphene moiré on Ir(111)[END_REF], we considered 2.7 Å as an optimal nearest neighbor distance [25]. Table compares the data for the tested materials. Tungsten was selected as a likely candidate for superlattice formation (all three figures are in favor of superlattice formation), but with a different crystal structure than Ir. Re, Pt and Au were selected as as potentially interesting materials for catalysis. According to our guidelines we expected Re to be most likely a superlattice forming material, also Pt, but with a slightly smaller probability and Au as an unlikely candidate. Fe and Ni were selected as materials because of their ferromagnetism. According to their figure of merits, however, we did not expect superlattice formation.

Experimental

Experiments were carried out in an ultra high vacuum variable temperature scanning tunneling microscopy apparatus with a base pressure of 1 × 10 -10 mbar equipped with a mass separated ion source, low energy electron diffraction, a gas inlet for ethylene exposure through a tube ending approximately 2 cm above the sample surface and a four pocket e-beam evaporator. The sample was cleaned by repeated cycles of sputtering with a beam of 2.5 keV Xe + ions at 300 K and annealing to 1520 K. Graphene was prepared using temperature programmed growth (TPG) at 1470 K or chemical vapor deposition (CVD) at 1370 K [START_REF] Coraux | Growth of graphene on Ir(111)[END_REF][START_REF] Van Gastel | Selecting a single orientation for millimeter sized graphene sheets[END_REF]. TPG results in a graphene surface coverage of about 25% with flakes of a few 100 Å to about 1000 Å extension. Adding a CVD step results in up to full graphene surface coverage and domains of µm and larger extension. Cluster growth was performed through e-beam evaporation of well degased high purity metals with typical deposition rates of a few times 10 -2 ML/s where 1 ML (one monolayer) corresponds to the surface atomic density of Ir(111). During deposition the pressure remained in the low 10 -10 mbar range. Precise calibration of the deposited amount Θ was obtained by STM image analysis of the fractional area of deposit islands on the clean Ir(111) surface after a defined deposition time. If necessary the sample was gently annealed prior to coverage calibration. Through annealing the heteroepitaxial islands became compact and their size increased, thereby minimizing imaging errors associated with the finite STM tip size. Clusters were imaged at deposition temperature, if not indicated otherwise. However, for deposition above 300 K or after annealing the sample was quenched to 300 K for imaging.

Results

3.1.

Cluster structure and superlattice formation at 300 K 111) is in all cases much more sticky to the deposited metals than the surface of graphite [START_REF] Bardotti | Experimental observation of fast diffusion of large Antimony cluster on graphite surfaces[END_REF]. However, not all materials form a cluster superlattice. Ir and Pt form superlattices of similar perfection [compare Figs. 1(a) and 1(b)]. For the represented Θ ≈ 0.2 ML both materials exhibit two distinct height levels of the clusters indicating an out-of-plane texture of the cluster orientation. Distinct height levels are present also for larger and higher clusters up to the coalescence threshold (compare also Fig. 1 of reference [START_REF] N'diaye | Two-dimensional Ir cluster lattices on a graphene moiré on Ir(111)[END_REF]). The apparent height differences between 3 ML and 4 ML clusters as well as those between 4 ML and 5 ML clusters are for Ir and Pt in the range of 2.2 Å and 2.3 Å, i.e. of the size of a monatomic step height h 1 on a (111) terrace [h 1,Ir = 2.22 Å and h 1,Pt = 2.27 Å]. The height differences in lower levels differ from these numbers. Specifically, the apparent height difference between the graphene substrate and the first cluster height level for s av > 15 atoms is always found to be larger than 2.5 Å while the difference between the first and second height level is typically below 2.0 Å. We interpret these deviations from the (111) step height as density of state effects. While for Ir and Pt the height of each single cluster is an integer number of (111) layers, the average cluster height h av may be noninteger due to the averaging. Fig. 2 displays an analysis of h av for Ir clusters grown at 350 K and Pt clusters grown at 300 K. The decrease of h av for Ir clusters between 1.5 ML and 2.0 ML is due to the onset of cluster sintering. Upon cluster sintering the clusters reshape and material flows into the gaps separating the clusters, thereby causing frequently a height reduction. It is also apparent from Fig. 2, that large Pt clusters tend to grow flatter than Ir clusters, giving rise to a somewhat earlier cluster sintering.

After having established the [111] out-of-plane texture of Pt and Ir clusters, the question arises whether the clusters possess also in-plane-texture, i.e. whether the clusters are also oriented within the surface plane. Fig. 3(a) displays a small area of an Ir cluster array after deposition of 1.5 ML imaged with a large tunneling resistance of 2.3 × 10 9 Ω. Despite the absence of atomic resolution at least some cluster edges appear to be oriented along the 211 -direction. Lowering the tunneling resistance to 7 × 10 6 Ω -thereby bringing the tip close to the cluster surfaces -and tuning the contrast to the different levels of the cluster top mesas changes the picture. The top mesas are almost atomically resolved (some row like corrugation is visible) and the edges of the top mesas are unambiguously oriented along 1 10 . It needs to be noted that under low tunneling resistance conditions necessary for atomic resolution clusters are usually picked up by the STM tip. The apparently different orientation of cluster edges at high tunneling resistances is a mere imaging artifact. If a tip scans a hexagonal grid of elevated objects in a large distance not the shape of the objects forming the grid but the hexagonal grid itself determines the apparent orientation of the boundaries between the objects. The inset of Fig. 3(d) represents a ball model of a five layer cluster containing 140 atoms which is consistent with the experiments. Although we are unable to prove directly that the cluster sidewalls are formed by {100} and {111} facets, facets of smaller slope would imply cluster contacts at their base. This is unlikely to be the case, as we find in annealing sequences clusters to reshape rapidly upon contact. To summarize, we have shown that Ir clusters (and the Pt ones most likely as well) are epitaxial clusters with the (111) cluster planes parallel to the substrate surface and the 1 10 cluster directions parallel to the 1 10 -directions of the Ir substrate and the 1 120 -directions of graphene. This epitaxy of Ir clusters on the graphene moiré is also predicted by the geometry in the DFT based model of cluster binding [START_REF] Feibelman | Pinning of graphene to Ir(111) by flat Ir dots[END_REF].

Also tungsten forms a cluster superlattice of high perfection. Compared to Pt and Ir the centers of mass of the clusters deviate slightly more from a perfect hexagonal superlattice. Still the scatter of the cluster positions is too small to result in cluster sintering for Θ = 0.44 ML as visualized in Fig. 1c. Close inspection of our data -also for Θ = 0.04 ML -shows that less than 1% of clusters is out registry with the hcp regions (see also below). The apparent cluster heights for Θ = 0.44 ML range from 4 Å to 8 Å with an average around 6 Å. The clusters seem higher than the Ir ones for a comparable Θ. Distinct height levels are also present for W clusters as is obvious from Fig. 1(c). However, the height levels are less well defined due to their smaller separation. Between adjacent clusters we measure frequently height differences of about 0.8 Å to 1 Å. With a small distortion the dense packed W(110) plane with a nearest neighbour distance of 2.74 Å would fit to the triangular 2.46 Å periodicity provided by the graphene for rehybridization. However, a [110] out-of-plane cluster texture would result in height levels spaced by 2.24 Å, i.e. a similar spacing as for Ir and Pt. From the presence of intermediate levels we exclude this cluster orientation as the single one. Small step heights of 0.8 Å to 1 Å are consistent with a [111] out-of-plane texture with a step spacing of 0.91 Å. The open W(111) plane has also the threefold symmetry of the graphene moiré in the hcp or fcc regions. However, in plane atomic spacings are 4.48 Å. They could be fitted to the 4.27 Å separation of a ( √ 3 × √ 3)R30 superstructure of graphene. For a final statement more detailed experiments are certainly necessary but also likely to be rewarding to settle the issue of the W cluster superlattice texture.

For Re only partial order of the cluster arrangement is realized as visible in Fig. 1(d). Two possible reasons could cause the apparent disorder: (i) the existence of several adsorption mimima within a moiré unit cell, causing less ordered growth followed by early coalescence and cluster rearrangement; (ii) a too low depth of the cluster size dependent adsorption mimina. Assuming an increase of the potential well with increasing cluster size, adatoms and small clusters up to a certain size s c would be likely to leave their unit cell during growth. Both scenarios would give rise to the observed heterogeneous size distribution, but the latter would explain also the existence of a large number of empty moiré unit cells. For Re we performed also low coverage experiments [compare Fig. 7(d)]. We find a comparatively low moiré unit cell occupation probability (or a comparatively large s av ) for the deposited amount, but with few exceptions all clusters adsorbed on a regular grid. We are therefore convinced that indeed the adsorption site minima are not of sufficient depth to keep small Re clusters up to a certain critical size (being much larger than the one for Ir, Pt and W) during and after growth on their position within the moiré. We note that the poor quality of the Re cluster superlattice is at variance with our expectations, as Re has a large cohesive energy, an extended d-orbital and a reasonably well matching nearest neighbour distance (compare table 1).

For Fe [Fig. 1(e)], Au [Fig. 1(f)] and Ni (data not shown) at room temperature no superlattice can be realized. Large clusters, lacking defined height levels or shape features are formed. The unstructured, hemispherical clusters display heights of up to 23 Å for Fe and 15 Å for Au. The absence of a regular cluster superlattice for these materials is expected in view of their small cohesive energy and/or their limited valence orbital extension. Binding of the deposit metal to graphene is apparently too weak to trap adatoms and small clusters, i.e. the depth of the potential energy minima within a moiré unit cell is not sufficient to stabilize a growing cluster.

Low temperature cluster superlattice growth and annealing

If we assume that cluster superlattice formation for Re and even more for Au, Fe and Ni is impeded by a too high mobility of small clusters during growth, lowering the growth temperature would decrease s c and thus be an efficient strategy to improve superlattice formation. Fig. 4(a) displays a Re cluster superlattice grown at 200 K by deposition of Θ = 0.45 ML. Annealing to 300 K does not change the cluster superlattice as visible in Fig. 4(b). The side-by-side comparison to Re clusters grown at 300 K in Fig. 4(c) makes the efficiency of lowering the growth temperature to improve superlattice formation obvious. The low growth temperature reduced s c , enabled the almost complete filling of the moiré unit cells and allowed the clusters to grow to a size being stable even at 300 K. One might speculate that a further lowering of the growth temperature would have improved the Re cluster superlattice even further. In the quantitative analysis of Fig. 4(d) it is also apparent that the difference in moiré unit cell occupation between growth at 400 K and annealing to 400 K from a formation temperature of 200 K is even larger than the corresponding one at 300 K. At the same time it is also obvious from the data of Fig. 4(d) that growth at a low temperature and annealing preserves the superlattice only up to a limited temperature [(compare up and down triangles at 400 K in Fig. 4(d)]. Lowering the growth temperature to 200 K for Au did not significantly enhance cluster nucleation. However, lowering the growth temperature even further to 90 K resulted in an Au cluster superlattice of moderate order as shown in Fig. 4(e). Also in this case the once formed superlattice may be preserved to a higher temperature. However, as visible from the quantitative analysis shown in Fig. 4(d), the Au cluster superlattice is deteriorated already after annealing to 220 K.

Mild annealing leads to more subtle effects which do not affect the positional order of the cluster array. For 0.45 ML of Ir deposited at 300 K, by annealing to 450 K for 300 s the amount of single layered clusters decreases from (15 ± 2) % to (10 ± 2) % with a negligible decrease of the overall occupational density of the moiré with clusters. This implies, that single layered clusters of a certain size transform to a more stable two layered form upon annealing.

Cluster seeding

Low cohesive energy metals tend not to form cluster superlattices on the graphene moiré on Ir(111), as tested by us for Au, Fe, and Ni. Such metals wet high cohesive energy metals, due to their lower surface free energy. High cohesive energy metals mostly form rather perfect cluster superlattices, tested here for Ir, Pt and W. It is thus natural to apply cluster seeding, i.e. to define the positions of the clusters by a small Θ of a high cohesive energy metal and to grow these seeds by subsequent deposition of a low cohesive energy metal [START_REF] Schmid | Nanotemplate with holes: Ultrathin alumina on Ni 3 Al(111)[END_REF][START_REF] Hamm | Bimetallic Pd-Au nanocluster arrays grown on nanostructured alumina templates[END_REF]. The successful application of this method is visualized in Fig. 5. As shown in Fig. 5(a

Temperature stability

For applications of cluster superlattices in nanomagnetism and nanocatalysis thermal stability of the cluster arrays and the absence of sintering at the temperature of use is of crucial importance. To provide data in this respect we investigated the thermal stability of the materials tested so far and display the results in Fig. 6. The example annealing sequence of Figs. 6(a) to 6(f) shows the gradual decay of the cluster superlattice through isochronal annealing steps of 300 s up to 650 K. The Pt cluster superlattice remains intact up to 400 K. Fig. 6(g) quantifies annealing by plotting the temperature dependence of the moiré unit cell occupation probability n as a function of temperature T . It is apparent that the Ir cluster superlattice is indeed the most stable one, decaying as the only one in two steps. Most cluster superlattices are stable up to 400 K, which provides a reasonable temperature window for nanocatalysis and nanomagnetism experiments.

The decay of all cluster superlattices occurs due to the thermally activated motion of clusters. The clusters fluctuate around their equilibrium positions within the moiré unit cell. The magnitude of cluster fluctuations depends on the cluster size and the internal cluster structure (the isomer). Upon encounter during their fluctuations the clusters merge immediately, on a time scale of less than a second. The outcome of the merging again depends on cluster size. We distinguish two prototypical situations. (i) The clusters consist only out of a few atoms. Such clusters result from a very low deposited amount Θ. For such a Θ also the moiré unit cell occupation probability n is typically well below 1. Through thermally activated fluctuations a cluster may surmount the activation barrier E a to leave its moiré unit cell. If the cluster arrives in an empty cell it will rest there, if it arrives in an occupied cell the two clusters in the cell coalesce. They reshape completely such that as end product a single, compact cluster results which is located entirely within a single moiré unit cell. This is the regime of complete cluster coalescence. Figs. 7(a)-(e) display a sequence of STM topographs taken at 390 K. The visible clusters result from Θ = 0.01 ML and have s av = 4.5 atoms. White circles in subsequent stills indicate locations of thermally activated changes. The white circles in the upper left corner of Figs. 7(a)-(c) highlight a situation of thermally activated cluster motion resulting eventually in complete cluster coalescence. Note that the resulting cluster appears to be larger and higher in consequence of complete coalescence. In the Pt annealing sequence of Fig. 6 in (d) a considerable number of larger and higher clusters appear, which are preferentially located next to empty moiré cells. They are likely to be formed by complete coalescence. In addition, in Figs. 7(a)-(e) a number of thermally activated cluster jumps into empty cells are circled, which consequently do not result in cluster coalescence. (ii) If the clusters are large, close to the coalescence threshold, cluster merging proceeds differently. Still such clusters fluctuate around the location of their potential energy minimum. According to their large mass and better internal stability the magnitude fluctuations has diminished and one might ask how cluster merging takes place at all. However, only small fluctuations are necessary to initiate cluster merging, as due to their large size the cluster have only a small edge separation of a few Ångströms. For coalescence the clusters do not have to leave their moiré unit cell, but it is sufficient to move a little up their shallow potential energy depression to encounter a neighbouring cluster. Due to their size and significant binding the resulting cluster spans two moiré unit cells and does not reshape completely. This is the regime of cluster sintering or incomplete cluster coalescence. Figs. 7 (f)-(j) display a situation of cluster sintering imaged at 470 K for clusters formed after deposition of 1.5 ML Ir (130 atoms per moiré unit cell) at 350 K. Two subsequent cluster sintering events of neighbouring clusters result eventually in a new single cluster extending over three moiré unit cells. The two scenarios depicted above are extreme cases and intermediate situations occur. From what has been said above it appears that cluster superlattice stability depends also on s av . It is expected that arrays of medium sized clusters with diminished fluctuation amplitudes and still sufficient separation from their neighbours are the most stable ones.

To obtain a quantitative estimate for parameters determining cluster superlattice decay we model it as follows. We assume the cluster superlattice to consist of clusters with a unique activation energy E a for cluster interaction with a neighbouring cluster and an interaction frequency ν = ν 0 e -Ea/k B T , where ν 0 is an attempt frequency characterizing the frequency of cluster fluctuations, k B the Boltzmann constant and T the temperature of the experiment. The probability that one cluster encounters another one is proportional to n. We assume complete coalescence, i.e. the final cluster to occupy only a single moiré unit cell. The number of these events is as well proportional to n. Under these conditions the decrease of n with time t at a given temperature is:

dn dt = -n 2 ν (1)
Using integration by parts we solve this differential equation for the boundary of the cluster density n 1 before, and n 2 after an annealing step of a fixed time interval ∆t resulting in

ν(T ) = 1 ∆t 1 n 2 - 1 n 1 . (2)
We emphasize here that our crude approximation effectively averages over different size dependent interaction frequencies ν for a given size distribution. However, using the Clusters E a ∆E a ν 0 ∆ν 0,- ∆ν 0,+ Ir, 0.45 ML (I) 0.41 eV 0.02 eV 1. [START_REF] Heiz | Nanocatalysis[END_REF] annealing time ∆t and the annealing temperature T , this appoach allows one to derive the temperature dependence of ν from an annealing sequence as shown in 6 (a)-(f).

The resulting Arrhenius plots are shown in Fig. 7 (h). Activation energies are between 0.38 eV and 0.75 eV. The resulting ν 0 lie between 1.4 Hz and 500 Hz. These attempt frequencies are much lower than a typical phonon frequency and also much lower than what is found for the diffusion of adatoms and small adclusters (compare e.g. [START_REF] Wang | Structure, stability, and surface diffusion of clusters:Ir x on Ir(111)[END_REF]). According to transition state theory the low ν 0 point to exceptionally large differences of the partition function of clusters in the bound state versus clusters in the transition state. The diffusion parameters have to be viewed as effective diffusion parameters for an ensemble of clusters comprising all size effects and not as the properties of an individual cluster. This is also illustrated by the large variations in parameters for the observed cluster lattices from Pt with different average cluster size.

For the case of Ir as shown in Fig. 6 (g) and (h), there is a distinct discontinuity in the cluster density and consequently in the estimated interaction frequencies ν between 550 K and 650 K. Interestingly this transition coincides with all single layered clusters dying out. We interpret the discontinuity as a result of different diffusion parameters for single layered and multi layered clusters.

This approach of effective diffusion parameters is checked for consistency with a kinetic Monte Carlo simulation. The algorithm for the simulation is based on work by Bortz at al. [START_REF] Bortz | New algorithm for monte-carlo simulation of ising spin systems[END_REF]. The cluster lattice is modeled as a hexagonal lattice with clusters, which can hop to adjacent sites with a frequency ν = ν 0 e Ea/k B T based on ν 0 and E a as given in table 2. The cluster lattice dwells at each annealing temperature for 300 s and is heated successively to higher temperature annealing intervals. Time for cooling, imaging, and reheating is omitted. The simulation reproduces the cluster densities well as shown in figure 8. Kinks occur in the curve, where the temperature changes. Not surprising, Iridium is an exception to the good match because one kind of clusters dies out rapidly and the approximation of effective diffusion parameters breaks down for the examined temperature range.

Binding sites of clusters in the superlattice

Experimentally [START_REF] N'diaye | Two-dimensional Ir cluster lattices on a graphene moiré on Ir(111)[END_REF][START_REF] N'diaye | Structure of epitaxial graphene on Ir(111)[END_REF] and by calculations [START_REF] Feibelman | Pinning of graphene to Ir(111) by flat Ir dots[END_REF] we find Ir clusters to adsorb preferentially in hcp regions of the moiré unit cells. These sites differ from the fcc regions only by the fact that instead of a threfold coordinated fcc hollow site a threefold coordinated hcp hollow site is centered in the carbon ring. They differ significantly from the atop-type area which has an atop site centered in the carbon ring. At low growth temperature we find for Ir deposition also fcc regions to be populated by small clusters, consistent with the similarity of the two areas [START_REF] N'diaye | Structure of epitaxial graphene on Ir(111)[END_REF]. It is not at all evident that also other materials adsorb preferentially to hcp regions. Specifically for materials with a different crystal structure like W with its bcc structure or Re with the hcp crystal structure we would not be surprised to find the clusters adsorbed preferentially to fcc regions or to be even unspecific to the small difference caused by the second layer underneath the Ir surface. To obtain cluster binding sites experimentally we make use of the fact that the graphene sheets on Ir form a jagged zig-zag edge when in contact with a 1 10 /{100} microfacet or A-step of the substrate. The step undulation of the graphene sheet has the moiré periodicity. The protrusions of the graphene flake's edge are bowing out towards the Ir terrace at atop-type areas. This fact does evidently not depend on the deposited material and allows us unambiguous cluster adsorption site assignment. In Fig. 9 for Ir, Pt, W and Re the corners of the moiré unit cell grids are fixed to these atop-type areas. We find that the clusters are always located in the triangular half-unit cells pointing away from the one dimensional graphene-Ir interface (green triangles in Fig. 9). According to our unit cell assignment (compare Fig. 1 of reference [START_REF] N'diaye | Two-dimensional Ir cluster lattices on a graphene moiré on Ir(111)[END_REF]) these are hcp regions. Let us point out that in Fig. 8 of reference [START_REF] N'diaye | Structure of epitaxial graphene on Ir(111)[END_REF] and in the accompanying text of Sec. 8 the labeling and use of hcp region and fcc region is erroneously interchanged.

Towards cluster superlattice materials

To probe the properties of cluster superlattices by averaging techniques and to investigate their suitability for potential applications it is necessary to cover a sample macroscopically with a cluster superlattice. This need is evident if one considers e.g. the analysis of reaction products from a cluster superlattice in nanocatalysis. The presence of the bare metal would result in additional peaks in thermal desorption spectra and certainly complicate the data analysis. To establish a macroscopic cluster superlattice the graphene moiré must cover the metal substrate entirely, be of unique orientation with an as large as possible moiré supercell which displays upon deposition of suitable materials local rehybridization. While it is likely that a number of graphene moirés on different metals fulfill all these conditions, so far they have been proven only for graphene moirés on Ir(111). Some optimization of the graphene growth procedure was necessary to achieve simultaneously full graphene coverage and a single orientation of the graphene and the graphene moiré [START_REF] Coraux | Growth of graphene on Ir(111)[END_REF][START_REF] Coraux | Structural coherency of graphene on Ir(111)[END_REF][START_REF] Van Gastel | Selecting a single orientation for millimeter sized graphene sheets[END_REF]. Fig. 10 displays a large scale STM topograph visualizing to a certain extent the quality of the available substrate. The cluster superlattice is present in the entire topograph in unique orientation and even steps merely present locations where a line of clusters is missing, but without disturbing the overall alignment of the superlattice.

Conclusion

In conclusion, we have established that the graphene moiré on Ir(111) is a versatile and active template for cluster superlattice growth of a great variety of materials and with macroscopic lateral extension. If necessary, techniques like low temperature growth or cluster seeding may permit cluster superlattice growth for cases, where simple room temperature deposition fails. The high thermal stability of the cluster superlattices and the ability to grow them on macroscopic areas opens new opportunities for fundamental cluster research and applications.

Figure 1 .

 1 Figure 1. STM topopgraphs of Ir(111) with graphene flakes after deposition of an amount Θ of various metals at 300 K. (a) Θ = 0.20 ML Ir, average cluster size s av = 17 atoms; (b) Θ = 0.25 ML Pt, s av = 22 atoms; (c) Θ = 0.44 ML W, s av = 38 atoms; (d) Θ = 0.53 ML Re, s av = 60 atoms; (e) Θ = 0.77 ML Fe, s av = 420 atoms; (f) Θ = 0.25 ML Au, s av = 100 atoms. Image size 700 Å × 700 Å.

Figure 1 displays

 1 Figure 1 displays STM topographs after deposition of 0.2-0.8 ML on Ir(111) partly covered with graphene flakes. The graphene flakes are typically attached to substrate steps, but also extend over one or several of them [Fig. 1(a), 1(b), 1(e)]. In the areas without graphene, deposit metal islands of monolayer height formed from the evaporated material. In Figs. 1(c)-1(e) already second layer island nucleation took place. Depending on the deposited metal the island nucleation density on Ir(111) varies considerably being

Figure 2 .

 2 Figure 2. Ir (full squares) and Pt (red dots) average cluster heights h rmav in monolayers as a function of deposited amount Θ.

Figure 3 .

 3 Figure 3. (a) STM topograph after deposition of 1.5 ML Ir on a graphene moiré on Ir(111), s av = 130. The dashed line indicates the position of an underlying substrate step. The visible clusters on the lower terrace have heights of 4 ML and 5 ML. For imaging the tunneling resistance was 2.3×10 9 Ω (I = 0.5 nA and U = 1.15 V. (b),(c),(d) Same location imaged successively with a low tunneling resistance of 7 × 10 6 Ω (I = 30 nA and U = 0.2 V) and contrast tuned to the different cluster levels. Cluster edges are aligned along 1 10 substrate directions [see (b)]. Inset in (d): Ball model of a 5 layer cluster of 140 atoms consistent with the experimental observations. Image size 130 Å × 160 Å.

Figure 4 .

 4 Figure 4. STM topographs of Ir(111) with graphene flakes after depositing amounts Θ of Re or Au at the indicated temperature T . (a) Θ = 0.45 ML Re, s av = 41, T = 200 K; (b) Θ = 0.45 ML Re, s av = 41, T = 200 K. Subsequently the sample has been annealed to 300 K and imaged; (c) Θ = 0.53 ML Re, s av = 60, T = 300 K; (d) Occupation probability n of moiré unit cells with clusters as a function of growth and annealing temperature T ; triangles pointing to the right: Au clusters, 0.25 ML deposited at the indicated T ; triangles pointing to the left: Au clusters, 0.25 ML deposited at 90 K and additionally annealed to the indicated T ; down triangles: Re clusters, 0.45 ML deposited at the indicated T ; up triangles: Re clusters, 0.45 ML deposited at 200 K and annealed to the indicated T . (e) Θ = 0.25 ML Au, s av = 24, T = 90 K.

  ) first through deposition of 0.1 ML Ir seed clusters are created in nearly all moiré unit cells. Subsequent deposition of Au [Fig. 5(b)] or Fe [Fig. 5(c)] at 300 K results in highly perfect Au and Fe cluster superlattices with Ir cores. Comparing Fig. 1(f) with Fig. 5(c) for Au and of Fig. 1(e) with Fig. 5(d) for Fe makes the dramatic effect of seeding obvious. Even after deposition of amounts beyond the coalescence threshold the seeding has beneficial effects on cluster uniformity and distribution. For deposition of Θ = 2 ML Fe still a high density of large, uniformly sized and spaced Fe clusters grows. These Fe clusters contain 760 Fe atoms and have a height of 20 Å [compare Fig. 5(h)]. They are not more positioned on a superlattice, but span 4 to 5 moiré unit cells and contain about 40 Ir atoms.

Figure 5 .

 5 Figure 5. (a), (c), (d),(e) STM topographs of Ir(111) with graphene flakes after depositing amounts Θ of Ir and Au or Fe at 300 K. Image size 500 Å × 500 Å. (a) Θ = 0.10 ML Ir, s av = 9. (b) Line scan along the line indicated in (a). The two red arrows indicate the height level of ML clusters. (c) Θ = 0.10 ML Ir and subsequently Θ = 0.35 ML Au corresponding to 30 Au atoms per seed cluster. (d) Θ = 0.10 ML Ir and subsequently Θ = 0.70 ML Fe corresponding to 61 Fe atoms per seed cluster. (e) Θ = 0.10 ML Ir and subsequently Θ = 2.0 ML Fe. Average number of Fe atoms per cluster is 760. (f) Line scan along the line indicated in (d). (g) Line scan along the line indicated in (e). (h) Line scan along the line indicated in (f). The red dashed lines in (f)-(h) indicate the height level of monolayer Ir clusters in (b).

Figure 7 .

 7 Figure 7. (a)-(e) STM topographs after deposition of 0.01 ML Ir at 350 K and subsequent heating to 390 K, The time lapse sequence images the same surface spot every 120 s at 390 K. Image size 250 Å × 250 Å, s av = 4.5 atoms. Circles indicate, where changes take place in successive images. (f)-(j) STM topographs after deposition of 2.0 ML Ir at 350 K and subsequent heating to 470 K, The time lapse sequence images the same surface spot every 120 s at 470 K. Image size 150 Å × 150 Å.

Figure 8 .

 8 Figure 8. Cluster density n evolution with a Monte Carlo simulation using average diffusion parameters. The temperature is increased every 300 s corresponding to Fig.6(g) and (h). Cluster densities after the annealing steps as in figure6are reshown for comparison.

Figure 9 .

 9 Figure 9. Binding site determination for (a) Ir, (b) Pt, (c) W and (d) Re clusters. Deposition was performed at 300 K and (a) Θ = 0.10 ML, s av = 9 atoms; (b) Θ = 0.04 ML, s av = 6 atoms; (c) Θ = 0.04 ML, s av = 4 atoms; (d) Θ = 0.03 ML, s av = 10 atoms. Due to the moiré the graphene flakes form a jagged edge if in contact with a 1 10 /{100} microfacet or A-step. The dark tips of the jagged graphene edge are atop site areas. Fixing the grid of moiré unit cells to these positions enables a binding site assignment. The clusters always sit in the green triangular half-unit cells pointing away from the step (see text).

Figure 10 .

 10 Figure 10. Ir cluster superlattice grown at 300 K with Θ = 0.80 ML resulting in s av = 70 on graphene prepared by temperature programmed growth followed by chemical vapor deposition and extending over the entire sample. Image size 0.5 µm × 0.3 µm, inset 500 Å × 300 Å.

Table 1 .

 1 material structure a/ Å r d /pm E coh /eV Crystal structure, nearest neighbor distance a, valence d-orbital radius r d and cohesive energy E coh of the tested materials for cluster superlattice formation on the graphene moiré on Ir(111).

	Ir	fcc	2.715	70.8	6.94
	W	bcc	2.741	77.6	8.90
	Re	hcp	2.761	73.9	8.03
	Pt	fcc	2.775	65.9	5.84
	Au	fcc	2.884	63.5	3.81
	Fe	bcc	2.483	38.2	4.28
	Ni	fcc	2.492	33.8	4.44

Table 2 .

 2 Diffusion parameters and corresponding statistical errors as derived from ν(T ), for the cases of Ir, Pt an W. The parameters have as well been determined separately for two sections (I) and (II) of the dataset as indicated in Fig.6(h) Attempt frequencies have an statistical asymmetric error, so that negative and positive one are given. Systematic errors may be larger (see text).

	Hz	0.5 Hz	0.8 Hz

Acknowledgements

Work at Cologne University was supported by DFG through the project "Two Dimensional Cluster Lattices on Graphene Moirés". T.M. acknowledges useful discussion with Peter J. Feibelman.


domain: sdv sde sdu.stu

text:
Claire Jouany

Francoise Vertès

Fabienne Barataud

L Fourrié

J Peigné

Thomas Nesme

Servane Penvern

Shared Research Questions on Soil Quality in OF Results of a participatory workshop

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Shared

  Research Questions on Soil Quality in OF Results of a participatory workshop Context: Soils perform a multitude of functions and provide a large panel of ES services  Soils quality maintenance and improvement are key issues and effective levers for development of Organic Farming systems Objectives: 1. to identify key research questions to be addressed on soils in OF systems ; 2. facilitate network/project building from interactions between academics and stakeholders. Material & Methods: Town Hall Meeting 1 with 3 successive rounds, each introduced by a question : 1. For you what is a high quality soil (HQS) in OF? 2. Which are the locks to undo to obtain a HQS in OF? 3. Which research questions do we need to answer to undo the locks? Over 150 participants from large professional backgrounds and diverse systems in Paris (France), 1 full day, Nov. 2018.  Each question discussed by 15 tables (10 participants + 1 facilitator), validated then transmitted to an expert panel  Experts gather similar ideas and allow reformulation to take into account nuances > projection on a full screen.  Participants can react by reinforcing or proposing new ideas. The third round produced 105 ideas aggregated in 20 questions, confirming the need of research on soils for OF systems.  Generic questions concerned mainly knowledge's on soil functioning (3, 10), biogeochemical cycling (4, 15) and biological interactions (6, 20).  Specific questions referred to C,N,P fluxes (4, 5), soil ecology (6) & health (1), long term dynamics and soil resilience (8, 16), impact of specific technics (5, 9, 14), tools and indicators for management (10, 13) and system design (8, 9, 12).  Emphasize on the role of academic teaching and knowledge's transfer to end-users (2, 15) confirm need for interactions with social sciences 2 Key role played by crop livestock production systems for soil quality and resilience (11, 17). et al., 2017 ; 2 Adewopo et al., 2014