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August 2019:

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The figure shows the time series of CO2 and XCO2 (column-averaged dry-air mole fraction of CO2) for satellite observations, station data, and the mean calculated from emission driven runs of two Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) (Eyring et al. 2016a) for the years 2003-2014. The satellite observations (Buchwitz et al. 2018) combine measurements of SCIAMACHY (SCanning Imaging Absorption Spectrometer for Atmospheric CHartographY) on Envisat and TANSO-FTS (Thermal And Near infrared Sensor for carbon Observation - Fourier Transform Spectrometer) on GOSAT (Greenhouse gases Observing SATellite). The station data are from the NOAA/ESRL (National Oceanic and Atmospheric Administration/Earth System Research Laboratory) surface measurements.

All data are processed using the Earth System Model Evaluation Tool (ESMValTool, Eyring et al. (2016c)). Currently, a release of a new version (v2.0) of the ESMValTool is in preparation, which is developed to analyze CMIP6 model simulations as soon as they are published to the CMIP6 archive. It includes a large collection of diagnostics and performance metrics for atmospheric, oceanic, and terrestrial variables for the mean state, trends, and variability. Here, the ESMValTool is used to convert the model results to XCO2, the quantity provided from satellite measurements, and for the sampling of the models in the same way than the observations. For better comparison of the seasonal cycle, the models results are corrected for an offset to the satellite data.

Models and observations show the expected increase in CO2and the characteristic seasonal cycles most pronounced in the Northern Hemisphere, with lower values in the summer when strong photosynthesis causes plants to absorb CO2, and higher values in the winter when photosynthesis stops and CO2is released through respiration. The amplitude of the seasonal cycle differs between models and observations. The reason for this difference and potential future changes will be further evaluated within the Advanced Earth System Model Evaluation for CMIP (EVal4CMIP) project funded by the Helmholtz Society. Changes in the seasonal cycle are expected because of the CO2 fertilization effect (Wenzel et al. 2016). New emergent constraints (Eyring et al. 2019) for the carbon-climate and CO2 fertilization effects are going to be developed within the “Climate-Carbon Interactions in the Coming Century” (CCiCC) project that is funded by the EU under the Horizon 2020 program. Further research within CCiCC includes the analysis of new data sets and recommendations for model improvements and observational strategies.

Related projects:

Advanced Earth System Model Evaluation for CMIP (EVal4CMIP)

Climate-Carbon Interactions in the Coming Century (CCiCC)

Coupled Model Intercomparison Project (CMIP)

Further reading:

Buchwitz, M., Reuter, M., Schneising, O., Noel, S., Gier, B., Bovensmann, H., Burrows, J.P., Boesch, H., Anand, J., Parker, R.J., Somkuti, P., Detmers, R.G., Hasekamp, O.P., Aben, I., Butz, A., Kuze, A., Suto, H., Yoshida, Y., Crisp, D., & O'Dell, C. (2018). Computation and analysis of atmospheric carbon dioxide annual mean growth rates from satellite observations during 2003-2016. Atmospheric Chemistry and Physics, 18

Eyring, V., Bony, S., Meehl, G.A., Senior, C.A., Stevens, B., Stouffer, R.J., & Taylor, K.E. (2016a). Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9, 1937-1958

Eyring, V., Cox, P.M., Flato, G.M., Gleckler, P.J., Abramowitz, G., Caldwell, P., Collins, W.D., Gier, B.K., Hall, A.D., Hoffman, F.M., Hurtt, G.C., Jahn, A., Jones, C.D., Klein, S.A., Krasting, J.P., Kwiatkowski, L., Lorenz, R., Maloney, E., Meehl, G.A., Pendergrass, A.G., Pincus, R., Ruane, A.C., Russell, J.L., Sanderson, B.M., Santer, B.D., Sherwood, S.C., Simpson, I.R., Stouffer, R.J., & Williamson, M.S. (2019). Taking climate model evaluation to the next level. Nature Climate Change, 9, 102-110

Eyring, V., Gleckler, P.J., Heinze, C., Stouffer, R.J., Taylor, K.E., Balaji, V., Guilyardi, E., Joussaume, S., Kindermann, S., Lawrence, B.N., Meehl, G.A., Righi, M., & Williams, D.N. (2016b). Towards improved and more routine Earth system model evaluation in CMIP. Earth System Dynamics, 7, 813-830

Eyring, V., Righi, M., Lauer, A., Evaldsson, M., Wenzel, S., Jones, C., Anav, A., Andrews, O., Cionni, I., Davin, E.L., Deser, C., Ehbrecht, C., Friedlingstein, P., Gleckler, P., Gottschaldt, K.D., Hagemann, S., Juckes, M., Kindermann, S., Krasting, J., Kunert, D., Levine, R., Loew, A., Makela, J., Martin, G., Mason, E., Phillips, A.S., Read, S., Rio, C., Roehrig, R., Senftleben, D., Sterl, A., van Ulft, L.H., Walton, J., Wang, S.Y., & Williams, K.D. (2016c). ESMValTool (v1.0) - a community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP. Geoscientific Model Development, 9, 1747-1802

Wenzel, S., Cox, P.M., Eyring, V., & Friedlingstein, P. (2016). Projected land photosynthesis constrained by changes in the seasonal cycle of atmospheric CO2. Nature, 538, 499-501

July 2019:

Figure 1 (click to enlarge)

Time series of annual mean total ozone (DU) in (a)–(d) four zonal bands, and (e) polar (60°–90°) total ozone in Mar (NH) and Oct (SH), the months when polar ozone losses usually are largest. Data are from WOUDC (World Ozone and Ultraviolet Radiation Data Centre) ground-based measurements combining Brewer, Dobson, SAOZ (Système D'Analyse par Observations Zénithales), and filter spectrometer data (red); the BUV/SBUV/SBUV2 V8.6/OMPS merged products from NASA (MOD V8.6, dark blue) and NOAA (light blue), the GOME/SCIAMACHY/GOME-2 products GSG from University of Bremen (dark green) and GTO from ESA/DLR (light green). MSR-2 (purple) assimilates nearly all ozone datasets after corrections with respect to the ground data. All six datasets have been bias corrected by subtracting averages for the reference period 1998–2008 and adding back the mean of these averages. The dotted gray lines in each panel show the average ozone level for 1970–79 calculated from the WOUDC data. Update from Weber et al. (2018b).

Midlatitude total ozone means were high in 2018, while the tropical values were low compared to the annual means observed in the recent decade as seen in Fig. 1, which shows the annual mean total ozone time series from various merged datasets (five satellite datasets and one based upon groundbased instruments) for the near-global (60°N–60°S) average, tropics, extratropics, and selected months in the polar regions.

For all latitude bands, except the tropics, the average total ozone levels have not yet recovered to the values of the 1970s, a time when ozone losses due to ozone-depleting substances (ODSs) were still very small (WMO 2018). Total ozone is defined as the vertical column amount or in other words the number of ozone molecules above a unit area. Typical units are Dobson units (DU) and the global average column amount is about 300 DU. The lower the ozone column, the higher is the amount of harmful UV radiation reaching the surface that can damage plant cells as well as cause skin cancer.

A recent study by us (Weber et al. 2018a) indicates that total ozone trends since the late 1990s are positive (<1% decade−1) but at most latitudes the trends do not reach statistical significance. Still, the small increase in global total ozone following the significant decline before the 1990s provides proof that the Montreal Protocol and its later Amendments, responsible for phasing out ozone-depleting substances, has been successful. The observed changes in total ozone are reproduced well by state-of-the-art chemistry-transport model calculations that account for changes in transport and for changes in the ozone-depleting substances regulated by the Montreal Protocol (Chipperfield et al. 2018).

In Figure 1 one of the satellite merged data were produced in our institute (GSG dataset) that combines various European sensors (GOME, SCIAMACHY, GOME-2A) that were retrieved with the WFDOAS (weighting function differential absorption spectroscopy) retrievals (Coldewey-Egbers et al., 2005). The European time series started in 1995 and in 2017 and 2018 two new sensors were launched, TROPOMI and GOME-2C, respectively. Both instruments will continue long-term ozone monitoring. In particular TROPOMI provides measurements at an unprecedented spatial resolution corresponding to a foot print of 3.5 km by 7 km at the surface.

Figure 2 shows the total ozone distribution above Antarctica from 1stOctober 2018. In early October the ozone hole reaches its largest extent. In 2018 the size of the ozone hole (defined by values below 220 DU) was higher than the average from recent years. However, the extent of the ozone hole varies from year-to-year depending on the polar meteorology (colder stratospheric winters produce larger ozone holes) as seen in panel e of Fig. 1. Nevertheless, there are signs that spring time total ozone above Antarctica is beginning to recover (Weber et al., 2018, WMO 2018).


References:

Chipperfield, M. P., Dhomse, S., Hossaini, R., Feng, W., Santee, M. L., Weber, M., Burrows, J. P., Wild, J. D., Loyola, D., Coldewey-Egbers, M, 2018: On the Cause of Recent Variations in Lower Stratospheric Ozone. Geophys. Res. Lett., 45, 5718-5726, https://doi.org/10.1029/2018GL078071.

Coldewey-Egbers, M., M. Weber, L. N. Lamsal, R. de Beek, M. Buchwitz, J. P. Burrows, 2005: Total ozone retrieval from GOME UV spectral data using the weighting function DOAS approach.Atmos. Chem. Phys. 5, 5015-5025, https://doi.org/10.5194/acp-5-1015-2005.

Weber, M., Coldewey-Egbers, M., Fioletov, V. E., Frith, S. M., Wild, J. D., Burrows, J. P., Long, C.
S., and Loyola, D., 2018a: Total ozone trends from 1979 to 2016 derived from five merged
observational datasets – the emergence into ozone recovery. Atmos. Chem. Phys., 18, 2097-2117,
https://doi.org/10.5194/acp-18-2097-2018.

Weber, M., Steinbrecht, W., van der A, R., Frith, S. M., Anderson, J., Coldewey-Egbers, M., Davis, S,
Degenstein, D., Fioletov, V., Froidevaux, L., Hubert, D., de Laat, J., Long, C. S., Loyola, D., Sofieva,
V., Tourpali, K., Roth, C., Wang, R., and Wild, J.D., 2018b: Stratospheric ozone [in "State of the
Climate in 2017"], Bull. Amer. Meteor. Soc., 99, S51-S54,
https://doi.org/10.1175/2018BAMSStateoftheClimate.1.

WMO, 2018: World Meteorological Organization/United Nations of Environmental Protection,
Scientific assessment of ozone depletion, 2018. Global Ozone Research and Monitoring Project–
Report No. 58, Geneva, Switzerland, available at https://www.esrl.noaa.gov/csd/assessments/ozone/.

Figure 2

Total ozone above Antarctica on October 1st, 2018, for S5P/TROPOMI. The data were retrieved using our WFDOAS approach (see main text). The data as shown are binned at a spatial resolution of 0.1° by 0.1°.

April 2019:

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The extent of the sea ice around Antarctica has a marked seasonal cycle

The extent of the sea ice around Antarctica has a marked seasonal cycle; the maximum is usually reached around September (at the end of austral winter), and the minimum in late February (at the end of austral summer). This year's minimum was reached in the last week of February. According to the sea ice data produced at IUP from satellite data (microwave radiometer AMSR2 on the Japanese satellite GCOM-W2), the lowest daily sea ice extent was 2.54 million km2 on February 23, 2019. By extent we mean the total area of all satellite pixels covered by at least 15% of sea ice.

The largest portion of remaining sea ice is, as usual, sitting in the Weddell Sea, where it is pushed towards the Antarctic Peninsula by the Weddell Gyre (middle figure). This can be compared with last year's ice extent maximum on 30 September 2018 (upper figure). The amplitude of the seasonal cycle in ice extent is more than 15 million km2, i.e. 1.5 times the size of Europe.Comparison with the other Antarctic sea ice minima since the beginning of satellite observations in 1978 (lower figure) shows that this year's minimum is low but not unique – the absolute minimum on record was in 2017. However, after an overall increase in Antarctic sea ice extent until about 2013 the last years show a strong decrease in both summer and winter.

Publications:

Spreen, G., L. Kaleschke, and G.Heygster (2008), Sea ice remote sensing using AMSR-E 89 GHz channels ,vol. 113, C02S03, doi:10.1029/2005JC003384.

AMSR2 ASI sea ice concentration data, Antarctic, version 5.4 (NetCDF) (July 2012 - December 2018). , https://doi.pangaea.de/10.1594/PANGAEA.898400


Projects:

Sea ice type distribution in the Antarctic from microwave satellite observations (SITAnt), (https://seaice.uni-bremen.de/sitant/)

March 2019:

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A bottom echo sounder (PIES) is fixed on deck and prepared for deployment. The instrument will stay in about 4000m depth for up to four years and measure every half hour the state of the ocean.

February 2019:

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Average extinction (top) and NO2 concentration (bottom) profiles, separated by day of the week as retrieved from measurements from the roof of IUP Bremen for May 2015 – September 2017. The lowest rows indicate the in situ concentrations from the Bremen air quality network BLUES site Oslebshausen with a second colour-scale on the right-hand side. The red lines show BOREAS aerosol optical depth (top) and NO2 vertical column (bottom) with the mean level depicted as dashed line.

Ground based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations are a frequently used method to determine atmospheric column amounts of reactive gases such as ozone, nitrogen dioxide or formaldehyde. By probing the atmosphere at different elevation angles, information on the vertical distribution of these absorbers can be determined, as well as on aerosol extinction. In order to extract the profile information from the observations taken at different elevation angles, inversion algorithms are needed which combine a priori information with the information from the measurements.

The Bremen Optimal estimation REtrieval for Aerosols and trace gaseS (BOREAS) is a new, flexible profiling algorithm which combines a non-linear aerosol retrieval module with a trace gas retrieval part. Both Optimal Estimation and Levenberg Marquardt approaches are implemented, and many options for a priori selection and pre-scaling, smoothing constraints, and retrieval modes are implemented. Results from BOREAS have been compared to those from other state of the art retrievals in an extensive study using synthetic data (Frieß et al., 2018) and using measurements during the CINDI-2 campaign (Tirpitz et al., manuscript in preparation) demonstrating the good performance of the algorithm. More details on BOREAS and its validation can be found in Bösch et al., 2018.

References:

Bösch, T., Rozanov, V., Richter, A., Peters, E., Rozanov, A., Wittrock, F., Merlaud, A., Lampel, J., Schmitt, S., de Haij, M., Berkhout, S., Henzing, B., Apituley, A., den Hoed, M., Vonk, J., Tiefengraber, M., Müller, M., and Burrows, J. P.: BOREAS – a new MAX-DOAS profile retrieval algorithm for aerosols and trace gases, Atmos. Meas. Tech., 11, 6833-6859, https://doi.org/10.5194/amt-11-6833-2018, 2018.

Frieß, U., Beirle, S., Alvarado Bonilla, L., Bösch, T., Friedrich, M. M., Hendrick, F., Piters, A., Richter, A., van Roozendael, M., Rozanov, V. V., Spinei, E., Tirpitz, J.-L., Vlemmix, T., Wagner, T., and Wang, Y.: Intercomparison of MAX-DOAS Vertical Profile Retrieval Algorithms: Studies using Synthetic Data, Atmos. Meach. Teech. Discuss., https://doi.org/10.5194/amt-2018-423, in review, 2018.

BLUES - Das Bremer Luftüberwachungssystem https://www.bauumwelt.bremen.de/umwelt/luft/luftqualitaet-24505

January 2019:

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First estimate of the CO2 year 2018 growth rate from satellites

Carbon dioxide (CO2) is an important greenhouse gas and increasing atmospheric concentrations lead to global warming. The IUP of the University of Bremen develops methods to measure the atmospheric CO2distribution from space.

The picture shows in (a) time series of the vertically averaged CO2mixing ratio (“XCO2”) including preliminary values for 2018. One can see that CO2increases approximately linearly with time. This is primarily due to burning of fossil fuels. The seasonal fluctuations are primarily due to uptake and release by vegetation. The time series have been computed from satellite data, which also show the spatial distribution (see maps in (c)). The XCO2unit is ppm (parts per million). 400 ppm means that the atmosphere contains on average 400 CO2molecules per one million air molecules.

In (c) the annual mean XCO2 growth rate is shown. As can be seen, the growth rate varies somewhat from year to year. A reason for this are fluctuations of the natural CO2 sinks (e.g., forests) or increasing emissions including emissions from wildfires. The preliminary estimate of the growth rate for 2018 is 2.5 ppm/year (uncertainty range +/- 0.8 ppm/year). This is somewhat less than in 2015 and 2016 (two years with weaker than average sinks and significant wildfires partly due to the natural climate phenomenon El Niῆo) but somewhat less than 2017. Future refined analysis will show to what extent this preliminary estimate is confirmed.

Press:

Copernicus (7-Jan-2019): Press release: “Last four years have been the warmest on record – and CO2continues to rise” URL: https://climate.copernicus.eu/last-four-years-have-been-warmest-record-and-co2-continues-rise

EuroNews (14-Dec-2018): Video: “Temperatures in November above average” URL: https://www.euronews.com/2018/12/14/temperatures-in-november-above-average

Publications:

Buchwitz, M., Reuter, M., Schneising, O., Noel, S., Gier, B., Bovensmann, H., Burrows, J. P., Boesch, H., Anand, J., Parker, R. J., Somkuti, P., Detmers, R. G., Hasekamp, O. P., Aben, I., Butz, A., Kuze, A., Suto, H., Yoshida, Y., Crisp, D., and O'Dell, C., Computation and analysis of atmospheric carbon dioxide annual mean growth rates from satellite observations during 2003-2016, Atmos. Chem. Phys., 18, 17355-17370, https://doi.org/10.5194/acp-18-17355-2018, 2018. URL: https://www.atmos-chem-phys.net/18/17355/2018/

Heymann, J., M. Reuter, M. Buchwitz, O. Schneising, H. Bovensmann, J. P. Burrows, S. Massart, J. W. Kaiser, D. Crisp, CO2emission of Indonesian fires in 2015 estimated from satellite-derived atmospheric CO2concentrations, Geophys. Res. Lett., DOI: 10.1002/2016GL072042, pp. 18, 2017. URL: http://onlinelibrary.wiley.com/doi/10.1002/2016GL072042/full

December 2018:

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XCO2 Seasonal Cycle Amplitude from CMIP5 models and satellite observations


The left side of the figure shows the mean seasonal cycle amplitude of column-averaged dry-air mole fraction of CO2(XCO2) for satellite observations and the multi-model mean calculated from 10 Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) for the years 2003-2016. The models are sampled the same way as the observations. The observations (Buchwitz et al., 2018) combine measurements of SCIAMACHY (SCanning Imaging Absorption Spectrometer for Atmospheric CHartographY) on Envisat and TANSO-FTS (Thermal And Near infrared Sensor for carbon Observation - Fourier Transform Spectrometer) on GOSAT (Greenhouse gases Observing SATellite). The seasonal cycle amplitude is defined as the peak-to-troughamplitude in a calendar year of the detrended time series.

Both models and observations show characteristic seasonal cycles in CO2, with lower values in the summer when strong photosynthesis causes plants to absorb CO2, and higher values in the winter when photosynthesis stops. The peak-to-trough amplitude of the seasonal cycle therefore depends on the strength of the summer photosynthesis and the duration of the growing season and is larger in the Northern than in the Southern Hemisphere.A study in the journal Nature shows that doubling of the CO2concentration in the atmosphere will cause global plant photosynthesis to further increase by approximately one third (Wenzel et al., 2016).

On the right side, following Schneising et al. (2014), the influence of the growing season temperature anomaly on the seasonal cycle amplitude for the northern mid-latitudes (30-60°N) is shown for the observations and the multi-model mean. The growing season temperature anomaly is defined as the temperature anomaly with respect to the monthly climatology averaged over the growing season (April to September for the Northern Hemisphere). Only vegetated areas are used, identified by the MODIS Land Cover Classification. The multi-model mean is able to reproduce the observed correlation and negative trend of the seasonal cycle amplitude with increasing growing season temperature.

The data are analyzed as part of the Advanced Earth System Model Evaluation for CMIP (EVal4CMIP) project funded by the Helmholtz Society. All data are processed and combined using the Earth System Model Evaluation Tool (ESMValTool, Eyring et al. (2016)), an open-source community-developed diagnostics and performance metrics tool for the systematic evaluation of ESMs with observations.

Related projects:

Advanced Earth System Model Evaluation for CMIP (EVal4CMIP)
Coupled Model Intercomparison Project (CMIP)

Further reading:

Buchwitz, M., Reuter, M., Schneising, O., Noël, S., Gier, B., Bovensmann, H., Burrows, J.P., Boesch, H.,
Anand, J., Parker, R.J., Somkuti, P., Detmers, R.G., Hasekamp, O.P., Aben, I., Butz, A., Kuze, A., Suto, H., Yoshida, Y., Crosp, D., O'Dell, C.Computation and analysis of atmospheric carbon dioxide annual mean growth rates from satellite observations during 2003-2016. Atmospheric Chemistry and Physics
Discussions, 1-22, doi:10.5194/acp-2018-158, 2018.


Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization ,
Geosci. Model Dev., 9, 1937-1958, doi:10.5194/gmd-9-1937-2016, 2016a.

Eyring, V., Righi, M., Lauer, A., Evaldsson, M., Wenzel, S., Jones, C., Anav, A., Andrews, O., Cionni, I.,
Davin, E. L., Deser, C., Ehbrecht, C., Friedlingstein, P., Gleckler, P., Gottschaldt, K.-D., Hagemann, S.,
Juckes, M., Kindermann, S., Krasting, J., Kunert, D., Levine, R., Loew, A., Mäkelä, J., Martin, G., Mason,
E., Phillips, A. S., Read, S., Rio, C., Roehrig, R., Senftleben, D., Sterl, A., van Ulft, L. H., Walton, J., Wang, S., and Williams, K. D.: ESMValTool (v1.0) – a community diagnostic and performance metrics tool forroutine evaluation of Earth system models in CMIP , Geosci. Model Dev., 9, 1747-1802, doi:10.5194/gmd-9-1747-2016, 2016b.

Eyring, V., Gleckler, P. J., Heinze, C., Stouffer, R. J., Taylor, K. E., Balaji, V., Guilyardi, E., Joussaume, S., Kindermann, S., Lawrence, B. N., Meehl, G. A., Righi, M., and Williams, D. N.: Towards improved andmore routine Earth system model evaluation in CMIP, Earth Syst. Dynam., 7, 813-830,
doi:10.5194/esd-7-813-2016, 2016c.

Schneising, O., Reuter, M., Buchwitz, M., Heymann, J., Bovensmann, H., and Burrows, J. P., Terrestrial
carbon sink observed from space: variation of growth rates and seasonal cycle amplitudes in
response to interannual surface temperature variability, Atmospheric Chemistry and Physics, 14(1),
133-141, doi:10.5194/acp-14-133-2014, 2014.

Wenzel, S., Cox, P. M., Eyring, V ., and Friedlingstein, P.: Projected land photosynthesis constrained bychanges in the seasonal cycle of atmospheric CO2, Nature, doi: 10.1038/nature19772, 2016.


Text: Veronika Eyring, Bettina Gier and Katja Weigel
Graphics: Bettina Gier


November 2018:

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The figure above presents the multiannual (1994-2014) simulated ozone vertical distribution for the Easter Island in Chile, using the TM4-ECPL model. a) Location of Rapa Nui (Easter Island) in the Pacific Ocean. b) The iconic statues of the island (Moai). c) TM4-ECPL values of ozone column in Rapa Nui. d) Measured values for ozone (ozonesondes). e) Mean vertical distribution of ozone using concurrent available measurements (gray line) and modelled data (green line). The vertical dashed line set at 150 ppb of ozone represents the chemical tropopause. Standard deviation of all used data is shown with the horizontal lines (green for modeled values and grey for measurements).

Text: Dr. Nikos Daskalakis and Prof. Mihalis Vrekoussis (LAMOS/IUP)

Image:

a) Easter Island map (a), ozone sonde data and back trajectories:Laura Gallardo, Adolfo HenrÍquez, Anne M. Thompson, Roberto Rondanelli, Jorge Carrasco, Andrea Orfanoz-Cheuquelaf & Patricio Velásquez (2016). The first twenty years (1994–2014) of ozone soundings from Rapa Nui (27°S, 109°W, 51 m a.s.l.), Tellus B: Chemical and Physical Meteorology, 68:1,DOI: 10.3402/tellusb.v68.29484

b) Moai picture (b): Matías Morel [CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0)], from Wikimedia Commons

c) Plots (c), (d) and (e): Dr. Nikos Daskalakis (IUP) from original data.

Modelling of the ozone vertical distribution

Introduction-Motivation: Modelling of ozone is a difficult task, since there are no direct ozone emissions. It is a purely secondary pollutant, chemically produced in the atmosphere. The main removal processes consist of chemical transformation and dry deposition. To simulate the vertical distribution of ozone in the troposphere, we need to properly account for both precursor species amounts (CO, NOx etc) and production/removal processes.

For this work, we used the highly documented TM4-ECPL model (Daskalakis et al., ACP, 2016 and references therein). TM4-ECPL is a Chemistry and Transport Model (CTM) with an analytical chemical scheme consisting of ~280 reactions involving 120 tracers (Myriokefalitakis et al., ACP, 2008, 2011). The model is driven by the ERA-Interim meteorology from ECMWF (Dee et al., GMD, 2011) and uses a variety of emissions covering all different sources (anthropogenic, biomass burning, biogenic, marine and soil).

Here we compare the simulated TM4-ECPL ozone concentrationsover the Easter Island (Rapa Nui) to the collocated time series of ozone sondes. Easter Island is chosen as a representative background site of the Southern Pacific region; making such a comparison extremely important for the understanding of the modeled processes. Such a remote location has minimal local anthropogenic impact on ozone precursor levels. This is supported by back trajectories of the region, which show that the air masses reaching the island come mainly from the west, being influenced mostly by the vast ocean (Gallardo et al., Tellus B, 2016).

The model-measurements comparison revealed that the model simulates correctly the seasonality of ozone levels. However, at the same time the comparison also pointed to model’s inability to simulate the tropopause height (panel (e)). The model simulates a higher tropopause affecting this way the mixing of the atmosphere. It manages to capture stratospheric ozone intrusions events that we see from the measurements with higher ozone values well below the tropopause, down to almost 10 km altitude (13 km altitude in the model). To further explain the ozone levels, the impact of long-range transport, wildfires and the El Niño-Southern Oscillation (ENSO) needs to be addressed.

October 2018

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Internal wave energy fluxes in a tidal beam south of the Azores

Internal gravity waves in the ocean are generated by tides, wind, and interaction of currents with rough seafloor topography. Models predict a global energy supply for the internal wave field of about 0.7–1.3 TW by the conversion of barotropic tides at mid-ocean ridges and abrupt topographic features. Winds acting on the oceanic mixed layer contribute 0.3–1.5 TW and mesoscale flow over rough topography adds an additional amount of 0.2 TW. Globally, 1–2 TW are needed to maintain the observed stratification of the deep ocean by diapycnal mixing that results from the breaking of internal waves. Observations indicate that the energy available for mixing is redistributed by internal tides and near-inertial waves at low vertical wavenumber that can propagate thousands of kilometers from their source regions. While eddy-permitting global ocean circulation models are partly able to quantify the different sources of energy input and to simulate the propagation of the lowest internal wave modes, the variation and dissipation of the internal wave energy flux along its paths needs to be parameterized.

The figure shows results from an experiment south of the Azores, where a seamount chain is a major generation site of internal waves. The waves emanate from the seamounts a relatively narrow tidal beam, which makes the area an ideal observation site for the processes acting on the waves. The schematic shows the bathymetry of the seamounts on the right side, with the amplitude patternof the tidal beam as observed from satellite altimetry indicated in red and blue. Our instrumentation to observe the associated internal wave fluxes are the CTD/LADCP system below the ship (used for time series stations), and a long-term current meter/temperature logger mooring to observe temporal variability within the beam. The data shown are (bottom) an excerpt from the fluxes recorded by the mooring, decomposed into wave modes, and the corresponding predicted tidal velocity, and (top right) the internal wave signal in velocity (upper panel) and stratification (lower panel) observed during the time series stations, unfiltered (left), and filtered for the M2 internal tide (right) fluctuations.


Project:

TRR181 Energy Transfers in Atmosphere and Ocean (https://www.trr-energytransfers.de), Subproject W2: 'Energy transfer through low mode internal waves' Monika Rhein (MARUM/IUP, University of Bremen), Jin-Song von Storch (MPI for Meteorology, Hamburg) DFG

August 2018:

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Müller-Dum, D., Warneke, T., Rixen, T., Müller, M., Baum, A., Christodoulou, A., Oakes, J., Eyre, B. D., and Notholt, J.: Impact of peatlands on carbon dioxide (CO2) emissions from the Rajang River and Estuary, Malaysia, Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-391, in review, 2018.

Carbon Dioxide Emissions from Southeast Asian Rivers

How much carbon dioxide (CO2) is released from Southeast Asian rivers? At the Institute of Environmental Physics (IUP), we have investigated this question in close collaboration with the Leibniz Center for Tropical Marine Research (ZMT), Bremen, and with the Swinburne University of Technology in Kuching, Malaysia. Our recent work, supported by the Central Development Research Fund of the University of Bremen, focused on the Rajang River, the longest river in Malaysia on the island of Borneo. It flows through mountainous terrain, tropical rainforests, oil palm plantations and peatlands. Southeast Asian peatlands store large amounts of organic carbon. It is expected that this carbon is released to the adjacent rivers, converted to CO2 and released to the atmosphere from the water surface. However, due to the proximity of the peatlands to the coast, the material is swiftly transported to the ocean, and CO2 emissions from Southeast Asian rivers are actually much lower than predicted. This was confirmed by our research at the Rajang River.

The left images are photographs of our scientists and students at work. The right image displays the measured partial pressure of CO2 (pCO2, in µatm) in the Rajang River. Peat areas are shown in dark colors. It can be seen that pCO2 increases as the river flows through the peat area, but soon decreases towards the river mouth due to mixing with seawater.

Our current knowledge of Southeast Asian river systems is mainly based on these kind of sampling campaigns. They can be realized in short term at relatively low cost and allow to resolve spatial patterns of carbon dynamics in a river. In order to better constrain the temporal variability of carbon fluxes in peat-draining rivers, it would be desirable to have additional long-term monitoring data. A new project, funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), will look into the use of satellites to monitor the amount of riverine dissolved organic carbon (DOC), which is one of the most important drivers of CO2 emissions.

Related Projects:

‘Integrating field measurements and numerical modeling in order to understand carbon dynamics in Southeast Asian rivers’, awarded to Denise Müller-Dum (IUP), CDRF (Uni Bremen)
‘Studying dissolved organic carbon in tropical rivers of Malaysia using in-situ and satellite observations’, awarded to Justus Notholt (IUP), Thorsten Warneke (IUP), Tim Rixen (ZMT), DFG

Text and Images: Denise Müller-Dum (IUP) and Moritz Müller (Swinburne University of
Technology, Malaysia)

June 2018:

Text and Image: Carlo Arosio

click to enlarge

The left panel shows long-term changes in zonal monthly mean ozone in the stratosphere over the 2003-2017 period as a function of altitude and latitude. Values are reported in % per decade and shaded areas indicate non-significant trends. The right panel shows the longitudinally resolved long-term changes at an altitude of 38 km, displaying a remarkable variability. These plots confirm a significant increase of ozone concentration at mid latitudes in the upper stratosphere, whereas, in the middle stratosphere down to 20 km the long-term changesare generally not significant.

The observed increase of ozone concentration around 35-45 km is attributed by recent studies to two main causes; the first one is the decreasing concentration of ozone depleting substances after the production and use of CFCs have been regulated by the Montreal Protocol and its amendments. The second explanation is related to the increasing concentration of greenhouse gases responsible for the recorded global tropospheric warming. Due to radiative processes, this leads to a stratospheric cooling that in turn impacts on the ozone chemistry, increasing its production efficiency at these altitudes. Changes in the stratospheric circulation also have a strong influence on the latitudinal and vertical distribution of ozone and its trends.

In order to obtain a long term record of ozone profiles and study the long-term changes, SCIAMACHY and OMPS Limb Profiler stratospheric ozone data sets have been retrieved and merged at the University of Bremen. Since the overlap of the two satellite missions is only 3 months at the beginning of 2012, a reference time series for the merging has been used. Data from the NASA Aura-MLS instrument have been chosen for this purpose, as the instrument performs limb observations with a broad latitude coverage and it is considered stable and reliable.

Trends have been computed using a multilinear regression model, accounting for all phenomena having a strong impact on stratospheric ozone on different temporal and spatial scale: the solar activity, the quasi-biennial oscillation, El Nino and seasonal terms with a period of 6 and 12 months.

May 2018:

Atmospheric CO2 reaches new high-water mark

Satellite data show that northern hemispheric CO2 has exceeded 410 parts per million (ppm) in April 2018. Globally approximately 407.6 ppm has been reached. These are the highest atmospheric CO2concentrations since at least 800000 years.

The figure presents time series of atmospheric CO2 mixing ratios for the entire world (black and grey lines), for the northern hemisphere (red) and for the southern hemisphere (green). Shown are monthly mean column-averaged molecular mixing ratios of CO2 (“XCO2”) as retrieved from satellite measurements.

The lines shown in pale colours (recent years) correspond to preliminary time series generated in Near-Real-Time (NRT) whereas the bright colours show a high-quality Climate Data Record (CDR) currently covering the time period 2003-2016.

All curves show an increasing trend due to increasing concentrations of atmospheric CO2 originating primarily from the burning of fossil fuels (coal, oil, gas). The seasonal variations within each year are primarily due to uptake and release of CO2 by vegetation (photosynthesis, respiration, decay of organic matter). As can be seen, the largest variations are over the northern hemisphere (red line), where most of the terrestrial vegetation is located. The northern hemispheric CO2 maximum is typically reached in May. After that CO2concentrations will decrease because the growing plants will take up large amounts of CO2from the atmosphere.

The satellite-derived CO2 time series have been generated at the Institute of Environmental Physics (IUP) of the University of Bremen, Germany. They have been derived from spectroscopic measurements of the European satellite instrument SCIAMACHY on Envisat (2002-2012) and from TANSO-FTS onboard the Japanese GOSAT satellite (since 2009).

The underlying retrieval algorithms and corresponding CO2 data products have been generated in the framework of three European projects: the GHG-CCI project of ESA’s Climate Change Initiative and the EU projects Copernicus Climate Change Service (C3S) and Copernicus Atmosphere Monitoring Service (CAMS).

The CAMS data product (pale colours, recent years) is generated in quasi near-real-time at University of Bremen for the European Centre for Medium-Range Weather Forecasts (ECMWF) for CO2 forecasting and other applications within CAMS.

The bright colours show a Climate Data Record (2003-2016) generated at University of Bremen for C3S, which will be extended each year by one additional year. This data product is based on merging several high-quality data products generated in Europe (by University of Bremen, SRON and University of Leicester), in Japan (by the National Institute for Environmental Studies (NIES)) and in the USA (by NASA’s CO2 ACOS team). The merging algorithm has been developed at University of Bremen in order to generate a data product with the highest possible data quality for challenging carbon and climate applications.

The satellite CO2 observations are mean molecular mixing ratios (or mole fractions) of CO2 with respect to dry air averaged over the entire vertical extent of the atmosphere. 410 parts per million means that on average 1 million air molecules (excluding water vapour) contain 410 CO2 molecules in the air above a given location. Note that these column-averaged observations are similar but not identical to CO2 measurements at the surface carried out, for example, by NOAA.

Monitoring of the atmospheric CO2 concentration is important because increasing atmospheric concentrations lead to global warming as CO2 is an important greenhouse gas. Before the industrial revolution, the atmospheric concentration of CO2 was below approximately 280 ppm for at least the last 800000 years. Since then the amount of atmospheric CO2 has increased by more than 40%. The goal of the Paris Agreement on Climate Change is to reduce emissions of greenhouse gases to limit global warming to less than 2 degrees Celsius - or even better to less than 1.5 degrees - with respect to pre-industrial times. Achieving this goal requires a major international effort. It is currently unclear if this goal can be reached.

Text and Images: Michael Buchwitz, Maximilian Reuter, Stefan Noël

April 2018:

Further investigation on megacities: EMeRGe HALO campaign in East Asia

The measurement campaign of the project EMeRGe (Effect of Megacities on the Transport and Transformation of Pollutants on the Regional and Global Scales) in East Asia started in March 2018 and will continue till 09.04.2018.

EMeRGe (http://www.iup.uni-bremen.de/emerge/), led by the Institute of Environmental Physics of the University of Bremen,aims at improving the knowledge and prediction of the transport and transformation patterns of European and Asian pollutant outflows of megacities by using the HALO research aircraft (www.halo.dlr.de). The first measurement campaign in Europe was successfully carried out in summer 2017.

The HALO payload for EMeRGe combines in situ and remote sensing instruments measuring O3and aerosol precursors, aerosol amounts and composition. This information, which is gathered following optimal HALO transects and vertical profiling, enables the investigation of the photochemical evolution of the megacity plumes, the lifetime of the emissions and the transport of the air masses.

For the second EMeRGe campaign in East Asia, HALO left Germany on the 07.03 to reach its airbase in Tainan (Taiwan) where it will stay till the 7.04.2018. Around 140 flight hours will be flown to investigate the transport and transformation of emissions from the megacities Manila, Taipei, Seoul, Tokyo, Beijing, Shanghai and Guangzhou. Already 10 flights have been successfully performed in March 2018.

EMeRGe additionaly stimulates measurements and modelling studies within an international best effort research partnership with the European, Asian, and American science community. More than 50 partners from 16 different countries are participating in EMeRGe international. From them 27 are Asian partners. EMeRGe international facilitates a much more comprehensive integrated analysis of all sets of observational data products (i.e. aircraft, ground and satellite based data) in the study of the transport and transformation of plumes from MPCs.

Text and Images: Lola Andres Hernandez

March 2018:

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Nitrogen dioxide total columns derived from measurements of the GOME2B instrument (left) and the Sentinel-5 precursor (right) for November 29, 2017. The large increase in spatial resolution at comparable signal to noise ratio makes the data much more useful for air pollution applications.

First NO2 results from the Sentinel-5 Precursor

On October 13, 2017, the Sentinel-5 precursor (S5P), the first of the atmospheric Copernicus instruments was successfully launched into an afternoon low earth orbit. The TROPOMI instrument on-board of this satellite continues the atmospheric remote sensing measurements of the GOME, SCIAMACHY, OMI and GOME-2 instruments. The main data products are O3, NO2, HCHO, CO, CH4 and cloud and aerosol information, but additional data products are possible and are currently being developed at several institutes, including IUP Bremen. Compared to previous instruments, S5P combines global coverage with excellent spatial resolution of 3.5 x 7 km2 (7 x 7 km2 in the SWIR), resulting in an unprecedented level of detail of the derived global maps.

The instrument is still in commissioning phase and official release of operational data is foreseen for July 2018. However, first spectra and lv2 products have already been made available to the core team and validation groups, and so far, data quality appears to be very good. Using the verification algorithms developed over the last years, IUP Bremen has used S5-P radiances and irradiances to produce first maps of CO, CH4, NO2, HCHO, H2O and BrO, all of which show good quality and interesting details.

As an example, data from one S5P overpass over Germany on November 29, 2017 is shown in the figure.


Disclaimer: The presented work has been performed within the framework of the Sentinel-5 Precursor Level 1/Level 2 Product Working Group activities. Results are based on preliminary (not fully calibrated/validated) Sentinel-5 Precursor data that are still subject to change.

Acknowledgement: Sentinel-5 Precursor is a European Space Agency (ESA) mission on behalf of the European Commission (EC). The TROPOMI payload is a joint development by ESA and the Netherlands Space Office (NSO). The Sentinel-5 Precursor ground-segment development has been funded by ESA and with national contributions from The Netherlands, Germany, and Belgium.

Links:
http://www.tropomi.eu/

January 2018:

Methane emissions from Landfills

For the first time, scientists of the Institute of Environmental Physics successfully conducted an independent verification of total landfill methane emissions using airborne remote sensing techniques.

During a measurement campaign in California, methane concentrations around a landfill were measured using remote sensing techniques and a standard in-situ technique.

With the help of new sophisticated data analysis techniques and a comparison of the remote sensing data with data obtained from standard measurement technique, they were able to demonstrate that remotely sensed methane concentration data acquired from aircraft are accurate enough to verify reported methane emissions from a landfill. For the landfill under study, good agreement between reported and independently determined emission was found.

During the measurement campaign in California, methane emissions from oil fields were also measured (see also picture of the month April 2015 [LINK]). This research was highlighted in the TV magazine PlusMinus recently (December 2017).
Currently, the researchers are developing the next generation of airborne methane remote sensors, with a much better precision for methane detection of localized emitters.

Contact: heinrich.bovensmann@uni-bremen.de

Publication:


Krautwurst, S., Gerilowski, K., Jonsson, H. H., Thompson, D. R., Kolyer, R. W., Iraci, L. T., Thorpe, A. K., Horstjann, M., Eastwood, M., Leifer, I., Vigil, S. A., Krings, T., Borchardt, J., Buchwitz, M., Fladeland, M. M., Burrows, J. P., and Bovensmann, H.: Methane emissions from a Californian landfill, determined from airborne remote sensing and in situ measurements, Atmos. Meas. Tech., 10, 3429-3452, https://doi.org/10.5194/amt-10-3429-2017, 2017

Link: https://www.atmos-meas-tech.net/10/3429/2017/

TV magazine ARD PlusMinus from 7.12.2017


http://www.daserste.de/information/wirtschaft-boerse/plusminus/sendung/plusminus-erdgasfoerderung100.html

December 2017:

Mooring deployment: (left)

The yellow top float houses an acoustic current profiler. It will be monitoring the currents in the upper 250 m. (centre) The smaller current meters are combined with temperature loggers to obtain time series of current velocity and temperature at the same depths. (right) The instruments are attached to floatation. The floatation holds the mooring upright in the water and brings it back to the surface at the end of the deployment period. To the left of the instruments is the 1.4 t anchor made of massive steel sheets.

Cruise 516 of the research vessel “Poseidon”

Text: Maren Walter, Christian Mertens
Photos: Florentina Münzner, Simon Rümmler

The cruise 516 of the research vessel Poseidon is part of the observational program of the Collaborative Research Center TRR 181 “Energy Transfers in Atmosphere and Ocean” (www.trr-energytransfers.de). During the three week cruise in July/August 2017 that started and ended in Ponta Delgada on the Azores, nine scientist and students from the Universities of Bremen and Hamburg were on board. The objective of the cruise was to measure energy fluxes along a tidal beam that emanates from the seamounts south of the Azores.

Waves and currents in the ocean are driven by winds and tides. These motions occur on all scales, ranging from basin wide currents to the millimeters of turbulence. The interaction between the different scales and the exchange of energy is not well understood. For example, tidal forcing at seamounts and continental shelves generates internal waves that could travel hundreds of kilometers through the ocean basins before they eventually disintegrate and dissipate. Their loss of energy is determined by a number of different processes and interactions, but the where and how of these processes is largely unknown. In project W2, we aim to better understand the propagation and dissipation of tidal energy in the oceans’ interior with the goal to better implement these processes in climate models.

To measure the internal wave energy fluxes, several time series stations were occupied along the tidal beam identified from satellite altimetry prior to the cruise. Each station lasted between 36 and 48 hours to observe the variability of currents and density associated with the semidiurnal as well as the diurnal tides. First results show a clear signal of the internal waves. The amplitude of the waves has a maximum between 800 m and 1300 m water depths, where the vertical excursions of the isopycnals are exceeding 100 m. To observe long-term temporal variability of the energy flux, a mooring was deployed within the tidal beam. It is equipped with current meters and temperature logger to record energy fluxes and their variations over the course of one year. It will be recovered during the next cruise in May 2018.

November 2017:

Image 1:

The 79-North-Glacier stretches from the Greenland mountains into the ocean. In the foreground, we see new sea ice with the trace of RV Polarstern on the left side.

Image 2:

To quantify the amount of glacial melt water in the ocean using noble gases (helium and neon) we store sea water samples from various depths in clamped off copper tubes that will be analyzed later at the IUP.

The strong temperature increase in the Nordic Seas causes the Greenland Glaciers to melt. In September and October 2017, members of the Department of Oceanography participated in an expedition on board the RV Polarstern. The objectives were to increase our understanding of the interaction between Arctic Ocean and Greenland Ice Sheets and Glaciers and to quantify the amount of glacial melt water flowing into the ocean. They took hundreds of seawater samples on the northeast Greenland shelf in front of the 79-Degree-North and the Zacharias Glacier. The samples will later be analyzed for the amount of helium and neon at the IUP noble gas lab. These trace gases allow to directly quantify the amount of glacial melt water in the ocean.

Text: Dr. Oliver Huhn, IUP, Bremen
Fotos: Dr. Tilia Breckenfelder, IUP+Marum, Bremen

October 2017:

Forschungsmeile 2017

This year, IUP participated again at the ‘Forschungsmeile’ during the ‘Maritime Woche 2017’ in Bremen. The working groups Physics and Chemistry of the Atmosphere, Remote Sensing and Oceanography presented on 23 and 24 September close to the Weser at the ‘Schlachte’ their current research areas to the public. Visitors could observe on-site measurements of air quality by the IUP mobile measurement truck. A specific highlight was the ‘Ice cube experiment’, which answered the question: Does an ice cube melt faster in fresh water or (salty) seawater? The possibly surprising answer is: In fresh water.

The explanation is that the cold melt water from the ice cube has a lower density, i.e. is lighter, than the salty seawater. It therefore builds a layer above the seawater, which keeps the ice cube cool. In fresh water, the cold melt water sinks down and mixes with the warmer fresh water. The ice cube therefore always stays in direct contact with warm fresh water and melts faster. Similar stratification is seen in the Arctic: Warm, more salty Atlantic water is separated from sea ice by a layer of fresh surface water.

Contact Gunnar Spreen (gunnar.spreen@uni-bremen.de) for more information on this topic.

September 2017:

Deployment

of a pressure inverted echo sounder from the research vessel Maria S. Merian. Photo: Dagmar Kieke

Salinity section

over the Atlantic from the Merian cruise in 2017 along 47°N from Canada (left) to Ireland (right). The salinity maxima at the surface mark branches of the North Atlantic Current, which transports warm, saline subtropical waters northward. The high salinity in the upper 1000 m at the eastern boundary originates from Mediterranean outflow water. At the western boundary, the Labrador Current transports very fresh surface water with contributions of melt water from the Arctic and Greenland southward. The low salinity water at the western boundary between 500 and 1500 m represents newly formed deep water from the Labrador Sea.

On this year’s cruise with the German research vessel Maria S. Merian, the IUP oceanography group continued to investigate the circulation and water mass transport in the subpolar North Atlantic. For this purpose, pressure inverted echo sounders (PIES) have been deployed along an east-west section following 47°N. These instruments are located at the ocean bottom and measure the sound travel time up to the surface and back to the instrument. As the sound velocity depends on temperature and salinity of the sea water, it is possible to infer these quantities as well as the density of the water from the PIES. Knowledge of the density field in turn allows the calculation of oceanic velocities and transports.

The PIES measurements in the western basin of the Atlantic already allowed to calculate the strength of the North Atlantic Current, which transports warm, saline waters from the subtropics into the subpolar North Atlantic and also influences the climate in north western Europe. This year for the first time, PIES have been deployed in the eastern basin of the Atlantic along 47°N. There they will also allow to quantify the exchange of warm and salty subtropical water and colder, fresher subpolar water masses.

On the Merian cruise that took place in May/June this year, the Bremen oceanography group was supported by colleagues from the German hydrographic institute and two Canadian students from the Arctrain research training program.

August 2017:

Global data sets on marine phytoplankton diversity at highest spatial and temporal resolution via the synergistic exploitation of hyper-and multispectral satellite data

Led by the AWI research group PHYTOOPTICS in collaboration with the IUP-UB, the Laboratoire d’Océanographie de Villefranche (LOV), Villefranche, France, and the Plymouth Marine Laboratory (PML), Plymouth, United Kingdom, satellite data products of the biomass (given as chlorophyll-a) of three major phytoplankton groups, namely diatoms, coccolithophores and prokaryotic phytoplankton (also called cyanobacteria), at best have been developed within the project SynSenPFT funded under the ESRIN/ESA within the SEOM (Sceintific Exploration of operational missions) - Sentinel for Science Synergy (SY-4Sci Synergy)" programme. SynSenPFT product are publicly available for the global ocean at daily, 4km x 4km resolution for the entire ENIVSAT mission time and the image shows the SynSenPFT products for the global ocean in September 2006.

To gain knowledge on the role of marine phytoplankton in the global marine ecosystem and biogeochemical cycles, information on the global distribution of major phytoplankton functional types (PFT) is essential. Products representing phytoplankton diversity have been developed by various algorithms mostly applied to multispectral satellite data. However, despite providing a good spatial resolution and coverage, those products are limited to either only indicating size fractions or the dominance of phytoplankton groups and all these products have a strong linkage to a-priori-information because the small number of wavelength bands and the broadband resolution of these sensors provide only limited information on the difference of the phytoplankton absorption structures. Former and current satellite instruments with a very high spectral resolution provide the opportunity for distinguishing more accurately multiple PFTs using spectral approaches as has been demonstrated with the Phytoplankton Differential Optical Absorption Spectroscopy (PhytoDOAS) method (developed by the AWI PHYTOOPTICS group in collaboration with IUP-UB) in the open ocean using hyperspectral satellite data from the sensor “SCanning Imaging Absorption Spectrometer for Atmospheric CHartographY" (SCIAMACHY). Being originally developed for atmospheric applications, hyperspectral sensors like SCIAMACHY do not provide operational water-leaving radiance products as do ocean color sensors. Since the pixel size of these data is very large (30 km by 60 km per pixel) and global coverage by these measurements is reached only within six days which limits the application of hyperspectral-based PFT data products.

To overcome the short-comings of current multi-and hyper-spectral PFT products the synergistic retrieval of PFT from space from hyper- and multispectral measurements (SynSenPFT) was developed to improve the retrieval of PFTs from space by exploring the synergistic use of low-spatial-hyper-spectral and high-spatial-multi-spectral satellite data. The SynSenPFT algorithm is based on input data of the improved/revised existing PFT algorithms based on hyper- (PhytoDOAS) and multi-spectral (OC-PFT) and then by combining those synergistically to derive PFT products with temporal and spatial resolution as multispectral ocean colour data but using the spectral information from the hyperspectral data. The algorithm principles, sensitivity studies and its thorough validation against a large global in-situ phytoplankton group data set have been published now (Losa et al 2017). This synergistic algorithm can be later applied to produce a synergistic PFT product from hyperspectral sensors Sentinel-5-Precursor, Sentinel-4 and Sentinel-5 and multispectral sensor OLCI on Sentinel-3 to ensure the prolongation of the time series over the next decades.

Further information can be found under:

Losa S., Soppa M. A., Dinter T., Wolanin A., Brewin R. J. W., Bricaud A., Oelker J., Peeken I., Gentili B., Rozanov. V. V., Bracher A., Synergistic exploitation of hyper- and multispectral precursor Sentinel measurements to determine Phytoplankton Functional Types at best spatial and temporal resolution (SynSenPFT). Frontiers in Marine Science Front. Mar. Sci. 4: 203; doi: 10.3389/fmars.2017.00203;

SynSenPFT-webpage:

https://www.awi.de/en/science/climate-sciences/physical-oceanography/main-research-focus/ocean-optics/projects/synsenpft.html

July 2017:

Transport and Transformation of Pollutants

from Major Population Centers: EMeRGe first campaign in Europe starts in July

Led by IUP-UB and in collaboration with eight German universities and research centers, the DFG project Effect of Megacities on the transport and transformation of pollutants on the Regional to Global scales, EMeRGe, aims to investigate the regional and global impact of pollutants emitted from European and Asian major population centers (MPC).

The first intensive EMeRGe airborne measurement campaign using the airborne platform HALO (High Altitude and Long Range Research Aircraft) will be carried out from the 10thto the 31st of July 2017 over Europe. After the installation and preparation phases with basis at DLR in Oberpfaffenhofen, a total of 52 HALO flight hours has been allocated for this part of the investigation with particular focus on European target MPC (London, Benelux, Ruhr area, Rome, Po Valley), the Mediterranean and Central Europe within summer events of photochemical interest.

Complementary measurements over Europe from the airborne platforms FAAM (www.faam.ac.uk) and ERA CNR SkyArrow, and from the European lidar and ground base network will be additionally carried out and used for planning and analysis in the framework of the EMeRGe international research partnership.

Further details can be found at www.iup.uni-bremen.de/emerge/

June 2017:

Vertical Colum Densities of NO2

Vertical Colum Densities of NO2 measured above Bucharest on Monday 2014-09-08. Numbered labels correspond to industrial point source emitters of NOx listed in the European Pollutant Release and Transfer Register (http://prtr.ec.europa.eu/). Black lines indicate major roads.

Vertical Colum Densities of NO2 measured above Bucharest on Monday 2014-09-08

Global maps of nitrogen dioxide (NO2) pollution are nowadays routinely produced from data of satellites such as GOME, SCIAMACHY, OMI and GOME-2. A similar instrument installed on an aircraft results in the same type of maps of tropospheric NO2columns, but with a much higher spatial resolution. During the AROMAT (Airborne Romanian Measurements of Aerosols and Trace gases) campaign which took place in Romania in summer 2014, the AirMAP instrument was installed on board of a Cessna operated by the FU Berlin and took such measurements above Bucharest on several days with a spatial resolution of the order of 100m. The image shows an example of the resulting maps , demonstrating the degree of spatial variability found in an area comparable to just a single pixel of a current state of the art satellite instrument. Comparison between measurements taken at different times and on different days also illustrates large temporal variations, underlying the need for geostationary satellites which can provide several measurements per day for the same location.

The AirMAP instrument is an imaging DOAS spectrometer covering either a band in the visible for high sensitivity NO2retrievals, or a spectral range more in the UV enabling simultaneous detection of SO2and NO2, albeit at lower signal to noise ratio. Data analysis employs the Differential Optical Absorption Spectroscopy (DOAS) method and air mass factors (AMF) based on surface reflectance values derived from the measurements of the AirMAP instrument. Validation of the AirMAP NO2columns with MAX-DOAS measurements from cars operated at the same time during the campaign by the Max-Planck Institute for Chemistry in Mainz and the University of Galati, Romania showed very good agreement, in particular for those measurements for which the time difference was small.

High resolution maps of tropospheric NO2can be used for a variety of applications, including satellite validation, analysis of the representativeness of low spatial resolution observations, emission estimates, and pollution mapping. The AirMAP instrument has already been operated during several other campaigns and it is planned to also employ it for validation of the upcoming Sentinel-5 precursor satellite.

More details can be found in:
Meier, A. C., Schönhardt, A., Bösch, T., Richter, A., Seyler, A., Ruhtz, T., Constantin, D.-E., Shaiganfar, R., Wagner, T., Merlaud, A., Van Roozendael, M., Belegante, L., Nicolae, D., Georgescu, L., and Burrows, J. P.: High-resolution airborne imaging DOAS measurements of NO2 above Bucharest during AROMAT, Atmos. Meas. Tech., 10, 1831-1857, doi:10.5194/amt-10-1831-2017, 2017.

May 2017:

Bremen composite Mg II index

Der Mg II Index ist ein Proxy für die Variabilität der solaren UV Strahlung, die mit der Sonnenaktivität variiert. Neben dem 11-Jahre Zyklus (Schwabe-Zyklus) verändert sich die solare UV Strahlung auch mit der Rotationsperiode der Sonne, die im Mittel etwa 27 Tage beträgt (Carrington-Zyklus). Der Mg II Index korreliert mit der Anzahl der Sonnenflecken, die vom solaren Minimum zum Maximum eines 12-Jahreszyklus zunimmt. Zur Zeit nähern wir uns dem solaren Minimum des nächsten Sonnenzyklus (Zyklus 25). Der Schwabe-Zyklus unterliegt Schwankungen in der Länge (10-12 Jahre) und der Intensität. Das Aktivitätsmaximum des Schwabe-Zyklus 24 (2014/15) war niedriger als die der drei vorherigen Zyklen 21 bis 23.

Der Mg II index wird bei uns aus den täglichen Sonnenmessungen der Satelliteninstrumente GOME, SCIAMACHY, GOME-2A, und -2B seit 1995 abgeleitet. Zusammen mit anderen Satellitendaten kann ein kombinierter Datensatz (´´Composite Mg II Index´´) erstellt werden, der etwa 38 Jahre umfasst (1978-2017) und sich über die Sonnenzyklen 21 bis 24 erstreckt. Diese Zeitserie wird täglich aktualisiert und aktuelle Daten und Bilder sind abrufbar unter http://www.iup.uni- bremen.de/UVSAT/Datasets/mgii.

Die UV Strahlung und deren Variation (Sonnenaktivität) hat einen starken Einfluss auf das stratosphärische Ozon und bestimmt die thermische Struktur der oberen Stratosphäre und beeinflusst damit die globale Luftzirkulation in der oberen Atmosphäre (oberhalb von 20 km).

April 2017:

Evolution of the volcanic plume after the Sarychev Peak eruption

Plots show zonal monthly mean aerosol extinction coefficients at 750 nm retrieved from SCIAMACHY limb measurements at the University of Bremen (V1.4). The volcanic plume is found to reach about 21 km altitude.

July 2009: the month just after the eruption of the Sarychev Peak (48oN, 153oE; June 11-21, 2009). A moderate increase of the stratospheric aerosols is seen around 50oN latitude.

October 2009: aerosol extinction is strongly increased, the plume is transported mostly equatorward.

December 2009: the aerosol load begins to decrease, tropical region is close to the background state.

May 2010: about 1 year after the eruption, the aerosol loading returns to its background state southwards from 50oN

March 2017:

Changes of stratospheric methane 2003 – 2011

Next to carbon dioxide (CO2), methane (CH4) is the most important anthropogenic greenhouse gas. It is produced in the lower atmosphere (the troposphere). Because of its long lifetime, it is eventually transported into higher altitudes, the stratosphere.

The figure (from Noël et al., 2016) shows the changes of stratospheric methane between 2003 and 2011 at Northern mid-latitudes derived from solar occultation measurements of the SCIAMACHY instrument on the ENVISAT satellite. The data have been averaged over one month, and seasonal variations have been removed, resulting in the displayed ‘anomalies’. This way, non-regular and long-term variations in the data become more visible.

In the current case, no clear methane trend for the period 2003 to 2011 can be identified, but there is a prominent variation between positive (red) and negative methane (blue) anomalies. This feature can be explained by transport effects related to the so-called quasi-biennial oscillation (QBO). The QBO is a change of stratospheric winds from easterly to westerly (and vice-versa) which occurs approximately every two years.

Reference:

Noël, S., K. Bramstedt, M. Hilker, P. Liebing, J. Plieninger, M. Reuter, A. Rozanov, C. E. Sioris, H. Bovensmann and J. P. Burrows, Stratospheric CH4 and CO2 profiles derived from SCIAMACHY solar occultation measurements, Atmos. Meas. Tech., 9(4), 1485-1503, 2016, doi: 10.5194/amt-9-1485-2016, http://www.atmos-meas-tech.net/9/1485/2016/

February 2017:

Indonesia experienced an exceptional number of fires in 2015 as a result of droughts related to an El Niño event. This situation was further intensified by human activities such as clearing of rain forests and drainage of peat land. These fires released large amounts of the greenhouse gas carbon dioxide (CO2) into the atmosphere. Emission databases such as the Global Fire Assimilation System (GFASv1.2) and the Global Fire Emission Database (GFEDv4s) estimated the CO2 emission to be approximately 1100 Mt CO2 in the time period from July to November 2015, which is more than the yearly anthropogenic CO2 emission of an industrialised country such as Germany. The emission from the database was indirectly estimated by using parameters like burned area, fire radiative power, and emission factors but not directly from CO2measurements.

In a recent study, the Indonesian fire CO2 emission is estimated by using CO2 concentrations derived from measurements of the Orbiting Carbon Observatory-2 (OCO-2) satellite mission. The estimated CO2 emissions for the Indonesian fires in the time period from July to November 2015 are shown in the figure above (bars to the right) based on OCO-2 (red, dark red columns are the satellite based CO2 emissions obtained by using two different methods) compared to the GFASv1.2 (light grey) and GFED4s emissions (dark grey). Shown is also the spatial distribution of the fire CO2 emissions based on GFASv1.2. The mean emission based on the satellite CO2 data is 748±296 MtCO2, which is about 30% lower than provided by the emission databases. More details about this study can be found in the publication of Heymann et al., 2017 (http://onlinelibrary.wiley.com/doi/10.1002/2016GL072042/full).

January 2017

Figure:

Part of the IUP-UB CINDI-2 team in front of the containers in which the DOAS instruments were operated.

IUP-UB participation in the CINDI-2 campaign

In September 2016, the Second Cabauw Intercomparison of Nitrogen measuring Instruments (CINDI-2) took place in Cabauw, the Netherlands. This campaign brought together more than 30 groups from all over the world to compare instruments and analysis methods for quantifying tropospheric and stratospheric NO2amounts. Most of the groups performed different versions of Differential Optical Absorption Spectroscopy (DOAS) measurements using sun light scattered in the atmosphere. The measurements had to follow a strict prescribed protocol and results from a day of measurements were submitted the next morning to a referee who collected them in a semi-blind comparison. The results were presented and discussed during daily meetings but curves were not labelled to keep the comparison semi-blind. A detailed analysis is currently being prepared and will be finalised during a dedicated workshop in April 2017.

During the CINDI-2 campaign, IUP-UB deployed not only a standard 2d-MAX-DOAS instrument and a mobile DOAS instrument mounted on the IUP Messwagen, but for the first time also operated the new Imaging DOAS instrument called IMPACT. This instrument which is a collaboration between the LAMOS and DOAS groups at IUP-UB takes a full vertical scan instantaneously, and scans the azimuthal direction over time. This greatly reduces the time needed for a full hemispherical scan of the atmospheric radiation field to less than 15 minutes. From these measurements, both the horizontal and the vertical gradients of NO2can be retrieved at high temporal resolution. The results could be compared to the retrievals from the 2d-MAX-DOAS instrument and good agreement was found. The instrument will be used for the analysis of pollution plumes and localised emission sources.

Figure: First Comparison of NO2 slant columns derived from the IUP-UB 2d MAX-DOAS instrument (large points) and the IMPACT imaging DOAS instrument. Very good agreement is found with the exception of the lowest viewing angle which is sensitive to the larger field of view of the imaging instrument. The much better temporal resolution of the imaging instrument is apparent which took 11 individual scans during one single scan of the MAX-DOAS instrument. As can be seen from the temporal evolution of the imaging data, the NO2distribution was not constant over the measurements, highlighting the advantage of rapid measurements.

August 2016

Prof. John P. Burrows

elected Fellow of the Royal Society

On 15th July 2016, Prof. John P. Burrows was admitted into the
Royal Society together with 59 other new fellows and foreign members in
a formal ceremony known as „Admission Day“. The ceremony is preceded
by a 2-day seminar where the new fellows give a talk about their current
research. The image shows a collage of pictures taken during Admission Day.

Prof. Dr. John P. Burrows FRS
With Venki Ramakrishnan, President of the Royal Society
The new fellows and foreign members for 2016/
Prof. Burrows 5th from the right, top row
4) Prof . Burrows signing the Charter Book.

December 2015

The left figure

shows in red the CO2 plumes from the city of Berlin and two near by coal fired plants, it would be detected by CarbonSat (Foto Berlin: Thomas Wolf, , Foto Jänschwalde: RaBoe/Wikipedia).

University of Bremen, 2. Dezember 2015

European Commission’s Experts recommend University of Bremen’s concept for quantifying greenhouse gas emissions from space

The European Union Copernicus Climate Change Service recently identified the lack of an operational monitoring system for man-made CO2emissions. This is of major relevance for the upcoming climate conference of the UN Framework Convention on Climate Change in Paris in December. A group of external experts brought together by the European commission was asked to assess the need and opportunity for an independent European space-borne CO2observational capacity to monitor and verify the compliance of parties to international climate agreements. Their report was released recently (see web link) and presented in Brussels in November. The expert group identified the space and ground segment required to deliver surface emissions for monitoring and treaty verification purposes. The report proposes and recommends a concept similar to the CarbonSat concept which was developed and published by researchers at the Institute of Environmental Physics of the University of Bremen. This concept uses the imaging of greenhouse gas “plumes” observed from space to determine the emissions from cities and strong local point sources. The concept builds on the success of a previous Bremen instrument called SCIAMACHY, which flew on ENVISAT 2002 to 2012 and made the first measurements of the atmospheric loading of CO2and CH4but at low spatial resolution. The high spatial resolution concept has been demonstrated by researchers of the University of Bremen using airborne measurements.


In two events in November the European vision of an operational CO2monitoring concept was presented first to members of the European parliament and then to the Copernicus User Forum. The required space segment for CO2monitoring will yield accurate, transparent and consistent quantification of fossil CO2emissions and their trends at the spatial scale of megacities, important industrial sites, small regions, countries, and the Earth as a whole. This capability would provide Europe with a unique and independent source of actionable information for all stages of the policy cycle. Furthermore, the data from a CarbonSat-type mission provides an objective independent contribution to a future international global carbon observing system. The researchers of the Institute of Environmental Physics of the University of Bremen are well prepared to contribute to the implementation of the CarbonSat concept.
Discussions will be held between ESA and the European Commission to investigate flying a Carbon Monitoring satellite within the EU Copernicus Sentinel programme – the suite of satellite sensors being launched by Europe to routinely observe the Earth. It is probable that ESA, whereas not selecting CarbonSat as Earth Explorer, will ask its member states at the agency's next ministerial meeting end of 2016 to fund a Carbon Monitoring prototype satellite to allow Europe for an independent view on CO2emissions.

In conclusion, the global monitoring of CO2emissions by a “CarbonSat type” system is accepted and the issue is now the political will to develop this important system.
Web-Links European Commission, COPERNICUS

http://www.copernicus.eu/main/towards-european-operational-observing-system-monitor-fossil-co2-emissions

WWW-Link CarbonSat@Universität Bremen
http://www.iup.uni-bremen.de/carbonsat/

WWW-Link: MAMAP@Universität Bremen:
http://www.iup.uni-bremen.de/optronics/projects/methaneairbornemappermamap/index.htm

Contact:
Institut für Umweltphysik
Universität Bremen
http://www.iup.uni-bremen.de

Prof. Dr. John P. Burrows
Fon: 0421 218 62100
E-Mail: burrows@iup.physik.uni-bremen.de

Dr. Heinrich Bovensmann
Fon: 0421 218 62102
E-Mail: heinrich.bovensmann@uni-bremen.de

October 2015

click for full size pdf poster

Young Scientist Jia Jia wins “Best Poster” at Atmospheric Limb Workshop

The Atmospheric Limb Workshop is a biennialevent involving more than 8 countries. The scientific focuses are theLimbmeasurements: Emission (UV, visible, IR, microwave), occultation (solar, stellar, lunar), scattering; past, current and future space-borne instruments: SMR, OSIRIS, ACE, GOMOS, MIPAS, SCIAMACHY, SMILES, SAGE, SABER, MLS, SOFIE, HIRDLS, OMPS, ALTIUS, MATS, STEAM; observations and modellingatMesosphere and above, stratosphere, UTLS and troposphere; retrieval algorithms and data assimilation; radiative transfer and spectroscopy. This year it took place from 15 to 17 September in Chalmers University of technology in Gothenburg, Sweden. Like many scientific events, a young scientist award is set for best oral and poster presentations among the PhD student and early stage postdocs. 25 candidates participated in the poster competition. These candidates come from 14 institutes and universities (e.g., JPL, NASA, KIT, NICT, University of Saskatchewan) from 6 countries - Canada, Germany, US, Sweden, Japan, and India. Jia Jia in our institute participated in the competition and won the best poster.

Jia comes from Shandong province in China. She joined IUP in October 2011 to optimize the SCIAMACHY Limb Nadir Matching method in tropospheric ozone retrieval with the funding from CSC (China Scholarship Council) scholarship. The tropospheric ozone monthly data is well improved with the benefitof the V3.0 limb ozone profile information. In this Limb Workshop, she showed the ozonesonde validation of improved SCIAMACHY limb ozone data on a global scale. The newly developedV3.0 limb dataset has a better agreement with ozonesonde in both vertical structure and partial column, especially in the Northern high latitudes. This work is also published in AMT.

Links:
Publication: http://www.atmos-meas-tech.net/8/3369/2015/amt-8-3369-2015.html
website: http://www.chalmers.se/en/conference/limb-workshop-2015/Pages/default.aspx

September 2015:

European and Chinese Scientists meet to assess and discuss Atmospheric
Pollution in Europe and China:


The PANDA Marco Polo summer school on Atmospheric Pollution at the Institute of Environmental Physics, University of Bremen23rd –30th August 2015

Recently, the World Health Organization (WHO) reported that one out of eight of
global deaths worldwide is caused by air pollution. The strong economic growth in
China over the past three decades has led to China being the largest emitter of
greenhouse gases. Also, serious regional air quality problems are now found in its
many mega cities, e.g., in Beijing, Shanghai and Hong Kong. At the same time and
as a result of large efforts made over the last three decades, mitigation measures in
industrial production practices and the development of strict legislation have led to
improved air quality in many regions of Europe and the USA. China, in particular, is
faced with the difficult problem of maintaining rapid economic growth whilst reducing
air pollution and improving quality of life. To tackle this problem, much more
quantitative information about the amounts and distribution of pollutants and a better
understating of the smog formation mechanisms are therefore needed to facilitate the
reduction of health threatening emissions from human activities while promoting the
most effective and sustained economic development.

Satellite observations provide an exciting, relatively novel tool for the attribution and
prediction of air quality and for monitoring the dispersion of air pollution. The
Institute of Remote Sensing / Institute of Environmental Physics led by
Professor John P. Burrows has pioneered the measurement of atmospheric
pollution from space-based instrumentation over the last 30 years, working together
with the leading atmospheric modelling and prediction groups. The PANDA
(PArtnership with chiNa on space DAta) project, supported by the European
Commission, is a consortium of 7 European laboratories and 7 Chinese research
groups. It provides the evidence base from measurements and modelling to improve
our knowledge on the formation and fate of air pollution required for the development
of adequate environmental policies for clean air and sustainable development.
PANDA is led by Prof. Guy Brasseur from Max Planck Institute of Meteorology
Hamburg, and comprises scientific partners from Universities and research
centres in Europe and China.

As part of PANDA and its European sister project Marco Polo, more than 40 early
career scientists, primarily from China and Europe, participated in a summer
research school from the 23rd to the 30th August, 2015, at the Institute of
Environmental Physics of the University of Bremen. The latest research results from
space-based remote sensing and atmospheric modelling together with the
interpretation of observations were central themes of the summer school. The topics
ranged from the fundamentals of remote sensing and atmospheric modelling to the
estimation of anthropogenic emissions and the impact of economic development and
legislation on air quality. The objective of this summer school and its counterpart
which will be held next year in Chain is to reinforce cooperation between scientists of
China and Europe to jointly address complex questions related to air pollution, and
climate change.

Link: Meeting Programme

August 2015:

This picture shows the change in sulphur content in ship fuels. Before the regulation change on January 1st2015, ships were allowed to use fuels with 1% sulphur content, since this date only much cleaner fuel with 0.1 % is allowed. Data was obtained by measuring exhaust gases of ships with in-situ instruments from a land-based measurement station in Wedel near Hamburg at the Elbe River. This method allows a monitoring for compliance of a large number of ships without having to enter the ships and take fuel samples. Within about 3 months of collecting data, 1413 ships could be analysed for their fuel sulphur content and 95 % of all ships analysed in January comply with the new, much stricter regulations. The measurements were carried out within the project “MeSmarT”, a cooperation between the IUP, Bremen, and the Bundesamt für Seeschifffahrt und Hydrographie, Hamburg.

Links:

Publication:http://www.atmos-chem-phys-discuss.net/15/11031/2015/acpd-15-11031-2015.html
Press release: http://www.iup.uni-bremen.de/deu/downloads/wittrock---150206marpol_vi_jahreswechsel_14_15.pdf
Website:http://www.mesmart.de/

April 2015:

First detection of a large scale methane plume extending several kilometers over a southern
California Oil Field using passive airborne remote sensing. The measurement was performed on
September 04, 2014 with the MAMAP sensor developed at the Institute of Environmental Physics –
IUP.

The data was acquired in summer 2014 during the COMEX-Campaign, a jointly funded ESA and NASA
project. The European MAMAP remote sensing sensor developed and operated by the Institute of
Environmental Physics at the University of Bremen in cooperation with the German Research Centre
for Geosciences (GFZ) was installed on a Twin Otter aircraft operated by the Center for
Interdisciplinary Remotely-Piloted Aircraft Studies CIRPAS. The instrument detected during several
flights unexpectedly large methane plumes over an Oil field in southern California, which could be
traced over a distance of several kilometers. These measurements demonstrate for the first time
that strong local methane emissions from Gas and Oil production could be detected by passive
remote sensing and traced in space. The data will be used to estimate the magnitude of the emissions resulting from such facilities.

See also press release of the University of Bremen :

Additional pictures are available at:
http://www.iup.uni-bremen.de/optronics/downloads/COMEX%20Release%20Oil_Field_final_v3_short_de_Pictures_Only.pdf

February 2015

This image was featured by ESA in a web-story entitled “Is Europe an underestimated sink for carbon dioxide?

http://www.esa.int/Our_Activities/Observing_the_Earth/Is_Europe_an_underestimated_sink_for_carbon_dioxide
A new study using satellite data suggests that Europe’s vegetation extracts more carbon from the atmosphere than previously thought. The complete study authored by Maximilian Reuter et al. was published recently in Atmospheric Chemistry and Physics.

http://www.atmos-chem-phys.net/14/13739/2014/acp-14-13739-2014.html

December 2014

click image for full resolution

This cover picture was published recently in the AGU journal Earth's Future (http://onlinelibrary.wiley.com/doi/10.1002/2014EF000265/abstract).

The composite image comprises the following:

a) the night-time image of light coming from the earth, using data acquired by the Visible Infra-red Imaging Radiometer Suite on-board the Suomi NPP satellite in 2012, and

b) an overlay showing the changes in the methane over the continuously growing oil and gas production regions Bakken, Eagle Ford, and Marcellus. The latter is the difference in column methane between the periods 2006-2008 and 2009-2011 and has been derived from measurements made by the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) satellite instrument. (Night-time lights background NASA / overlay by O. Schneising). SCIAMACHY flies on the ESA Envisat and downlinked measurements from 2002 to 2012 when Envisat failed.

The complete study is published in "Remote sensing of fugitive methane emissions from oil and gas production in North American tight geologic formations"; EARTH'S FUTURE Volume 2, Issue 10, October 2014, Pages: 548–558, Oliver Schneising, John P. Burrows, Russell R. Dickerson, Michael Buchwitz, Maximilian Reuter and Heinrich Bovensmann; Article first published online : 6 OCT 2014, DOI: 10.1002/2014EF000265