5th iLEAPS Science Conference Abstracts - E4/E5

Abstracts – Session E4 & E5

Ground-based and Earth observations for ecosystem-atmosphere interactions

E4/E501 ORAL-0344: An Earth system data cube for better understanding land-surface interactions

Miguel Mahecha, Guido Kraemer, Milan Flach, Markus Reichstein, Fabian Gans, Gunnar Brandt, Norman Fomferra, Hans Permana, Carsten Brockmann, Sarah Cornell

Understanding land-surface interactions from an observational point of view requires exploring multiple Earth observations (EO) in a synergistic manner. In order to facilitate this research, we built Earth System Data Cube (i.e. a wide range of consistent EOs at different resolutions) accompanied with a multi-language data analytic toolkit. The later should enable complex analyses of the multiple dimensions of the hyper-data cube. In this talk we show progress in our grand challenge towards describing characteristic biosphere-atmosphere system trajectories. We show that these trajectories integrate responses of land-surface processes to e.g. the ENSO. We also show how regional climate extremes propagate into land-surface fluxes and reveal new insights into spatiotemporal compensation effects. This talk is also invitation to stimulate the iLEAPS community to team-up for collaborations within the framework of the ESA supported Earth system data cube: earthsystemdatacube.org

E4/E502 ORAL-0106: Sequential assimilation of Copernicus vegetation products into SURFEX for better constraining soil-plant parameters and variables

Jean-Christophe Calvet1, Clement Albergel1, Alina Barbu1, Dominique Carrer1, Hélène Dewaele1, David Fairbairn2, Delphine Leroux1, Catherine Meurey1, Simon Munier1

1CNRM, Meteo France, Toulouse, France 2ECMWF, Reading, United Kingdom

CNRM has developed a global Land Data Assimilation System (LDAS-Monde) based on the SURFEX open-source modeling platform. This is now the only LDAS chain able to sequentially assimilate vegetation products, jointly with soil moisture products. In particular, LAI and surface soil moisture from the Copernicus Global Land Service (land.copernicus.eu/global) are assimilated. It is shown that: (1) since the assimilation of LAI impacts the soil moisture analysis, and vice versa, the consistency between these products can be evaluated, (2) the impact of the assimilation of EO data into SURFEX on river discharge can be assessed (SURFEX is coupled to the CTRIP hydrological model), (3) the assimilation of LAI can be used to retrieve key soil-plant parameters such as the maximum available soil water content. A new method able to disaggregate 1-km LAI products is presented. LAI disaggregation is needed to better represent specific vegetation types such as crops. In the framework of the eartH2Observe project (www.earth2observe.eu), a global reanalysis of vegetation and water variables was produced by LDAS-Monde from 2000 to 2013, at a spatial resolution of 1 degree. Enhanced spatial resolutions can be achieved over selected areas (e.g. 0.5 degree over Europe, 0.1 over France). Further technical work is ongoing in order to: (1) optimize the LDAS-Monde chain in order to achieve better spatial resolutions at a global scale, (2) allow near-real-time operations, (3) assimilate LAI at a spatial resolution of 300 m.

E4/E503ORAL-0279: Advancing land surface model development with satellite-based Earth observations

Rene Orth1, Emanuel Dutra2, Isabel Trigo2, Gianpaolo Balsamo3

1Stockholm University, Stockholm, Sweden 2Universidade de Lisboa, Lisbon, Portugal 3European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help improve LSM configuration, and hence can contribute to improved weather predictability.
We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts, we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills.
In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability, and understanding of climate system feedbacks.
References: Orth, R., Dutra, E., Trigo, I. F., and Balsamo, G.: Advancing land surface model development with satellite-based Earth observations, Hydrol. Earth Syst. Sci., 21, 2483-2495, doi:10.5194/hess-21-2483-2017, 2017.

E4/E504 - ORAL-0155: Improving estimates of BVOC emissions from woody biomass species in the UK

Gemma Purser1, Mathew Heal1, Julia Drewer2, James Morison3

1University of Edinburgh, Edinburgh, United Kingdom 2Centre for Ecology & Hydrology, Wallingford, United Kingdom 3Forest Research, Surrey, United Kingdom

Recent focus on the mitigation of carbon dioxide (CO2) emissions in response to climate change has seen bioenergy crops proposed as a source of renewable energy and as part of Carbon Capture Storage (CCS) schemes.
Terrestrial vegetation has long been known to emit biogenic volatile organic compounds (BVOCs) such as isoprene and terpenes. These reactive compounds undergo oxidation in the troposphere that can contribute to increases in the concentration of ground-level ozone (O3), which is a human health pollutant and can damage ecosystems.
Forest Research established trial sites in 2010 at sixteen locations in the UK, across a gradient of climate, to determine the likely biomass yields of up to fourteen different Short Rotation Forest (SRF) crops. These included mainly native broadleaved but also conifer and exotic tree species e.g. Aspen, Alder, Eucalyptus, Cedar.
Historically BVOC emission potentials for UK vegetation have been derived from field measurements taken in other, often warmer, climates. Emission potential algorithms are commonly used to convert data measured from the field (or laboratory) to give a standard emission potential at 1000 µmol m-2 s‑1 and 30 ⁰C.
The aim of this study is to quantify and assess the variability in UK-specific emissions for SRF species. Branch-scale and soil BVOC emissions are being collected from flow-through enclosures onto thermal desorption tubes packed with 200 mg poly(2,6-diphenylphenylene oxide) (Tenax) and 100 mg Carbotrap (20/40). Isoprene, monoterpenes and sesquiterpene are then qualitatively and quantitatively determined using Thermal Desorption-Gas Chromatography-Mass Spectrometry. Additional data including CO2 concentration, Photosynthetically-Active Radiation, humidity, soil moisture and temperature (branch enclosure and leaf) is also collected to help understand drivers for emission and to parameterise the fluxes. A summary of measurements to date will be reported.

E4/E505ORAL-0298: Detecting short-term ozone deposition impacts on ecosystems using remote sensing observations

Laurens Ganzeveld, Cornelis Vak, Jan Verbesselt, Wim de Vries

Assessments of ozone deposition impacts on vegetation functioning is generally limited to small-scale laboratory and field experiments and some large-scale modelling studies. In this explorative study we demonstrate the potential to apply MODIS Gross Primary Production (GPP) data to assess short-term (~weeks) and ecosystem scale ozone deposition impacts on vegetation functioning. Seven sites in France, Belgium, Spain and Italy were selected near measurement stations that monitor ambient ozone concentration. Multiple linear regression models were fitted to MODIS 8-day GPP data using temperature, soil moisture, evapotranspiration, land cover classes and the ozone exposure index, AOT40. The inputs were retrieved from various sources, mostly raster data with continental or global coverage of varying spatial and temporal resolution. Three land cover classes were distinguished: needle-leaved evergreen forest, broad-leaved deciduous forest and rain-fed agriculture. Thresholds beyond which short-term ozone impacts were found were set empirically for land cover classes at an 8-day AOT40 of ~250 ppb x h. A significantly negative impact of short-term ozone exposure was found beyond these thresholds resulting in an ~~5% decrease in GPP decrease for an 8-day AOT40 increase of 0.1 ppm x h. Differences in sensitivity between land cover classes could not be shown due to limited amount of – as well of uncertainty in – input data, the simplicity of the used regression models and the large differences in response to ozone exposure between individual species and plants. However, despite these limitations, this study demonstrates the potential of integrating remote sensing and air quality and micrometeorological observations and model data to quantify ecosystem-scale ozone impacts on vegetation functioning.

E4/E506ORAL-0255: Combined application of modelling and Sentinel 2 remote sensing data for novel pasture status monitoring

Suvarna Punalekar1, Anne Verhoef1, Tristan Quaife1, David Humphries1, Chris Reynolds1

1University of Reading, Reading, United Kingdom

The Innovate-UK funded PASQUAL project brings together remote sensing data (in-situ and Sentinel 2) with radiative transfer- and growth modelling to allow for monitoring and near-future (~10-14 days) predictions of pasture yield and quality, for dairy farming.
We present initial results, with the objective to assess the potential of spectral data of different spectral resolutions to monitor changes in pasture yield during a grazing cycle. A pasture model, driven by meteorological driving data and with a range of biophysical parameters, was developed. It accounts for processes such as photosynthesis, growth, respiration, evapotranspiration, senescence and management. A detailed sensitivity analysis showed that maximum light use efficiency was the most critical parameter followed by minimum temperature for optimum growth, and root biomass allocation fraction.
A typical perennial ryegrass in the Southwest of the UK was monitored regularly using field hyperspectral spectroradiometers. Simultaneously, leaf area index (LAI) was measured using a ceptometer and yield was measured, indirectly using a ‘plate meter’ and directly by destructive sampling. The spectral data were used to retrieve LAI with PROSAIL model (Verhoef et al. 2009), which was compared against field observations. Retrieved LAI was assimilated in the growth model for calibration of sensitive parameters using 4D-Var scheme. The effect of spectral resolution on LAI retrieval and growth model skill was studied by convolving narrow spectral bands in broad bands that match with present-day satellites – Sentinel 2A and Landsat 8. It was found that retrieved LAI, using narrow as well as broad spectral bands, can significantly improve yield estimates. These calibrated model parameters compared well with literature. The assimilation of remote sensing information in grass growth models offers a potential tool to monitor pasture growth in response to weather and management and hence can be used effectively in user- friendly pasture prediction software for dairy farmers.

E4/E507 - ORAL-0362: Large‐scale investigations of forest carbon fluxes based on remote sensing biomass products

Martin Thurner2, 1, Christian Beer2, 1, Karlheinz Erb3, Matthias Forkel4, Wei Li5

1Stockholm University, Stockholm, Sweden 2Bolin Centre for Climate Research, Stockholm, Sweden 3Alpen-Adria Universität Klagenfurt-Vienna-Graz, Vienna, Austria 4TU Wien (Vienna University of Technology), Vienna, Austria 5Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France

In research contributing to current IPCC reports, the land carbon sink is inferred as the residual of fossil fuel emissions, the atmospheric CO2 increase, the net ocean sink, and the net land use change flux. However, among these carbon fluxes especially the emissions from land use change imply large uncertainties, resulting in uncertain terrestrial carbon sink estimates. More precise estimates of the land use change flux, as well as potential direct estimates of processes contributing to the land carbon sink, are substantially constrained by the uncertainty in vegetation biomass estimates. Recent advances in remote sensing biomass mapping have the potential to overcome limitations associated with forest inventory data and will help informing the predictions of changes in the land carbon balance by global vegetation models. Here we present how remote sensing biomass products can be used to directly estimate the most uncertain vegetation-atmosphere carbon fluxes in forest ecosystems: Vegetation carbon turnover including fire emissions and other turnover processes, plant respiration, and the net land use change flux. Such independent estimates help to disentangle the contributions of these processes to the carbon balance of the terrestrial vegetation and allow for analyses of the spatial patterns of these fluxes and underlying environmental influences. Ongoing investigations will be further facilitated by prospective new information on global vegetation biomass, e.g. from the GlobBiomass project or the BIOMASS mission.

E4/E508 ORAL-0387: Constraining terrestrial gross primary productivity using solar-induced chlorophyll fluorescence from OCO-2

Jingfeng Xiao1, Xing Li1, 2, Binbin He2

1University of New Hampshire, Durham, The United States of America 2University of Electronic Science and Technology of China, Chengdu, The United States of America

Solar-induced chlorophyll fluorescence (SIF) opens a new perspective on the monitoring of vegetation photosynthesis from space, and has been recently used to estimate gross primary productivity (GPP). Recent studies indicated that SIF provides a more direct measure of photosynthesis of terrestrial ecosystems than widely-used vegetation indices including normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Here we use SIF data from a new satellite platform - the Observing Carbon Observatory 2 (OCO-2) to estimate terrestrial GPP. OCO-2 launched in July 2014 has been collecting SIF measurements globally. We examine the relationship between OCO-2 SIF and tower GPP for a number of eddy covariance flux sites across the globe for the first time. OCO-2 SIF shows a strong relationship with tower GPP at both instantaneous and daily timescales. The relationship at the daily timescale is slightly stronger than that at the instantaneous timescale. SIF exhibits a stronger relationship with GPP than does NDVI or EVI. The strength of the GPP-SIF relationship also varies with vegetation type. Our results demonstrate that OCO-2 provides valuable SIF measurements for constraining GPP at the global scale. SIF observations from spaceborne platforms have great potential for estimating GPP for a variety of vegetation types. Meanwhile, the OCO-2 observations are not spatially continuous, which limits the capability of OCO-2 in estimating GPP in a spatially and temporally continuous manner.

E4/E509ORAL-0258: The contribution of L-band observations to characterising land-atmosphere interactions

Susanne Mecklenburg1

1European Space Agency, Frascati, Italy

Measurements in L-Band are a rather new observation type for scientific and operational user communities. They allow accurate global observations of emitted radiation originating from land and ocean surfaces since the atmosphere is almost transparent in this spectral range. Three dedicated (passive) L-Band missions, namely ESA’s SMOS and NASA’s Aquarius and SMAP missions, provide(d) global measurements of brightness temperatures over the Earth’s surfaces, thus characterising the land surface and its interaction with the atmosphere.
This paper will focus on the European Space Agency’s (ESA) Soil Moisture and Ocean Salinity (SMOS) mission, in orbit for more than 7 years. SMOS data products that contribute to the characterisation of the land surface, in addition to brightness temperature measurements, are soil moisture, vegetation optical depth and soil freeze and thaw state.
SMOS brightness temperatures and soil moisture measurements have been assimilated, constraining the land – atmosphere interactions, into numerical weather prediction, carbon assimilation schemes, and evaporation models. This paper will give a synthesis of the current work:
  • ECMWF is continuously monitoring SMOS brightness temperatures over land and ocean and using them successfully for their soil moisture analysis; the integration into the Integrated Forecasting System is planned for 2018.
  • Assimilating SMOS surface soil moisture into a carbon assimilation scheme built around a terrestrial biosphere model was found to improve estimates of net ecosystem exchange (NEE).
  • Assimilating SMOS surface soil moisture and AMSR-E derived vegetation optical depth into an evapotranspiration model was found to improve latent heat flux estimates over Australia.
After more than 7 years in orbit, SMOS starts to provide a valuable source of data for observing and understanding longer-term processes and phenomena that were not necessarily targeted in the original mission design (e.g., drought pattern monitoring). This paper will give a first indication of how SMOS can contribute to these aspects.

E4/E510 ORAL-0311: A terrestrial assimilation system for vegetation optical depth derived from SMOS

Marko Scholze1, Thomas Kaminski2, Wolfgang Knorr1, Michael Vossbeck2, Mousong Wu1, Paolo Ferrazzoli3, Yann Kerr4, Arnaud Mialon4, Philippe Richaume4, Nemesio Rodriguez4, Jean-Pierre Wigneron 5, Matthias Drusch6

1Lund University, Lund, Sweden 2The Inversion Lab, Hamburg, Germany 3Tor Vergata University, Roma, Italy 4CESBIO, Toulouse, France 5INRA, Bordeaux, France 6ESA-ESTEC, Noordwijk, The Netherlands

ESA's Soil Moisture and Ocean Salinity (SMOS) satellite was launched on 2 November 2009 and is dedicated to making global observations of soil moisture over land and salinity over oceans. Over land soil moisture and vegetation optical depth (VOD) products are routinely retrieved.
The ESA funded 'SMOS + Vegetation' project combines a retrieval component that aims at further improving the SMOS VOD product with an assimilation component that aims at demonstrating the added value of this product in constraining simulated surface fluxes of carbon dioxide. SMOS delivers, for the first time, a VOD product measured at L-band, L-VOD, which is different to the VOD measured at other frequencies.
This presentation focuses on the project's modelling and assimilation component. We describe the construction of a dedicated observation operator that links the state of the terrestrial biosphere model to the simulated VOD. We discuss global maps of simulated VOD and biomass. We present our assimilation system around the terrestrial biosphere model and demonstrate its operation in initial identical twin experiments, i.e. by assimilation of pseudo data.

E4/E511ORAL-0299: Patterns of shallow lakes in permafrost areas

Annett Bartsch1, 2, 3, Georg Pointner3, Marina Leibman4, Yuri Dvornikov4, Artem Khomutov4, Anna Maria Trofaier5

1ZAMG, Vienna, Austria 2Austrian Polar Research Institute, Vienna, Austria 3b.geos, Korneuburg, Austria 4Russian Academy of Science, Tyumen, The Russian Federation 5UNIS, Longyearbyen, Norway

Shallow lakes are common across the entire Arctic. They play an important role as methane sources and wildlife habitats, and they are also associated with thermokarst processes which are characteristic of permafrost environments. They partially freeze to the ground (for depths up to 2m). Unfrozen parts are known to release methane during winter time. The identification of these lakes and their patterns in thus of interest to emission studies, e.g. for upscaling of in situ measurements.
Ground-fast ice can be identified using C-band SAR satellite data. Its fraction has been derived circumpolar for two million lake objects larger than 0.025 km2. The algorithm has been calibrated with bathymetric measurements from the Yamal peninsula and evaluated using further lake depth data from Alaska, Canada and Russia. Results have been eventually compared to soil organic carbon maps. The proportion of ground-fast ice increases with increasing soil organic carbon content in the proximity of the lakes. This underlines the importance of such lakes for emission studies and the need to map the occurrence of ground-fast lake ice.

E4/E512 - ORAL-0113: Finding solutions to environmental challenges relevant to Arctic-boreal regions

Hanna Lappalainen1, 2, Tuukka Petaja1, Veli-Matti Kerminen1, Timo Vihma2, Alexander Baklanov3, Nikolay Kasimov4, Valery Bondur5, Vladimir Melnikov6, Sergej Zilitinkevich7, Markku Kulmala1

1University of Helsinki, Helsinki, Finland 2Finnish Meteorological Institute, Helsinki, Finland 3World Meteorological Organization, Geneve, Swaziland 4Moscow State University, Moscow, The Russian Federation 5AEROCOSMOS, Moscow, The Russian Federation 6Tyumen State University, Tyumen, The Russian Federation 7Finnsih Meteorological Institute, Helsinki, Finland

We need to perform a holistic research approach and establish coordinated comprehensive measurements in order to solve still open scientific questions that are specifically important for the Arctic-boreal region in the coming years. The open science questions in the context of global climate change and its consequences to nature and to the Northern societies are related to net effects of various feedback mechanisms connecting the biosphere, atmosphere and human activities. Such feedbacks stem from higher temperature and increased concentration of greenhouse gases in the future that lead to further permafrost thawing, land cover changes, increased dissolved organic carbon content in freshwaters, acidification of the Arctic Ocean, increased photosynthetic activity, elevated GHG uptake by terrestrial ecosystems and increased Biogenic Volatile Organic Compound emissions leading to aerosol and cloud formation affecting the radiation budget. These feedbacks either hinder or speed up the climate change. The latest review of the current in situ observations over the Northern Eurasian region demonstrates the urgent need for the comprehensive, coordinated in situ observation system detecting the Earth surface and atmosphere processes. Also the marine observations from the ocean, sea ice, and atmosphere are needed to obtain a better understanding on the state and change of the marine Arctic climate system. New concepts, methods including analysis of big data and coordinated research activity are needed to find solutions to these challenges. It is also important to establish education program and create processes where research outcomes are effectively used for the policy making and for the benefit of the Northern societies.

E4/E513 - ORAL-0414: Energy Balance and evapotranspiration changes following large scale conversion of native forests to cultivated crops in Brazil

Bernardo Barbosa da Silva1, Vicente de Paulo Rodrigues da Silva1, Thomas Rocha Ferreira1, Celina Candida Ferreira Rodrigues1

1Universidade Federal de Campina Grande, Campina Grande, Brazil

In Brazil, much of the native Atlantic, Cerrado and Caatinga forests have been converted to farmland under intensive agriculture. Land cover change at this scale has important implications for water and energy budgets, but at present these implications are poorly understood. For this study, we used remote sensing to document changes in radiation and energy balances, and in evapotranspiration (ET) in different areas of Brazil following conversion of: a) native Cerrado forest to cultivated crops in Mogi-Guaçu watershed in São Paulo State; and b) native Caatinga forest to irrigated crops in a semiarid watershed of Brazil. We determined radiation and energy balances, and ET rates using the Surface Energy Balance Algorithm for Land (SEBAL) for TM - Landsat 5 and OLI-TIRS – Landsat 8 imagery taken during 2005 and 2015, respectively. These results were compared with ET data obtained via eddy covariance (ETec) and MOD16 (ETmod16) techniques. Like SEBAL, MOD16 is a remote-sensing-based method for determining ET, but SEBAL provides much higher spatial resolution. Our analysis indicated that land cover change causes strong shifts in albedo, land-surface temperature, and vegetation index, with consequences for radiation and energy balances, and ET. The Absolute Mean Difference, Relative Mean Difference, and Square Root Mean Difference derived via SEBAL and ETec were 1.08 mm, 33.14%, and 1.36 mm, respectively; those derived via ETmod16 were 0.94 mm, 33.47%, and 1.14 mm, respectively. Evapotranspiration rates for the native forests were comparable with those for eucalyptus forests, ET for sugar cane fields was much lower. Our results highlight the dramatic and large-scale decline on ET following conversion of native forests in Brazil to cultivated land in the Mogi-Guaçu watershed, but at the Caatinga forest such changes increased the ET and dropped the land surface temperature.

E4/E514ORAL-0375: Potential deposition of atmospheric aerosols on the snow and albedo reduction in the Mendoza river basin, Argentina

Tomás Rafael Bolaño Ortiz1, 2, David Gabriel Allende1, S. Enrique Puliafito1, 2, Romina Maria Pascual Flores1, 2, Maria Florencia Ruggeri1, 2

1National Technological University, MENDOZA, Argentina 2CONICET, MENDOZA, Argentina

In this investigation, we analyzed the changes of snow albedo in the area of ​​the upper Mendoza river basin, that it is associated with the potential deposition of atmospheric aerosols in spring using snow albedo, aerosol optical depth, land surface temperature, and other relevant relevant parameters obtained by the Moderate Resolution Imaging Spectroradiometer (MODIS) anboard NASA Terra satellite in the period 2000-2016. We have been selected satellite pixels with 100% snow coverage to derive the average snow albedo, optical aerosol depth, surface temperature, and days after snowfall from September to November to perform the multiple regression analysis. The results indicate that after the land surface temperature, the aerosol optical depth represents the most important parameter that affects the variation of snow albedo. Regression analysis illustrates that an increase in one standard deviation at ground surface temperature (3.7 °C) and aerosol optical depth (0.12306) may lead to a decrease in snow albedo of 0.03762 and 0.00354, respectively. This study also shows that approximately 21% of the spring snow albedo reduction over the Mendoza river basin is caused by an increase in aerosol optical depth, thus having a significant impact on the resources available to ecosystem and cities that are supplied from this basin.

E4/E515ORAL-0324: Observed vegetation-atmosphere coupling as a constraint for modeled temperature extremes

Jakob Zscheischler1, Sebastian Sippel, Rene Orth, Miguel Mahecha, Markus Reichstein, Martha Marie Vogel, Sonia Seneviratne

1ETH Zurich, Zurich, Switzerland

Land-atmosphere coupling and its changes are an important component for understanding vegetation-climate feedbacks and making regional future climate projections. We present the Vegetation-Atmosphere Coupling (VAC) index, which identifies regions and times of concurrent strong anomalies in temperature and i) remotely sensed photosynthetic activity or ii) evapotranspiration (ET). The different classes of the index determine whether a location is currently in an energy-limited or water-limited regime. Its high temporal resolution allows investigating how these regimes change over time at the regional scale. In particular, it can be used to understand land-atmosphere processes occurring during climate extremes. In addition, the VAC index helps to distinguish different evaporative regimes and provides indirect information about the local soil moisture state.
Climate models differ widely in the representation of land–atmosphere coupling. For instance, a large fraction of state-of-the-art climate models produces systematically too frequent coincidences of high temperature anomalies with negative ET anomalies in midlatitude regions during the warm season and in several tropical regions year-round, as identified by the VAC index. These coincidences (high temperature, low ET) are closely related to the representation of temperature variability and extremes across the multi-model ensemble. We derive a constraint based on the VAC index to obtain a subset of models whose land-atmosphere coupling behaviour is better aligned with observations. The constrained multi-model simulations display more realistic temperature extremes of reduced magnitude in present-day climate in many regions. In addition, the multi-model simulations for the coming decades show decreased absolute temperature extremes in the constrained ensemble. In summary, our approach offers a physically consistent, diagnostic-based constraint to evaluate multi-model ensembles based on observed land-atmosphere coupling and subsequently reduce model biases in simulated and projected temperature extremes.

E4/E516 - ORAL-0142: Integration of satellite-induced fluorescence and vegetation optical depth to improve the retrieval of land evaporation

Brianna Pagán1, Brecht Martens1, Wouter Maes1, Diego Miralles1

1Ghent University, Ghent, Belgium

Global satellite-based data sets of land evaporation overcome limitations in coverage of in situ measurements while retaining some observational nature. Although their potential for water management, agricultural planning and drought monitoring is promising, their value during dry conditions is still poorly understood. In fact, most evaporation retrieval algorithms are not directly sensitive to soil moisture. An exception is the Global Land Evaporation Amsterdam Model (GLEAM), which uses satellite surface soil moisture and precipitation to account for land water availability. Preliminary results from inter-model comparisons and in situ validations suggest that the performance of GLEAM in dry conditions is slightly better than that of other state-of-the-art evaporation data sets. However, the methodology may greatly benefit from the optimal integration of novel observations of the land surface: microwave vegetation optical depth and near-infrared solar-induced fluorescence are expected to reflect different aspects of the evaporative stress. While the former is considered to be a proxy of vegetation water content, the latter is indicative of the activity of photosynthetic machinery. An important motivation to incorporate observations in the derivation of land evaporation is that plant transpiration – usually the largest component of the flux – is extremely challenging to model due to species-dependent responses to drought, thus its accurate estimation relies on adequate use of available observational constraints. Here, we present a novel assimilation of vegetation optical depth and solar-induced fluorescence into GLEAM that can yield accurate estimates of transpiration over large-scales, which are essential to further understand ecosystem-atmosphere feedbacks and the response of terrestrial hydrology and ecology to meteorological drought. Furthermore, the resulting retrievals of land evaporation can be used to benchmark climate model representation of turbulent fluxes, at a time in which these models still treat water stress rudimentarily, and typically assume the same sensitivity for all vegetation types to drought stress.

E4/E517POSTER-0052: Using microwave remote sensing to improve productivity estimates for the Amazon basin

Thomas Janssen1, Katrin Fleischer2, Han Dolman1

1VU University Amsterdam, Amsterdam, The Netherlands 2Technical University of Munich, Munich, Germany

The Amazon basin contains the largest continuous tropical forest on Earth, driving to a large extent the global annual variability in gross primary productivity (GPP). Forest inventories have indicated that from 1998 to 2010 the basin increased in living biomass, representing a significant carbon sink to the atmosphere. However, the baseline sink is found to be offset by recent drought events. Currently, discrepancies exist between the observed seasonality and drought response of GPP to that what is simulated by terrestrial biosphere models (TBMs). This model-observation mismatch has major implications for the suitability of TBMs to accurately predict the effects of climate change induced warming and drying on the productivity of the Amazon forest, and consequently, the terrestrial carbon sink. We use in situ estimates of ecosystem carbon fluxes and meteorological data in combination with a satellite derived vegetation optical depth (VOD) dataset (1988-2011) to investigate the effects of seasonality and recent droughts on the productivity of the Amazon forest. In addition, rainfall data from the tropical rainfall measuring mission (TRMM) and GRACE terrestrial water storage are used to identify the relation of VOD and GPP to precipitation and soil moisture. The VOD data is derived from passive microwave remote sensing and is sensitive to canopy biomass and water content. We find that the seasonality of VOD in eastern and central Amazonia corresponds closely to the seasonality of in situ estimated GPP. Furthermore, a decline of VOD in the dry season is observed during recent droughts that relates to observed declines in GPP and net carbon uptake by the vegetation. However, the VOD is found to be sensitive to soil moisture and flooding in wet periods. When corrected for soil moisture and flooding, the VOD record could improve estimates of basin-wide productivity and be used to constrain current TBMs.

E4/E518 POSTER-0075: The Importance and Current Limitations of Planetary Boundary Layer (PBL) Retrieval from Space

Joseph Santanello1, Alex Schaefer2

1NASA-GSFC, Greenbelt, The United States of America 2University of North Carolina at Charlotte, Charlotte, The United States of America

There is an established need for improved PBL observations over land for hydrology, land-atmosphere (L-A), PBL, cloud/convection, pollution/chemistry studies and associated model evaluation and development. Most notably, the connection of surface hydrology (through soil moisture) and ecology to clouds and precipitation relies on proper quantification of water’s transport through the coupled system, which is modulated strongly by PBL structure, growth, and feedback processes such as entrainment. In-situ (ground-based or radiosonde) measurements will be spatially limited to small field campaigns for the foreseeable future, so satellite data is a must in order to understand these processes globally. The scales of these applications require diurnal resolution (e.g. 3-hourly or finer) at <100m vertical and 1-10km spatial resolutions in order to assess processes driving land-PBL coupling and water and energy cycles at their native scales. Today’s satellite sensors do not reach close to any of those targets in terms of accuracy or resolution. Unfortunately, there is very little attention or planning (short or long-term) in place for improving lower tropospheric sounding over land. As a result of this lack of PBL-focused missions, PBL and L-A interactions have been identified as ‘gaps’ in current programmatic focal areas. In this poster, the importance of PBL information (structure, evolution) for L-A coupling diagnostics and model development will be summarized. The current array of PBL retrieval methods and products from space will then be assessed in terms of meeting the needs of these models, diagnostics, and scales, with a look forward as to how this can and must be improved through future mission and sensor design.

E4/E519 POSTER-0080: Interactions between Land and Atmosphere: Knowledge utilisation of Regional Climate Models (RCM) at the local level

Alizan Mahadi1

1Keio University, Tokyo, Japan

The interactions between terrestrial and atmosphere is increasingly being studied and recognised in both the academic and policy spheres. However, there is still a lack of instrumental use of the results of climate change projections. It is argued that this is largely due to the fact that the results are often not at the decision-making scales, where the Global Circulation Models (GCM) are projected at the global scale. Secondly, the results are often perceived to be of little policy relevance with only indirect links to social benefit areas. This study seeks to undertake a process of downscaling through simulating impacts of land use and land cover change (LULCC) to the carbon cycle by applying a Regional Circulation Model (RCM) in Manjung, a district in Perak, Malaysia. Utilising the Earth Simulator, a dynamic downscaling approach is used. Three scenarios are selected for the case study. Firstly, where there is no change in land use, secondly, change in land use as per the local district plan, and thirdly, changes based on business as usual, taking the rate of change in the past 15 years. The impacts to both local and global climate is simulated along with the potential impacts to other social benefit areas. The results provide significant contribution to understanding the process and results of downscaling and utilising RCMs at the local level. More generally, due to uncertainties and its complex nature, it is argued that knowledge utilization of climate modelling should shift its focus from its instrumental use (used directly for action and decision-making), to its conceptual use, as a tool for policy learning. It is argued that if there are clear linkages to social benefit areas as well as higher certainty through increase in availability and quality of data, downscaling through RCMs can potentially provide a policy relevant tool.

E4/E520POSTER-0095: The impacts of Amazonian forest cover change on surface albedo

Jamie Wilson1, Dominick Spracklen1, Piers Forster1, Stephen Arnold1, Catherine Scott1

1University of Leeds, Leeds, United Kingdom

Extensive land-use change has occurred over the past few decades in the Amazon, with large areas of forest converted to agriculture and pasture. Such changes impact the climate through emissions of CO2, but also through biophysical changes, including changes in surface albedo. Previous observational studies suggest that pasture and agricultural land in the Amazon have an albedo that is 0.015-0.12 greater than forest. However, few studies have compared surface albedo before and after forest loss, so the change in albedo due to deforestation is still uncertain.
We combine data from different satellites to quantify the impacts of land-use change on surface albedo over the Amazon. Using data derived from the Landsat satellite, we identify regions of deforestation over the period 2000 to 2014. We combine this with data collected by the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, to assess the impacts of deforestation on surface albedo. We also compare surface albedo across regions with different forest canopy cover. We find that deforestation leads to an increase in surface albedo of 0.0070-0.0202, considerably less than previous studies. The impacts of this reduced change on the climate will be investigated using the Suite of Community Radiative Transfer codes based on Edwards and Slingo (SOCRATES).
Our results suggest that previous modelling studies have overestimated the increase in surface albedo that occurs due to tropical deforestation, potentially causing these studies to underestimate the warming impact of tropical deforestation.

E4/E521 - POSTER-0163: PAN enhancement in late afternoon at peri-urban forest in Korea

Junsu Gil1, Meehye Lee1, Lee Hojoon1, Yeong-jae Lee2, Hyunju Park2, Saewung Kim3

1Department of Earth and Environmental Science, Korea University, Seoul, The Republic Of Korea 2National Institute of Environmental Research (NIER), Incheon, The Republic Of Korea 3Department of Earth System Science, University of California, Irvine, The United States of America

As PAN (Peroxyacetyl Nirtrate) is produced by the reaction NOx (= NO + NO2) and VOCs (Volatile Organic Compounds), it is considered as a photochemical indicator of polluted air. To understand the effects of biogenic emissions when being mixed with anthropogenic emissions, measurement was conducted near Seoul Metropolutan Area in Korea during April ~ October 2012 (August and September were missing), May ~ November 2013.
PAN was measured at six heights (4.1, 9.5, 15, 20, 31, 39 m) of a 41m tower along with O3, NOx, CO, SO2 and BVOCs (Biogenic Volatile Organic Compounds). PAN was measured using gas chromatography system. During the measurement, the 5%ile, 50%ile, and 95%ile of PAN and O3 concentrations were 0.12 ppbv, 0.46 ppbv, and 2.09 ppbv respectively.
The PAN maxima averaged 1 hour was 7.78 ppbv and ovserved in August 2013, when the O3 and NOx were also highly elevated. PAN was visibly higher during warm seasons (May~ August) than cold seasons and their monthly mean concentrations were the highest in June. It is noteworthy that there were second peaks of PAN and O3 near 6 PM, with the increase of NO2 from 3 PM especially in June, 2013. Also the isoprene reached maximum around 5 PM, the PAN peaks observed in late afternoon were affected by BVOCs with NOx. A box model was used to examine the contribution of BVOCs and NOx to PAN production.

E4/E522 - POSTER-0212: Assessment of the hydrological status of Marshlands in the South of Iraq using a combination of remote sensing and drought indices

Ahmed AlArazah1, Anne Verhoef1, Kevin White1, Shovonlal Roy

1University of Reading, Reading, United Kingdom

A combination of permanent and seasonal marshes in the southern part of Iraq play a vital role in the maintenance of biodiversity in the Middle East. Three major marshland areas are Chibyish, Hammar, and Hawizeh Marshes, covering an area of approximately 20000 km2 in the lower part of the Mesopotamian basin. Over the past decades, these extensive marshlands system have been heavily affected by both climate and anthropogenic factors. The marshes were artificially drained during the early 1990’s for political reasons, converting approximately 90% of the marshes into deserts. These marshlands were reflooded in 2003, ending the artificial drainage as well as a three-year meteorological drought period (2000-2003). This study analyses the combined effects of artificial draining and meteorological drought using land surface temperature (LST) and Normalised Vegetation Difference Index (NDVI) derived from remote sensing data, together with drought indices (SPI/SPEI, derived from ERA-Interim and in-situ weather data), for the years 2001 to 2015. NDVI has been used widely to detect changes in vegetation extent; LST was employed as a proxy for evapotranspiration. NDVI was obtained from MOD13A2 products (16-Day L3 Global 1km SIN Grid VI datasets), designed for vegetation. LST was obtained through MOD11A2 products available at a spatial resolution of 1km and a temporal resolution of 8 days. ERDAS Imagine 2013 was used for image processing and to extract the value of NDVI and LST. ArcGIS 10.1 software was used for the final analysis stages (including map construction). Assessing marshlands ecological function is important in order to evaluate how the recovery process is progressing and the restoration methods are achieving their goals, as well as their interplay with droughts. We show that remote sensing has a useful role to play in this. Combined with drought indices it allows us to attribute changes to environmental and anthropogenic factors.

E4/E523 - POSTER-0272: Highly Sensitive Detection of Ammonia with a Novel Multi-pass Cell Based on Two Flat Convex Mirrors

Jiajin Chen1, Tu Tan1, Jiaoxu Mei1, Yang Dong1, Jingjing Wang1, Weidong Chen2, Xiaoming Gao1, *

1 Laboratory of Atmospheric Physico-Chemistry, Anhui Institute of Optics & Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China; 2 Laboratoire de Physicochimie de l’Atmosphère, Université du Littoral Côte d’Opale, 189A, Av, Maurice Schumann, 59140, Dunkerque, France

Ammonia (NH3) emissions come from agriculture, and contribute to soil and water acidification. Monitoring of NH3 gas has been widely used in the fields of ecological environment and industrial production. Coupling TDLAS (Tunable Diode Laser Absorption Spectroscopy) to a multi-pass cell is an efficient way for high sensitivity monitoring of ammonia. In the case of using conventional optical multi-pass cell, corrosive ammonia will pollute the coating film of the mirrors, thus affecting the detection sensitivity. In this paper, a novel optical multi-pass cell based on two flat convex mirrors is designed for avoiding corrosive coating film of the multi-pass cell. which avoids the direct contact between the coating film of the mirrors and the corrosive ammonia gas, ensures that the multi pass cell is not affected by ammonia corrosion, thereby improving the detection limit of the ammonia gas.
The effective optical path lengths of the multi-pass cell is 8.8 m. NH3 measurement using the multi-pass cell with a fiber-coupled distributed-feedback laser at 1.531 μm has been performed. The sensor achieves a sensitivity of 0.38 ppm of NH3 with 1 s sample rate. The Allan deviation plot also shows an optimal sensitivity of less than 0.06 ppm with an average time of 50 s for NH3.

E4/E524 - POSTER-0326: Aerosol Source Apportionment in the GoAmazon experiment: Comparison of background stations versus polluted sites

Andre Burger1, Paulo Artaxo1

1Institute of Physics, University of Sao Paulo, Sao Paulo, Brazil

The GoAmazon experiment looked at the impact of Manaus urban emissions on the natural biogenic aerosols from Central Amazonia. Aerosols were sampled in three stations in Amazon Basin – Biological Reserve Rebio Cuieiras (ZF2 – T0), TIWA (T2) and Manacapuru (T3). The background site (ZF2-T0) is located 60km upwind from Manaus city, with more than 1,7 million inhabitants. Two sites downwind of Manaus were also used, one of them (T2) was located close to Manaus. Finally, after being transported for 150 Km, a third site was operated in Manacapuru. Nuclepore filters were analyzed for particulate mass (PM), Equivalent Black Carbon (EBC) and elemental composition by X-Ray Fluorescence. At the dry season, FPM concentration was 5,5ug/m³ at T0, 11,0ug/m³ at T2 and 3,3ug/m³ at T3 and for the CPM it was of 5,5ug/m³, 7,1ug/m³ and 2,2ug/m³, respectively. During the wet season it was observed a reduction on the concentration of all sites at both modes. The data were analyzed with ME-2 algorithm through PMF5.0 (US EPA) and APCA (Absolute Principal Component Analysis) in order to quantify sources profiles and compare the results obtained for both techniques. For the FPM three main sources were identified at all sites: biomass burning, marine aerosol and soil dust whilst PMF could also extract a biogenic factor. At T2 two other factors were identified as vehicular and pollution factors and at T3 only PMF was able to extract a factor identified as pollution. For the CPM three factors were identified at all sites: biogenic emission, soil dust and marine aerosol. PMF also found a second factor related with Cl depletion on marine aerosol. At the site T2 both methods extracted a factor identified as pollution and PMF also found a factor related with vehicular emissions whilst at T3 only APCA extracted a pollution factor.

E4/E525 POSTER-0384: Intercomparison of land–atmosphere interactions over different surface types in the lower reaches of the Yangtze River valley

Weidong Guo1, Xueqian Wang1

1CMA-NJU Joint Laboratory for Climate Prediction Studies, Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University, nanjing, China

The lower reaches of the Yangtze River valley is located within the typical East Asia monsoon zone. Rapid urbanization, industrialization, and development of agriculture have led to fast and complicated land use and land cover change(LUCC) in this region. We analyzed and compared the micro-meteorological elements, surface energy fluxes and different land surface factors based on the data from four sites with different surface types around Nanjing, including urban surface at Dangxiao, suburban surface at Xianling, and grassland and farmland at Lishui County. Then, we quantified the contributions of land surface factors to the surface temperature differences (ΔTs) by considering the effects of surface albedo, roughness length, and evaporation respectively, and try to find the dominant surface factor.
Results indicate that urban heat island(UHI) and farmland cooling effects are both obvious in this region, and UHI results in 2oC higher at urban site than other sites in the nighttime. LUCC changes the radiation, heat fluxes by altering the surface albedo, roughness and Bowen ratio, and finally impacts the micro-meteorological elements. It is found that the cropland cooling effect decreases Ts by -1.76℃ and urban heat island effect increases Ts by 1.25℃. Albedo, evaporation, convection and atmospheric background all contribute to ΔTs, and it is the evaporative cooling effect that plays the most important role in this region and accounts for -1.40℃ of the crop cooling and 2.29℃ of the urban warming. Besides, the background atmospheric circulation is also an indispensable part in land-atmosphere feedback induced by land use change and reinforces both these two effects. This study not only fill the observed data gaps of land-atmosphere interaction in this region, but also provide evidence of the numerical simulation and model development.

E4/E526 POSTER-0407: Measurements of peroxyacetyl nitrate at a background site in the Pearl River Delta region: production efficiency and regional transport

Zheng Xu1, 2, Likun Xue 3, Tao Wang2, Peter Louie4

1Nanjing University, Nanjing, China 2Hong kong polytechnic university, Hong Kong , Hong Kong 3shandong university, Jinan, China 4Environmental Protection Department, the Government of Hong Kong Special Administrative Region, Hong Kong, Hong Kong

Peroxyacetyl nitrate (PAN) is a trace constituent of the atmosphere but plays important roles in air pollution and atmospheric chemistry. To understand the chemical and transport processes of PAN in the Pearl River Delta (PRD) region, measurements of PAN, its precursors and related parameters were made at a regional background site in late summer and late autumn of 2011. Despite the fairly low ambient levels of PAN in general, several photochemical episodes with peak concentrations of PAN and ozone (O3) as high as 4.86 and 189 ppbv were observed when the region was under influence of a tropical cyclone. PAN showed a seasonal variation with higher levels in autumn than in summer. PAN production efficiency, defined as the amount of PAN formed per unit amount of nitrogen oxides (NOX) oxidized, was examined for the polluted PRD plumes, which indicated that PAN production accounted for on average approximately one third of the NOZ formation. The photochemical production efficiency of PAN was much lower with respect to that of O3, suggesting that ~2.9 ppbv of PAN could be produced per formation of 100 ppbv of O3 in the PRD plumes. Varying air masses including maritime air, regional air masses from the PRD, and continental outflow from eastern China were identified, which showed different chemical signatures in terms of both pollution levels and NOZ budget. The highest abundances of PAN were measured in the PRD air masses, compared to the lowest concentrations in the marine air. Overall, the present study provides some new insights into the photochemical production and regional transport of PAN in the PRD region, where such investigations were very scarce before.

E4/E527POSTER-0409: Fluorescence In Situ Hybridization as molecular genetic analysis method for bioaerosols in ambient air samples

Maria Praß1, Isabella Hrabe de Angelis1, Oliver Lauer1, Bruna Holanda1, Thomas Klimach1, Florian Ditas1, Mira L. Pöhlker1, Bettina Weber1, Sandra Ritz2, Joseph M. Prospero3, Paulo Artaxo4, Meinrat Andreae5, Ulrich Pöschl1, Christopher Pöhlker1

1Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany 2Institute of Molecular Biology, Mainz, Germany 3Department of Atmospheric Sciences & Rosenstiel School of Marine and Atmospheric Science, Miami, The United States of America 4Physics Institute of University of Sao Paulo, Sao Paulo, Brazil 5Biogeochemistry Department, Max Planck Institute for Chemistry, Mainz, Germany

Biological aerosol particles are ubiquitous in the Earth’s atmosphere with fractions of up to 70% in the coarse mode aerosol population. Airborne bacteria, pollen and spores are well known to play an important role in public health and the spread of organisms. Moreover, bioaerosols are supposed to affect the Earth’s climate by influencing the atmospheric energy budget as well as physical and chemical processes. Even though the importance of these highly diverse particles was already realized decades ago, their composition, abundance and identity are still poorly understood (Després et al., 2012).
A promising technique to address the afore mentioned open questions is Fluorescence In Situ Hybridization (FISH). This molecular biological method enables the identification of single cells in complex biological and non-biological material such as ambient aerosol samples. Thereby, fluorescently labeled oligonucleotide probes mark target organisms down to the genus level (Amann and Fuchs, 2008). As a result, we receive information on dominant organism groups and their mixing and agglomeration properties.
This method is currently being established for ambient air samples, which were collected in Central and South America. Trade winds carry Saharan desert dust plumes over the Atlantic Ocean to the sampling sites in Barbados and Brazil. Besides mineral particles, these air masses contain biological matter (Prospero et al., 2005). By the application of FISH to daily aerosol samples, we aim to clarify which organisms are co-advected with the Saharan dust plumes. The subsequent microscopic analysis provides a direct visualization of the aerosol mixing state and helps to clarify the bioaerosol transport modes. Thus, the FISH results will allow comprehensive insights into bioaerosol abundance and mixing properties in general and their specific role in transatlantic dust transport.