40 research outputs found
Intercomparison of ILAS-II version 1.4 and version 2 target parameters with MIPAS-Envisat measurements
This paper assesses the mean differences between the two ILAS-II data versions (1.4 and 2) by comparing them with MIPAS measurements made between May and October 2003. For comparison with ILAS-II results, MIPAS data processed at the Institut für Meteorologie und Klimaforschung, Karlsruhe, Germany (IMK) in cooperation with the Instituto de Astrofísica de Andalucía (IAA) in Granada, Spain, were used. The coincidence criteria of &plusmn;300 km in space and &plusmn;12 h in time for H<sub>2</sub>O, N<sub>2</sub>O, and CH<sub>4</sub> and the coincidence criteria of &plusmn;300 km in space and &plusmn;6 h in time for ClONO<sub>2</sub>, O<sub>3</sub>, and HNO<sub>3</sub> were used. The ILAS-II data were separated into sunrise (= Northern Hemisphere) and sunset (= Southern Hemisphere). For the sunrise data, a clear improvement from version 1.4 to version 2 was observed for H<sub>2</sub>O, CH<sub>4</sub>, ClONO<sub>2</sub>, and O<sub>3</sub>. In particular, the ILAS-II version 1.4 mixing ratios of H<sub>2</sub>O and CH<sub>4</sub> were unrealistically small, and those of ClONO<sub>2</sub> above altitudes of 30 km unrealistically large. For N<sub>2</sub>O and HNO<sub>3</sub>, there were no large differences between the two versions. Contrary to the Northern Hemisphere, where some exceptional profiles deviated significantly from known climatology, no such outlying profiles were found in the Southern Hemisphere for both versions. Generally, the ILAS-II version 2 data were in better agreement with the MIPAS data than the version 1.4, and are recommended for quantitative analysis in the stratosphere. For H<sub>2</sub>O data in the Southern Hemisphere, further data quality evaluation is necessary
Aerosol retrieval experiments in the ESA Aerosol_cci project
Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010–2013), algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL.
This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data: qualitatively by inspection of monthly mean AOD maps and quantitatively by comparing daily gridded satellite data against daily averaged AERONET sun photometer observations for the different versions of each algorithm globally (land and coastal) and for three regions with different aerosol regimes.
The analysis allowed for an assessment of sensitivities of all algorithms, which helped define the best algorithm versions for the subsequent round robin exercise; all algorithms (except for MERIS) showed some, in parts significant, improvement. In particular, using common aerosol components and partly also a priori aerosol-type climatology is beneficial. On the other hand the use of an AATSR-based common cloud mask meant a clear improvement (though with significant reduction of coverage) for the MERIS standard product, but not for the algorithms using AATSR. It is noted that all these observations are mostly consistent for all five analyses (global land, global coastal, three regional), which can be understood well, since the set of aerosol components defined in Sect. 3.1 was explicitly designed to cover different global aerosol regimes (with low and high absorption fine mode, sea salt and dust)
Challenges in constraining anthropogenic aerosol effects on cloud radiative forcing using present-day spatiotemporal variability
This is the final version. Available from National Academy of Sciences via the DOI in this recordA large number of processes are involved in the chain from emissions of aerosol precursor gases and primary particles to impacts on cloud radiative forcing. Those processes are manifest in a number of relationships that can be expressed as factors dlnX/dlnY driving aerosol effects on cloud radiative forcing. These factors include the relationships between cloud condensation nuclei (CCN) concentration and emissions, droplet number and CCN concentration, cloud fraction and droplet number, cloud optical depth and droplet number, and cloud radiative forcing and cloud optical depth. The relationship between cloud optical depth and droplet number can be further decomposed into the sum of two terms involving the relationship of droplet effective radius and cloud liquid water path with droplet number. These relationships can be constrained using observations of recent spatial and temporal variability of these quantities. However, we are most interested in the radiative forcing since the preindustrial era. Because few relevant measurements are available from that era, relationships from recent variability have been assumed to be applicable to the preindustrial to present-day change. Our analysis of Aerosol Comparisons between Observations and Models (AeroCom) model simulations suggests that estimates of relationships from recent variability are poor constraints on relationships from anthropogenic change for some terms, with even the sign of some relationships differing in many regions. Proxies connecting recent spatial/temporal variability to anthropogenic change, or sustained measurements in regions where emissions have changed, are needed to constrain estimates of anthropogenic aerosol impacts on cloud radiative forcing.The Pacific Northwest National Laboratory (PNNL) is operated for the Department of Energy (DOE) by Battelle Memorial Institute under Contract DE-AC06-76RLO 1830. Work at PNNL was supported by the US DOE Decadal and Regional Climate Prediction using Earth System Models program and by the US DOE Earth System Modeling program. Work of M.W. and S.Z. performed at Nanjing University was supported by the One Thousand Young Talent Program, Jiangsu Province Specially-Appointed Professor Grant, and the National Natural Science Foundation of China (41575073). A portion of this research was performed using PNNL Institutional Computing resources. The ECHAM6-HAM model was developed by a consortium composed of ETH Zurich, Max Planck Institut für Meteorologie, Forschungszentrum Jülich, University of Oxford, the Finnish Meteorological Institute, and the Leibniz Institute for Tropospheric Research, and is managed by the Center for Climate Systems Modeling (C2SM) at ETH Zurich. D.N. acknowledges support by the Austrian Science Fund (J 3402-N29, Erwin Schrödinger Fellowship Abroad). C2SM at ETH Zurich is acknowledged for providing technical and scientific support. This work was also supported by a grant from the Swiss National Supercomputing Centre under Project ID s431. D.G.P. and P.S. acknowledge support from the United Kingdom (UK) Natural Environment Research Council Grant NE/I020148/1. P.S. and Z.K. acknowledge funding from the European Research Council (ERC) under the European Union’s Seventh Framework Programme (FP7/2007–2013) ERC project ACCLAIM (Grant Agreement FP7-280025). The development of modal version of the GLObal Model of Aerosol Processes (GLOMAP-mode) within Hadley Center Global Environmental Mode (HadGEM) is part of the United Kingdom Chemistry and Aerosols (UKCA) project, which is supported by both National Environmental Research Council (NERC) and the Joint Department of Energy & Climate Change/Department for Environment, Food & Rural Affairs Meteorology Office Hadley Centre Climate Programme. We acknowledge use of the Met Office and NERC MONSooN high performance computing system, a collaborative facility supplied under the Joint Weather and Climate Research Programme, a strategic partnership between the Met Office and the NERC. Simulations by SPRINTARS were executed with the supercomputer system SX-9/ACE of the National Institute for Environmental Studies, Japan. SPRINTARS is partly supported by the Environment Research and Technology Development Fund (S-12-3) of the Ministry of the Environment, Japan and Japan Society for the Promotion of Science KAKENHI Grants-in-Aid for Scientific Research 15H01728 and 15K12190. Computing resources for CAM5-MG2 simulations were provided by the Climate Simulation Laboratory at National Center for Atmospheric Research (NCAR) Computational and Information Systems Laboratory. NCAR is sponsored by the US National Science Foundation
VALIDATION OF ENVISAT-1 LEVEL-2 PRODUCTS RELATED TO LOWER ATMOSPHERE O3 AND NOy CHEMISTRY BY A FTIR QUASI-GLOBAL NETWORK
A coordinated action involving eleven stations of the ground-based Network for Detection of Stratospheric Change (NDSC) equipped with Fourier transform infrared (FTIR) instruments was conducted to contribute to the validation of the three atmospheric chemistry instruments onboard ENVISAT, that are MIPAS, SCIAMACHY and GOMOS.
The target products for validation are total columns of O3, CH4, CO and some important NOy species (NO2, HNO3, NO) and the source gas N2O. Together the eleven stations cover the latitudes between 79 °N and 78°S, including polar, mid -latitude and subtropical and tropical locations. The goal is to contribute to the assessment of the data quality of the aforementioned ENVISAT instruments, from a quasi-global perspective.
The period of intensive ground-based data collection for the benefit of the ENVISAT Validation Commissioning Phase that is dealt with in the present paper is July 15 to December 1, 2002. The FTIR network involved collected a data set corresponding to an equivalent of approximately 400 days of measurements; about three quarter of the data have already been submitted to the ENVISAT Calval database and are included in the present work.
Unfortunately, the distribution of ENVISAT data has been slow and limited. Only a limited number of coincidences has been found for making data inter-comparisons. Therefore, the conclusions drawn in this paper are very preliminary and cover only a limited set of data products from SCIAMACHY only.
Our findings up to now concerning the above mentioned target products are the following: (1) SCIAMACHY near infrared operational products (CO, CH4, N2O) have no scientific meaning yet, (2), the operational SCIAMACHY total vertical O3 column product derived in the ultraviolet window has undergone some improvements with changing versions of the processor(s) but it still underestimates the column by about 5 – 10 %, (3), the operational SCIAMACHY total vertical O3 column product derived in the visible window is unrealistically large, and (3), the operational NO2 total column product from SCIAMACHY seems to largely overestimate the real column, but very few coincidences and large dispersions of the data do inhibit any further conclusion at present.
In a next phase, the same ground-based correlative data set will be exploited to further validate the ENVISAT data as soon as more and reprocessed data will be distributed
The Cabauw Intercomparison Campaign for Nitrogen Dioxide Measuring Instruments (CINDI): Design, Execution, and Early Results
From June to July 2009 more than thirty different in-situ and remote sensing instruments from all over the world participated in the Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI). The campaign took place at KNMI's Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands. Its main objectives were to determine the accuracy of state-ofthe- art ground-based measurement techniques for the detection of atmospheric nitrogen dioxide (both in-situ and remote sensing), and to investigate their usability in satellite data validation. The expected outcomes are recommendations regarding the operation and calibration of such instruments, retrieval settings, and observation strategies for the use in ground-based networks for air quality monitoring and satellite data validation. Twenty-four optical spectrometers participated in the campaign, of which twenty-one had the capability to scan different elevation angles consecutively, the so-called Multi-axis DOAS systems, thereby collecting vertical profile information, in particular for nitrogen dioxide and aerosol. Various in-situ samplers and lidar instruments simultaneously characterized the variability of atmospheric trace gases and the physical properties of aerosol particles. A large data set of continuous measurements of these atmospheric constituents has been collected under various meteorological conditions and air pollution levels. Together with the permanent measurement capability at the CESAR site characterizing the meteorological state of the atmosphere, the CINDI campaign provided a comprehensive observational data set of atmospheric constituents in a highly polluted region of the world during summertime. First detailed comparisons performed with the CINDI data show that slant column measurements of NO2, O4 and HCHO with MAX-DOAS agree within 5 to 15%, vertical profiles of NO2 derived from several independent instruments agree within 25% of one another, and MAX-DOAS aerosol optical thickness agrees within 20-30% with AERONET data. For the in-situ NO2 instrument using a molybdenum converter, a bias was found as large as 5 ppbv during day time, when compared to the other in-situ instruments using photolytic converters
Concentrations and radiative forcing of anthropogenic aerosols from 1750 to 2014 simulated with the Oslo CTM3 and CEDS emission inventory
We document the ability of the new-generation Oslo
chemistry-transport model, Oslo CTM3, to accurately simulate present-day
aerosol distributions. The model is then used with the new Community Emission
Data System (CEDS) historical emission inventory to provide updated time
series of anthropogenic aerosol concentrations and consequent direct
radiative forcing (RFari) from 1750 to 2014.Overall, Oslo CTM3 performs well compared with measurements of surface
concentrations and remotely sensed aerosol optical depth. Concentrations are
underestimated in Asia, but the higher emissions in CEDS than previous
inventories result in improvements compared to observations. The treatment
of black carbon (BC) scavenging in Oslo CTM3 gives better agreement with
observed vertical BC profiles relative to the predecessor Oslo CTM2. However,
Arctic wintertime BC concentrations remain underestimated, and a range of
sensitivity tests indicate that better physical understanding of processes
associated with atmospheric BC processing is required to simultaneously
reproduce both the observed features. Uncertainties in model input data,
resolution, and scavenging affect the distribution of all aerosols species,
especially at high latitudes and altitudes. However, we find no evidence of
consistently better model performance across all observables and regions in
the sensitivity tests than in the baseline configuration.Using CEDS, we estimate a net RFari in 2014 relative to 1750 of
−0.17 W m−2, significantly weaker than the IPCC AR5 2011–1750
estimate. Differences are attributable to several factors, including stronger
absorption by organic aerosol, updated parameterization of BC absorption, and
reduced sulfate cooling. The trend towards a weaker RFari over recent years
is more pronounced than in the IPCC AR5, illustrating the importance of
capturing recent regional emission changes.</p
AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations
Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes. Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50% decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2/3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1. Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AOD(f), AOD(c)), Angstrom exponent (AE), dry surface scattering (SCdry), and absorption (AC(dry)) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21% +/- 20% (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from -37% (MODIS-Terra) to -16% (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R > 0.75), suggesting that the models are capable of capturing spatiotemporal variations in AOD. We find a much larger underestimate in coarse AOD(c) (similar to-45% +/- 25 %) than in fine AOD(f) (similar to-15% +/- 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AOD(c) bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AOD(c). Column AEs are underestimated by about 10% +/- 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140% if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment. Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of -35% +/- 25% and -20% +/- 18% for SCdry and AC(dry), respectively. The larger underestimate of SCdry than AC(dry) suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models. Considerable inter-model diversity in the simulated optical properties is often found in regions that are, unfortunately, not or only sparsely covered by ground-based observations. This includes, for instance, the Sahara, Amazonia, central Australia, and the South Pacific. This highlights the need for a better site coverage in the observations, which would enable us to better assess the models, but also the performance of satellite products in these regions. Using fine-mode AOD as a proxy for present-day aerosol forcing estimates, our results suggest that models underestimate aerosol forcing by ca. -15 %, however, with a considerably large interquartile range, suggesting a spread between -35% and +10 %.Peer reviewe
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Maritime aerosol network as a component of AERONET - First results and comparison with global aerosol models and satellite retrievals
The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. Over 80 cruises were completed through early 2010 with deployments continuing. Measurement areas included various parts of the Atlantic Ocean, the Northern and Southern Pacific Ocean, the South Indian Ocean, the Southern Ocean, the Arctic Ocean and inland seas. MAN deploys Microtops hand-held sunphotometers and utilizes a calibration procedure and data processing traceable to AERONET. Data collection included areas that previously had no aerosol optical depth (AOD) coverage at all, particularly vast areas of the Southern Ocean. The MAN data archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we present results of AOD measurements over the oceans, and make a comparison with satellite AOD retrievals and model simulations
Validation of water vapour profiles (version 13) retrieved by the IMK/IAA scientific retrieval processor based on full resolution spectra measured by MIPAS on board Envisat
Vertical profiles of stratospheric water vapour measured by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) with the full resolution mode between September 2002 and March 2004 and retrieved with the IMK/IAA scientific retrieval processor were compared to a number of independent measurements in order to estimate the bias and to validate the existing precision estimates of the MIPAS data. The estimated precision for MIPAS is 5 to 10% in the stratosphere, depending on altitude, latitude, and season. The independent instruments were: the Halogen Occultation Experiment (HALOE), the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), the Improved Limb Atmospheric Spectrometer-II (ILAS-II), the Polar Ozone and Aerosol Measurement (POAM III) instrument, the Middle Atmospheric Water Vapour Radiometer (MIAWARA), the Michelson Interferometer for Passive Atmospheric Sounding, balloon-borne version (MIPAS-B), the Airborne Microwave Stratospheric Observing System (AMSOS), the Fluorescent Stratospheric Hygrometer for Balloon (FLASH-B), the NOAA frostpoint hygrometer, and the Fast In Situ Hygrometer (FISH). For the in-situ measurements and the ground based, air- and balloon borne remote sensing instruments, the measurements are restricted to central and northern Europe. The comparisons to satellite-borne instruments are predominantly at mid- to high latitudes on both hemispheres. In the stratosphere there is no clear indication of a bias in MIPAS data, because the independent measurements in some cases are drier and in some cases are moister than the MIPAS measurements. Compared to the infrared measurements of MIPAS, measurements in the ultraviolet and visible have a tendency to be high, whereas microwave measurements have a tendency to be low. The results of &chi;<sup>2</sup>-based precision validation are somewhat controversial among the comparison estimates. However, for comparison instruments whose error budget also includes errors due to uncertainties in spectrally interfering species and where good coincidences were found, the &chi;<sup>2</sup> values found are in the expected range or even below. This suggests that there is no evidence of systematically underestimated MIPAS random errors
Evaluation of the inter-annual variability of stratospheric chemical composition in chemistry-climate models using ground-based multi species time series
The variability of stratospheric chemical composition occurs on a broad spectrum of timescales, ranging from day to decades. A large part of the variability appears to be driven by external forcings such as volcanic aerosols, solar activity, halogen loading, levels of greenhouse gases (GHG), and modes of climate variability (quasi-biennial oscillation (QBO), El Niño-Southern Oscillation (ENSO)). We estimate the contributions of different external forcings to the interannual variability of stratospheric chemical composition and evaluate how well 3-D chemistry-climate models (CCMs) can reproduce the observed response-forcing relationships. We carry out multivariate regression analyses on long time series of observed and simulated time series of several traces gases in order to estimate the contributions of individual forcings and unforced variability to their internannual variability. The observations are typically decadal time series of ground-based data from the international Network for the Detection of Atmospheric Composition Change (NDACC) and the CCM simulations are taken from the CCMVal-2 REF-B1 simulations database. The chemical species considered are column O3, HCl, NO2, and N2O. We check the consistency between observations and model simulations in terms of the forced and internal components of the total interannual variability (externally forced variability and internal variability) and identify the driving factors in the interannual variations of stratospheric chemical composition over NDACC measurement sites. Overall, there is a reasonably good agreement between regression results from models and observations regarding the externally forced interannual variability. A much larger fraction of the observed and modelled interannual variability is explained by external forcings in the tropics than in the extratropics, notably in polar regions. CCMs are able to reproduce the amplitudes of responses in chemical composition to specific external forcings. However, CCMs tend to underestimate very substantially the internal variability and hence the total interannual variability for almost all species considered. This lack of internal variability in CCMs might partly originate from the surface forcing of these CCMs by analysed SSTs. The results illustrate the potential of NDACC ground-based observations for evaluating CCMs