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  • 1.
    Buehler, Stefan
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Defer, E.
    CNRS, Laboratoire d'Etudes du Rayonnement et de la Matière en Astrophysique, Observatoire de Paris.
    Evans, F.
    Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder.
    Eliasson, Salomon
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Mendrok, Jana
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Erikssson, P.
    Chalmers University of Technology, Department of Earth and Space Sciences.
    Lee, C.
    Met Office Hadley Centre, Exeter.
    Jimenez, C.
    CNRS, Laboratoire d'Etudes du Rayonnement et de la Matière en Astrophysique, Observatoire de Paris.
    Prigent, C.
    CNRS, Laboratoire d'Etudes du Rayonnement et de la Matière en Astrophysique, Observatoire de Paris.
    Crewell, S.
    Institute for Geophysics and Meteorology, University of Cologne.
    kasai, Y.
    National Institute of Information and Communications Technology, 4-2-1 Nukui-kitamachi, Koganei.
    Bennartz, R.
    Atmospheric and Oceanic Sciences, University of Wisconsin.
    Gasiewski, A.J.
    NOAA-CU Center for Environmental Technology (CET), Department of Electrical and Computer Engineering, University of Colorado at Boulder.
    Observing ice clouds in the submillimeter spectral range: the CloudIce mission proposal for ESA's Earth Explorer 82012In: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 5, no 7, 1529-1549 p.Article in journal (Refereed)
    Abstract [en]

    Passive submillimeter-wave sensors are a way to obtain urgently needed global data on ice clouds, particularly on the so far poorly characterized 'essential climate variable' ice water path (IWP) and on ice particle size. CloudIce was a mission proposal to the European Space Agency ESA in response to the call for Earth Explorer 8 (EE8), which ran in 2009/2010. It proposed a passive submillimeter-wave sensor with channels ranging from 183 GHz to 664 GHz. The article describes the CloudIce mission proposal, with particular emphasis on describing the algorithms for the data-analysis of submillimeter-wave cloud ice data (retrieval algorithms) and demonstrating their maturity. It is shown that we have a robust understanding of the radiative properties of cloud ice in the millimeter/submillimeter spectral range, and that we have a proven toolbox of retrieval algorithms to work with these data. Although the mission was not selected for EE8, the concept will be useful as a reference for other future mission proposals.

  • 2.
    Buehler, Stefan
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Milz, Mathias
    Eliasson, Salomon
    Upper tropospheric humidity and cloud ice: comparing global climate models and satellite observations2008In: 2008 European Geosciences Union General Assembly, Austria Center Vienna, Vienna (Austria), 13-18 Apr 2008, European Geosciences Union (EGU), 2008Conference paper (Other academic)
    Abstract [en]

    Upper tropospheric humidity (UTH) and cloud ice (measured as ice water content IWC or vertically integrated ice water path IWP) are parameters of the climate system on which current global climate models do not agree well. This is illustrated by intercomparing the models in the IPCC AR4 archive. It is then discussed, to what extent different satellite measurements agree on these parameters. The focus is on passive observations from different infrared (HIRS, IASI) and microwave (AMSU-B, HSB) sensors.

  • 3.
    Buehler, Stefan
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Östman, S.
    Luleå tekniska universitet.
    Melsheimer, C.
    Institute of Environmental Physics, University of Bremen.
    Holl, Gerrit
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Eliasson, Salomon
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    John, V.O.
    Met Office Hadley Centre, Exeter.
    Blumenstock, T.
    Forschungszentrum Karlsruhe, Institut für Meteorologie und Klimaforschung Karlsruhe.
    Hase, F.
    Forschungszentrum Karlsruhe, Institut für Meteorologie und Klimaforschung Karlsruhe.
    Ekgered, G.
    Chalmers University of Technology, Department of Earth and Space Sciences.
    Raffalski, U.
    Swedish Institute of Space Physics / Institutet för rymdfysik.
    Nasuno, T.
    Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokohama.
    Satho, M.
    Atmosphere and Ocean Research Institute, University of Tokyo.
    Milz, Mathias
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Mendrok, Jana
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    A multi-instrument comparison of integrated water vapour measurements at a high latitude site2012In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 12, no 22, 10925-10943 p.Article in journal (Refereed)
    Abstract [en]

    We compare measurements of integrated water vapour (IWV) over a subarctic site (Kiruna, Northern Sweden) from five different sensors and retrieval methods: Radiosondes, Global Positioning System (GPS), ground-based Fourier-transform infrared (FTIR) spectrometer, ground-based microwave radiometer, and satellite-based microwave radiometer (AMSU-B). Additionally, we compare also to ERA-Interim model reanalysis data. GPS-based IWV data have the highest temporal coverage and resolution and are chosen as reference data set. All datasets agree reasonably well, but the ground-based microwave instrument only if the data are cloud-filtered. We also address two issues that are general for such intercomparison studies, the impact of different lower altitude limits for the IWV integration, and the impact of representativeness error. We develop methods for correcting for the former, and estimating the random error contribution of the latter. A literature survey reveals that reported systematic differences between different techniques are study-dependent and show no overall consistent pattern. Further improving the absolute accuracy of IWV measurements and providing climate-quality time series therefore remain challenging problems.

  • 4.
    Eliasson, Salomon
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Ice clouds in satellite observations and climate models2013Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Ice clouds have an important role in climate. They are strong modulators of the outgoing longwave radiation and the incoming shortwave radiation and are an integral part of the hydrological cycle. However, our knowledge about them is inadequate. Climate models are far from consensus on the magnitude and spatial distribution of several cloud parameters, including the column integrated cloud ice amount, called Ice Water Path (IWP). The lack of adequate constraints from observations is a main contributor to the non-consensus. Cloud ice retrievals from satellite measurements are an important source of observations, since they are global and continuous. However, they carry large uncertainties since different sensors are sensitive to different aspects of clouds, and because clouds are largely inhomogeneous with complicated microphysical properties. Satellite observations are also notoriously difficult to use for model evaluation, due to a mismatch on how cloud parameters are defined in the models compared to what is actually observed. No satellite instrument can measure information from the entire cloud column, as desired from the model point of view. This thesis mainly concerns IWP, which is one of the key cloud parameters. By measuring clouds using different techniques at different wavelengths, the IWP retrievals are sensitive to different parts of the ice particle size distribution, and different depths in the cloud. A main aim of the PhD project is to assess the agreement of datasets based on different techniques and how they may be complementary. This investigation of IWP in observations and models starts by a comparison study of monthly averaged IWP from a climate perspective. The study shows that the differences in IWP within a group of models, and compared to observations are up to an order of magnitude. This confirmed results from previous studies, but in this study, large differences in the spatial distribution of IWP are also identified. The spatial distributions of modelled IWP indicate that they are in disagreement on where the Tropical convective regions are and how much IWP is found there in relation to the global averaged IWP. However, the observational datasets also differ by up to an order of magnitude and the uncertainties for the monthly averaged observations are almost intangibly large. This prompted a new study comparing strictly collocated observations to each other. By doing so, large uncertainties caused by spatially and temporally averaging data were removed. DARDAR, with IWP retrievals based on a combination of Radar and Lidar measurements, is regarded as the best dataset of IWP, and was therefore chosen as the reference dataset. This study determines that DARDAR has a relatively low uncertainty of between 20% to 50%. The validity ranges of the other datasets, i.e., the IWP values where data are trustworthy, are determined by comparing to DARDAR IWP. Once established for each dataset, the systematic and random errors of each dataset are quantified. It is shown that retrievals based on solar reflectance measurements are sensitive to the largest range of IWP values, from ∼30 gm-2 to ∼7000 gm-2, and have random uncertainties less than a factor of two throughout most of this range. To analyse the uncertainties further, the collocated measurements are assessed separately in different types of cloudy scenarios. It is shown that large uncertainties are attributed to the assumed cloud phase and the choice of IWP parameterisations. Further in depth studies on models were carried out using the EC-Earth climate model. A validation study of several upper tropospheric parameters showed that the model captures most large-scale features but has problems with clouds. This led to another study comparing the modelled evolution of several atmospheric variables before and after deep convection events to that of observations. A follow-up study analyses the impacts of clouds on upper tropospheric humidity (UTH) retrievals depending on if they are based on microwave or infrared measurements. By these cross-dataset comparisons we are closer to understanding how to utilise datasets that normally are not comparable due to their different sensitivities.

  • 5.
    Eliasson, Salomon
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Ice clouds in satellite observations and climate models2011Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis concerns the microphysical properties of clouds made up of ice particles, called ice clouds. Ice clouds are strong modulators of the outgoing longwave radiation and incoming shortwave radiation, yet our knowledge on several key ice cloud properties, which govern the magnitude and sign of the net contribution to the Earth’s atmospheric radiation budget, is inadequate. For instance, currently climate models are far from consensus on the magnitude and spatial distribution of ice water path (IWP), a vital radiative property of ice clouds, and the main property of concern in this thesis. The large spread amongst the models in terms of IWP is mostly due to the lack of constraints from observations on ice cloud properties. The lacking constraints reflect the major difficulties faced in observing global ice cloud properties.In-situ measurements provide useful sources of information on ice clouds, but are far from adequate due to the sparseness of measurements. Cloud ice observations from satellites provides a global view and is the most useful source of information. However, measurements from satellites also carry large uncertainties and are notoriously difficult to use for model evaluation, due to a mismatch on how IWP is defined in the models compared to what is actually observed. Not one satellite instrument can measure ice particle information from the entire ice cloud column, as desired from the model point of view. Satellite observations of IWP depend for the most part on the wavelength spectrum the instrument measures in, hence the instruments measure related, but different information on clouds.A study addressing the satellite observed and modeled IWP is presented in the first appended article: Eliasson et al. [2011]. Large differences between climate models are observations, especially in areas with frequent deep convection, were reported and discussed. The second appended article is a first evaluation study of cloud parameters, such as IWP, in the EC-Earth climate model using satellite A-Train observations. The model captures large-scale features for the most part but has problems related to ice water content and cloud fraction. This is strongly linked to the treatment of precipitation.The thesis contains introductory chapters on ice clouds; their formation, radiative importance, and representation in climate models. This is followed by a more in depth chapter on the observational data. The different satellite techniques are then discussed following a radiation physics and radiative transfer background section.

  • 6. Eliasson, Salomon
    et al.
    Buehler, Stefan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Milz, Mathias
    A study on the ice water path descrepencies between global climate models2008Conference paper (Other academic)
  • 7.
    Eliasson, Salomon
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Buehler, Stefan
    Milz, Mathias
    Eriksson, P.
    Department of Radio and Space Science, Chalmers University of Technology.
    John, V.O.
    Met Office Hadley Centre, Exeter.
    Assessing modelled spatial distributions of ice water path using satellite data2010In: Atmospheric Chemistry and Physics Discussions, ISSN 1680-7367, E-ISSN 1680-7375, Vol. 10, no 5, 12185-12224 p.Article in journal (Refereed)
    Abstract [en]

    The climate models used in the IPCC AR4 show large differences in monthly mean cloud ice. The most valuable source of information that can be used to potentially constrain the models is global satellite data. For this, the data sets must be long enough to capture the inter-annual variability of Ice Water Path (IWP). PATMOS-x was used together with ISCCP for the annual cycle evaluation in Fig. 7 while ECHAM-5 was used for the correlation with other models in Table 3. A clear distinction between ice categories in satellite retrievals, as desired from a model point of view, is currently impossible. However, long-term satellite data sets may still be used to indicate the climatology of IWP spatial distribution. We evaluated satellite data sets from CloudSat, PATMOS-x, ISCCP, MODIS and MSPPS in terms of monthly mean IWP, to determine which data sets can be used to evaluate the climate models. IWP data from CloudSat cloud profiling radar provides the most advanced data set on clouds. As CloudSat data are too short to evaluate the model data directly, it was mainly used here to evaluate IWP from the other satellite data sets. ISCCP and MSPPS were shown to have comparatively low IWP values. ISCCP shows particularly low values in the tropics, while MSPPS has particularly low values outside the tropics. MODIS and PATMOS-x were in closest agreement with CloudSat in terms of magnitude and spatial distribution, with MODIS being the best of the two. As PATMOS-x extends over more than 25 years and is in fairly close agreement with CloudSat, it was chosen as the reference data set for the model evaluation. In general there are large discrepancies between the individual climate models, and all of the models show problems in reproducing the observed spatial distribution of cloud-ice. Comparisons consistently showed that ECHAM-5 is the GCM from IPCC AR4 closest to satellite observations

  • 8.
    Eliasson, Salomon
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Buehler, Stefan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Milz, Mathias
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Eriksson, P.
    Chalmers University of Technology, Department of Earth and Space Sciences.
    John, V.O.
    Met Office Hadley Centre, Exeter.
    Assessing observed and modelled spatial distributions of ice water path using satellite data2011In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 11, no 1, 375-391 p.Article in journal (Refereed)
    Abstract [en]

    The climate models used in the IPCC AR4 show large differences in monthly mean ice water path (IWP). The most valuable source of information that can be used to potentially constrain the models is global satellite data. The satellite datasets also have large differences. The retrieved IWP depends on the technique used, as retrievals based on different techniques are sensitive to different parts of the cloud column. Building on the foundation of Waliser et al. (2009), this article provides a more comprehensive comparison between satellite datasets. IWP data from the CloudSat cloud profiling radar provide the most advanced dataset on clouds. For all its unmistakable value, CloudSat data are too short and too sparse to assess climatic distributions of IWP, hence the need to also use longer datasets. We evaluate satellite datasets from CloudSat, PATMOS-x, ISCCP, MODIS and MSPPS in terms of monthly mean IWP, in order to determine the differences and relate them to the sensitivity of the instrument used in the retrievals. This information is also used to evaluate the climate models, to the extent that is possible. ISCCP and MSPPS were shown to have comparatively low IWP values. ISCCP shows particularly low values in the tropics, while MSPPS has particularly low values outside the tropics. MODIS and PATMOS-x were in closest agreement with CloudSat in terms of magnitude and spatial distribution, with MODIS being the better of the two. Additionally PATMOS-x and ISCCP, which have a temporal range long enough to capture the inter-annual variability of IWP, are used in conjunction with CloudSat IWP (after removing profiles that contain precipitation) to assess the IWP variability and mean of the climate models. In general there are large discrepancies between the individual climate models, and all of the models show problems in reproducing the observed spatial distribution of cloud-ice. Comparisons consistently showed that ECHAM-5 is probably the GCM from IPCC AR4 closest to satellite observations

  • 9.
    Eliasson, Salomon
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Holl, Gerrit
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Buehler, Stefan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Kuhn, Thomas
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Stengel, M.
    Iturbe-Sanchez, F.
    Johnston, M.
    Systematic and random errors between collocated satellite ice water path observations2013In: Journal of Geophysical Research, ISSN 0148-0227, E-ISSN 2156-2202, Vol. 118, no 6, 2629-2642 p.Article in journal (Refereed)
    Abstract [en]

    There remains large disagreement between IWP in observational datasets, largely because the sensors observe different parts of the ice particle size distribution. A detailed comparison of retrieved IWP from satellite observations in the Tropics ({plus minus}30{degree sign} latitude) in 2007 is made using collocated measurements. The DARDAR IWP dataset, based on combined Radar/Lidar measurements, is used as a reference as it provides arguably the best estimate of the total column IWP. For each dataset, usable IWP dynamic ranges are inferred from this comparison. IWP retrievals based on solar reflectance measurements, MODIS, and AVHRR-based CMSAF, and PATMOS-x, were found to be correlated with DARDAR over a large IWP range (~20-7000 g/m-2;). The random errors of the collocated datasets have a close to log-normal distribution, and the combined random error of MODIS and DARDAR is less than a factor of 2, which also sets the upper limit for MODIS alone. In the same way the upper limit for the random error of all considered datasets is determined. Datasets based on passive microwave measurements,MSPPS, MiRS, and CMO, are largely correlated with DARDAR for IWP values larger than approximately 700 g/m². The combined uncertainty between these datasets and DARDAR in this range is slightly less MODIS-DARDAR, but the systematic bias is nearly an order of magnitude.

  • 10.
    Eliasson, Salomon
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Mendrok, Jana
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Systematic and random errors between collocated satellite ice water path observations2013Conference paper (Other academic)
    Abstract [en]

    There remains large disagreement between ice-water path (IWP) in observational data sets, largely because the sensors observe different parts of the ice particle size distribution. A detailed comparison of retrieved IWP from satellite observations in the Tropics (±30° latitude) in 2007 was made using collocated measurements. The radio detection and ranging(radar)/light detection and ranging (lidar) (DARDAR) IWP data set, based on combined radar/lidar measurements, is used as a reference because it provides arguably the best estimate of the total column IWP. For each data set, usable IWP dynamic ranges are inferred from this comparison. IWP retrievals based on solar reflectance measurements, in the moderate resolution imaging spectroradiometer (MODIS), advanced very high resolution radiometer–based Climate Monitoring Satellite Applications Facility (CMSAF), and Pathfinder Atmospheres-Extended (PATMOS-x) datasets, were found to be correlated with DARDAR over a large IWP range (~20–7000 g m-2). The random errors of the collocated data sets have a close to lognormal distribution, and the combined random error of MODIS and DARDAR is less than a factor of 2, which also sets the upper limit for MODIS alone. In the same way, the upper limit for the random error of all considered data sets is determined. Data sets based on passive microwave measurements, microwave surface and precipitation products system (MSPPS), microwave integrated retrieval system (MiRS), and collocated microwave only (CMO), are largely correlated with DARDAR for IWP values larger than approximately 700 g m-2. The combined uncertainty between these data sets and DARDAR in this range is slightly less MODIS-DARDAR, but the systematic bias is nearly an order of magnitude.

  • 11. Eliasson, Salomon
    et al.
    Tetzlaff, Anke
    Karlsson, Karl-Göran
    Prototyping an improved PPS cloud detection for the Arctic polar night2007Report (Other academic)
  • 12.
    Holl, Gerrit
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Eliasson, Salomon
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Mendrok, Jana
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Buehler, Stefan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    SPARE-ICE: Synergistic ice water path from passive operational sensors2014In: Journal of Geophysical Research: Atmospheres, ISSN 2169-8996, Vol. 119, no 3, 1504-1523 p.Article in journal (Refereed)
    Abstract [en]

    This article presents SPARE-ICE, the Synergistic Passive Atmospheric Retrieval Experiment-ICE. SPARE-ICE is the first Ice Water Path (IWP) product combining infrared and microwave radiances. By using only passive operational sensors, the SPARE-ICE retrieval can be used to process data from at least the NOAA 15 to 19 and MetOp satellites, obtaining time series from 1998 onward. The retrieval is developed using collocations between passive operational sensors (solar, terrestrial infrared, microwave), the CloudSat radar, and the CALIPSO lidar. The collocations form a retrieval database matching measurements from passive sensors against the existing active combined radar-lidar product 2C-ICE. With this retrieval database, we train a pair of artificial neural networks to detect clouds and retrieve IWP. When considering solar, terrestrial infrared, and microwave-based measurements, we show that any combination of two techniques performs better than either single-technique retrieval. We choose not to include solar reflectances in SPARE-ICE, because the improvement is small, and so that SPARE-ICE can be retrieved both daytime and nighttime. The median fractional error between SPARE-ICE and 2C-ICE is around a factor 2, a figure similar to the random error between 2C-ICE ice water content (IWC) and in situ measurements. A comparison of SPARE-ICE with Moderate Resolution Imaging Spectroradiometer (MODIS), Pathfinder Atmospheric Extended (PATMOS-X), and Microwave Surface and Precipitation Products System (MSPPS) indicates that SPARE-ICE appears to perform well even in difficult conditions. SPARE-ICE is available for public use.

  • 13.
    Johnston, Marston
    et al.
    Chalmers University of Technology, Chalmers University of Technology, Department of Earth and Space Sciences.
    Eliasson, Salomon
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Eriksson, Patrik
    Chalmers University of Technology, Chalmers University of Technology, Department of Earth and Space Sciences.
    Forbes, R.M.
    European Centre for Medium-Range Weather Forecasts, Reading, ECMWF, Shinfield Park, Reading.
    Gettelman, Andrew
    National Center for Atmospheric Research, Boulder, Colorado.
    Räisänen, Petri
    Finnish Meteorological Institute, Helsinki.
    Zelinka, M.D.
    Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore.
    Diagnosing the average spatio-temporal impact of convective systems: part 2:a model intercomparison using satellite data2014In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 14, no 16, 8701-8721 p.Article in journal (Refereed)
    Abstract [en]

    The representation of the effect of tropical deep convective (DC) systems on upper-tropospheric moist processes and outgoing longwave radiation is evaluated in the EC-Earth3, ECHAM6, and CAM5 (Community Atmosphere Model) climate models using satellite-retrieved data. A composite technique is applied to thousands of deep convective systems that are identified using local rain rate maxima in order to focus on the temporal evolution of the deep convective processes in the model and satellite-retrieved data. The models tend to over-predict the occurrence of rain rates that are less than 3 mm 1 compared to Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA). While the diurnal distribution of oceanic rain rate maxima in the models is similar to the satellite-retrieved data, the land-based maxima are out of phase. Despite having a larger climatological mean upper-tropospheric relative humidity, models closely capture the satellite-derived moistening of the upper troposphere following the peak rain rate in the deep convective systems. Simulated cloud fractions near the tropopause are larger than in the satellite data, but the ice water contents are smaller compared with the satellite-retrieved ice data. The models capture the evolution of ocean-based deep convective systems fairly well, but the land-based systems show significant discrepancies. Over land, the diurnal cycle of rain is too intense, with deep convective systems occurring at the same position on subsequent days, while the satellite-retrieved data vary more in timing and geographical location. Finally, simulated outgoing longwave radiation anomalies associated with deep convection are in reasonable agreement with the satellite data, as well as with each other. Given the fact that there are strong disagreements with, for example, cloud ice water content, and cloud fraction, between the models, this study supports the hypothesis that such agreement with satellite-retrieved data is achieved in the three models due to different representations of deep convection processes and compensating errors.

  • 14.
    Johnston, Marston
    et al.
    Chalmers University of Technology.
    Eriksson, Patrik
    Chalmers University of Technology.
    Eliasson, Salomon
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Jones, Colin
    SMHI.
    Forbes, R.M
    ECMWF, Shinfield Park, Reading.
    Murtagh, Donal
    Chalmers University of Technology, Department of Earth and Space Sciences.
    The representation of tropical upper tropospheric water in EC Earth V22012In: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894, Vol. 39, no 11, 2713-2731 p.Article in journal (Refereed)
    Abstract [en]

    Tropical upper tropospheric humidity, clouds, and ice water content, as well as outgoing longwave radiation (OLR), are evaluated in the climate model EC Earth with the aid of satellite retrievals. The Atmospheric Infrared Sounder and Microwave Limb Sounder together provide good coverage of relative humidity. EC Earth's relative humidity is in fair agreement with these observations. CloudSat and CALIPSO data are combined to provide cloud fractions estimates throughout the altitude region considered (500-100 hPa). EC Earth is found to overestimate the degree of cloud cover above 200 hPa and underestimate it below. Precipitating and non-precipitating EC Earth ice definitions are combined to form a complete ice water content. EC Earth's ice water content is below the uncertainty range of CloudSat above 250 hPa, but can be twice as high as CloudSat's estimate in the melting layer. CERES data show that the model underestimates the impact of clouds on OLR, on average with about 9 W m -2. Regionally, EC Earth's outgoing longwave radiation can be ~20 W m -2 higher than the observation. A comparison to ERA-Interim provides further perspectives on the model's performance. Limitations of the satellite observations are emphasised and their uncertainties are, throughout, considered in the analysis. Evaluating multiple model variables in parallel is a more ambitious approach than is customary.

  • 15.
    Johnston, M.S.
    et al.
    Chalmers University of Technology, Department of Earth and Space Sciences.
    Eliasson, Salomon
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Eriksson, P.
    Chalmers University of Technology, Department of Earth and Space Sciences.
    Forbes, R.M.
    European Centre for Medium-Range Weather Forecasts, Reading.
    Wyser, K.
    Swedish Meteorological and Hydrological Institute, Norrköping.
    Zelinka, M.D.
    Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore.
    Diagnosing the average spatio-temporal impact of convective systems: part 1: A methodology for evaluating climate models2013In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 13, no 23, 12043-12058 p.Article in journal (Refereed)
    Abstract [en]

    An earlier method to determine the mean response of upper-tropospheric water to localised deep convective systems (DC systems) is improved and applied to the EC-Earth climate model. Following Zelinka and Hartmann (2009), several fields related to moist processes and radiation from various satellites are composited with respect to the local maxima in rain rate to determine their spatio-temporal evolution with deep convection in the central Pacific Ocean. Major improvements to the earlier study are the isolation of DC systems in time so as to prevent multiple sampling of the same event, and a revised definition of the mean background state that allows for better characterisation of the DC-system-induced anomalies. The observed DC systems in this study propagate westward at similar to 4 ms(-1). Both the upper-tropospheric relative humidity and the outgoing longwave radiation are substantially perturbed over a broad horizontal extent and for periods > 30 h. The cloud fraction anomaly is fairly constant with height but small maximum can be seen around 200 hPa. The cloud ice water content anomaly is mostly confined to pressures greater than 150 hPa and reaches its maximum around 450 hPa, a few hours after the peak convection. Consistent with the large increase in upper-tropospheric cloud ice water content, albedo increases dramatically and persists about 30 h after peak convection. Applying the compositing technique to EC-Earth allows an assessment of the model representation of DC systems. The model captures the large-scale responses, most notably for outgoing longwave radiation, but there are a number of important differences. DC systems appear to propagate east-ward in the model, suggesting a strong link to Kelvin waves instead of equatorial Rossby waves. The diurnal cycle in the model is more pronounced and appears to trigger new convection further to the west each time. Finally, the modelled ice water content anomaly peaks at pressures greater than 500 hPa and in the upper troposphere between 250 hPa and 500 hPa, there is less ice than the observations and it does not persist as long after peak convection. The modelled upper-tropospheric cloud fraction anomaly, however, is of a comparable magnitude and exhibits a similar longevity as the observations.

  • 16.
    Moradi, Isaac
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Buehler, Stefan
    John, Viju
    Met Office Hadley Centre, Exeter.
    Eliasson, Salomon
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology.
    Comparing upper tropospheric humidity data from microwave satellite instruments and tropical radiosondes2010In: Journal of Geophysical Research, ISSN 0148-0227, E-ISSN 2156-2202, Vol. 115, no 24, D24310Article in journal (Refereed)
    Abstract [en]

    Atmospheric humidity plays an important role in the Earth's climate. Microwave satellite data provide valuable humidity observations in the upper troposphere with global coverage. In this study, we compare upper tropospheric humidity (UTH) retrieved from the Advanced Microwave Sounding Unit (AMSU-B) and the Microwave Humidity Sounder (MHS) against radiosonde data measured at four of the central facilities of the Atmospheric Radiation Measurement (ARM) program. The Atmospheric Radiative Transfer Simulator (ARTS) was used to simulate satellite brightness temperatures from the radiosonde profiles. Strong ice clouds were filtered out, as their influence on microwave measurements leads to incorrect UTH values. Day and night radiosonde profiles were analyzed separately, to take into account the radiosonde radiation bias. The comparison between radiosonde and satellite is most meaningful for data in cloud free, night time conditions, and with a time difference of less than 2 hours. We found good agreement between the two data sets. The satellite data are slightly moister than the radiosonde data, with a mean difference of 1-2.3 %RH, depending on the radiosonde site. Monthly gridded data were also compared, and showed slightly larger mean difference of up to 3.3 %RH, which can be explained by sampling issues.

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