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  • 1. Bender, Frida A. -M.
    et al.
    Charlson, Robert J.
    Ekman, Annica M. L.
    Stockholm University, Faculty of Science, Department of Meteorology .
    Leahy, Louise V.
    Quantification of Monthly Mean Regional-Scale Albedo of Marine Stratiform Clouds in Satellite Observations and GCMs2011In: Journal of Applied Meteorology and Climatology, ISSN 1558-8424, E-ISSN 1558-8432, Vol. 50, no 10, p. 2139-2148Article in journal (Refereed)
    Abstract [en]

    Planetary albedo the reflectivity for solar radiation is of singular importance in determining the amount of solar energy taken in by the Earth-atmosphere system. Modeling albedo, and specifically cloud albedo, correctly is crucial for realistic climate simulations. A method is presented herein by which regional cloud albedo can be quantified from the relation between total albedo and cloud fraction, which in observations is found to be approximately linear on a monthly mean scale. This analysis is based primarily on the combination of cloud fraction data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and albedo data from the Clouds and the Earth's Radiant Energy System (CERES), but the results presented are also supported by the combination of cloud fraction and proxy albedo data from satelliteborne lidar [Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CA LIPSO)]. These data are measured and derived completely independently from the CERES-MODIS data. Applied to low-level marine stratiform clouds in three regions (off the coasts of South America, Africa, and North America), the analysis reveals regionally uniform monthly mean cloud albedos, indicating that the variation in cloud shortwave radiative properties is small on this scale. A coherent picture of low effective cloud albedo emerges, in the range from 0.35 to 0.42, on the basis of data from CERES and MODIS. In its simplicity, the method presented appears to be useful as a diagnostic tool and as a constraint on climate models. To demonstrate this, the same method is applied to cloud fraction and albedo output from several current-generation climate models [from the Coupled Model Intercomparison Project, phase 3 (CMIP3), archive]. Although the multimodel mean cloud albedo estimates agree to within 20% with the satellite-based estimates for the three focus regions, model-based estimates of cloud albedo are found to display much larger variability than do the observations, within individual models as well as between models.

  • 2.
    Bengtsson, Lisa
    et al.
    Sveriges meteorologiska och hydrologiska institut (SMHI), Norrköping.
    Tijm, Sander
    Vána, Filip
    Svensson, Gunilla
    Stockholm University, Faculty of Science, Department of Meteorology .
    Impact of flow-dependent horizontal diffusion on resolved convectionin AROME.2012In: Journal of Applied Meteorology and Climatology, ISSN 1558-8424, E-ISSN 1558-8432, Vol. 51, no 1, p. 54-67Article in journal (Refereed)
    Abstract [en]

    Horizontal diffusion in numerical weather prediction models is, in general, applied to reduce numerical noise at the smallest atmospheric scales. In convection-permittingmodels, with horizontal grid spacing on the order of 1–3 km, horizontal diffusion can improve themodel skill of physical parameters such as convective precipitation. For instance, studies using the convection-permitting Applications of Research to Operations at Mesoscale model (AROME) have shown an improvement in forecasts of large precipitation amounts when horizontal diffusion is applied to falling hydrometeors. The nonphysical nature of such a procedure is undesirable, however. Within the current AROME, horizontal diffusion is imposed using linear spectral horizontal diffusion on dynamicalmodel fields. This spectral diffusion is complemented by nonlinear, flow-dependent, horizontal diffusion applied on turbulent kinetic energy, cloud water, cloud ice, rain, snow, and graupel. In this study, nonlinear flowdependent diffusion is applied to the dynamical model fields rather than diffusing the already predicted falling hydrometeors. In particular, the characteristics of deep convection are investigated. Results indicate that, for the same amount of diffusive damping, the maximum convective updrafts remain strong for both the current and proposed methods of horizontal diffusion. Diffusing the falling hydrometeors is necessary to see a reduction in rain intensity, but amore physically justified solution can be obtained by increasing the amount of damping on the smallest atmospheric scales using the nonlinear, flow-dependent, diffusion scheme. In doing so, a reduction in vertical velocity was found, resulting in a reduction in maximum rain intensity.

  • 3.
    Garcia-Carreras, Luis
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology . University of Leeds, United Kingdom.
    Challinor, A. J.
    Parkes, B. J.
    Birch, C. E.
    Nicklin, K. J.
    Parker, D. J.
    The Impact of Parameterized Convection on the Simulation of Crop Processes2015In: Journal of Applied Meteorology and Climatology, ISSN 1558-8424, E-ISSN 1558-8432, Vol. 54, no 6, p. 1283-1296Article in journal (Refereed)
    Abstract [en]

    Global climate and weather models are a key tool for the prediction of future crop productivity, but they all rely on parameterizations of atmospheric convection, which often produce significant biases in rainfall characteristics over the tropics. The authors evaluate the impact of these biases by driving the General Large Area Model for annual crops (GLAM) with regional-scale atmospheric simulations of one cropping season over West Africa at different resolutions, with and without a parameterization of convection, and compare these with a GLAM run driven by observations. The parameterization of convection produces too light and frequent rainfall throughout the domain, as compared with the short, localized, high-intensity events in the observations and in the convection-permitting runs. Persistent light rain increases surface evaporation, and much heavier rainfall is required to trigger planting. Planting is therefore delayed in the runs with parameterized convection and occurs at a seasonally cooler time, altering the environmental conditions experienced by the crops. Even at high resolutions, runs driven by parameterized convection underpredict the small-scale variability in yields produced by realistic rainfall patterns. Correcting the distribution of rainfall frequencies and intensities before use in crop models will improve the process-based representation of the crop life cycle, increasing confidence in the predictions of crop yield. The rainfall biases described here are a common feature of parameterizations of convection, and therefore the crop-model errors described are likely to occur when using any global weather or climate model, thus remaining hidden when using climate-model intercomparisons to evaluate uncertainty.

  • 4.
    Karlsson, Johannes
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology .
    Svensson, Gunilla
    Stockholm University, Faculty of Science, Department of Meteorology .
    Cardoso, Sambingo
    Teixeira, Joao
    Subtropical cloud regime transitions: boundary layerdepth and cloud-top height evolution2010In: Journal of Applied Meteorology and Climatology, ISSN 1558-8424, E-ISSN 1558-8432, Vol. 49, no 9, p. 1845-1858Article in journal (Refereed)
    Abstract [en]

    In this study, the mean and variability of boundary layer height (BLH) are analyzed along a transect in the eastern Pacific Ocean for the summer of 2003 using BLH estimates based on the height of the main relative humidity (RH) inversion and the height of low cloud tops (CTH). The observations and the regional and global model data have been prepared in the context of the Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) Pacific Cross-Section Intercomparison (GPCI). The GPCI transect covers the transition from a stratocumulus-topped marine boundary layer (MBL) off the coast of California to a trade cumulus-topped, less-well-defined, MBL, and finally to the deep-convection regions in the intertropical convergence zone (ITCZ). The Atmospheric Infrared Sounder (AIRS) and the Multiangle Imaging Spectroradiometer (MISR) have been used to derive observational records of the two BLH estimates. Analyses from the ECMWF are also used in the study. Both BLH estimates in the models, the ECMWF analysis, and the observations agree on a southward vertical growth of the MBL along the GPCI transect in the stratocumulus region. Away from the region typically associated with extensive cloud cover, the two BLH estimates depict different evolutions of the MBL. In most models, the height of the main RH inversion decreases southward from; similar to 18 degrees N, reaching a minimum at the ITCZ, whereas the height of the RH inversion in the ECMWF analysis and a few of the models is fairly constant all the way to the ITCZ. As a result of insufficient vertical resolution of the gridded dataset, the AIRS data only manage to reproduce the initial growth of the BLH. The median-model CTH increases from the stratocumulus-topped MBL to the ITCZ. In contrast, the observed MISR CTHs decrease southward from 20 degrees N to the ITCZ, possibly indicative of the fact that in these regions MISR manages to capture a variety of cloud tops with a mean that is below the subsidence inversion while the models and the ECMWF analysis mainly simulate CTHs corresponding to the height of the subsidence inversion. In most models and in the ECMWF analysis, the height of the main RH inversion and the CTH tend to coincide in the northern part of the GPCI transect. In the regions associated with trade cumuli and deep convection there is a more ambiguous relation between the two BLH estimates. In this region, most of the models place the CTH above the main RH inversion. The ECMWF analysis shows a good agreement between the BLH estimates throughout the transect.

  • 5. Kumar, Vijayant
    et al.
    Svensson, Gunilla
    Stockholm University, Faculty of Science, Department of Meteorology .
    Holtslag, A. A. M.
    Meneveau, Charles
    Parlange, Marc B.
    Impact of Surface Flux Formulations and Geostrophic Forcing on Large-Eddy Simulations of Diurnal Atmospheric Boundary Layer Flow2010In: Journal of Applied Meteorology and Climatology, ISSN 1558-8424, E-ISSN 1558-8432, Vol. 49, no 7, p. 1496-1516Article in journal (Refereed)
    Abstract [en]

    The impact of surface flux boundary conditions and geostrophic forcing on multiday evolution of flow in the atmospheric boundary layer (ABL) was assessed using large-eddy simulations (LES). The LES investigations included several combinations of surface boundary conditions (temperature and heat flux) and geostrophic forcing (constant, time varying, time and height varying). The setup was based on ABL characteristics observed during a selected period of the Cooperative Atmosphere-Surface Exchange Study-1999 (CASES-99) campaign. The LES cases driven by a constant geostrophic wind achieved the best agreement with the CASES-99 observations specifically in terms of daytime surface fluxes and daytime and nighttime profiles. However, the nighttime fluxes were significantly overestimated. The LES cases with the surface temperature boundary condition and driven by a time-and height-varying geostrophic forcing showed improved agreement with the observed nighttime fluxes, but there was less agreement with other observations (e.g., daytime profiles). In terms of the surface boundary condition, the LES cases driven by either surface temperature or heat fluxes produced similar trends in terms of the daytime profiles and comparisons with data from soundings. However, in reproducing the fluxes and nighttime profiles, the agreement was better with imposed temperature because of its ability to interact dynamically with the air temperature field. Therefore, it is concluded that surface temperature boundary condition is better suited for simulations of temporally evolving ABL flow as in the diurnal evolution of the ABL.

  • 6. ReVelle, Douglas O.
    et al.
    Nilsson, E. Douglas
    Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM).
    Summertime low-level jets over the high-latitude Arctic Ocean2008In: Journal of Applied Meteorology and Climatology, ISSN 1558-8424, E-ISSN 1558-8432, Vol. 47, no 6, p. 1770-1784Article in journal (Refereed)
    Abstract [en]

    The application of a simple analytic boundary layer model developed by Thorpe and Guymer did not produce good agreement with observational data for oceanic low-level jet observations even though this model has worked well for the predictions of low-level jets over continental surfaces. This failure to properly predict the boundary layer wind maxima was very puzzling because more detailed numerical boundary layer models have properly predicted these low-level oceanic wind maxima. To understand the reasons for its failure to explain the ocean observations, the authors modified the frictional terms in the horizontal linear momentum equations of Thorpe and Guymer, using a standard eddy viscosity closure technique instead of the Rayleigh friction parameterization originally used. This improvement in the modeling of the dissipation terms, which has resulted in the use of an enhanced Rayleigh friction parameterization in the horizontal momentum equations, modified the boundary layer winds such that the continental predictions remained nearly identical to those predicted previously using the Thorpe and Guymer model while the oceanic predictions have now become more representative of the measured wind speed from recent Arctic expeditions.

  • 7.
    Sedlar, Joseph
    Stockholm University, Faculty of Science, Department of Meteorology .
    Implications of Limited Liquid Water Path on Static Mixing within Arctic Low-Level Clouds2014In: Journal of Applied Meteorology and Climatology, ISSN 1558-8424, E-ISSN 1558-8432, Vol. 53, no 12, p. 2775-2789Article in journal (Refereed)
    Abstract [en]

    Observations of cloud properties and thermodynamics from two Arctic locations, Barrow, Alaska, and Surface Heat Budget of the Arctic (SHEBA), are examined. A comparison of in-cloud thermodynamic mixing characteristics for low-level, single-layer clouds from nearly a decade of data at Barrow and one full annual cycle over the sea ice at SHEBA is performed. These cloud types occur relatively frequently, evident in 27%-30% of all cloudy cases. To understand the role of liquid water path (LWP), or lack thereof, on static in-cloud mixing, cloud layers are separated into optically thin and optically thick LWP subclasses. Clouds with larger LWPs tend to have a deeper in-cloud mixed layer relative to optically thinner clouds. However, both cloud LWP subclasses are frequently characterized by an in-cloud stable layer above the mixed layer top. The depth of the stable layer generally correlates with an increased temperature gradient across the layer. This layer often contains a specific humidity inversion, but it is more frequently present when cloud LWP is optically thinner (LWP, 50 gm(-2)). It is suggested that horizontal thermodynamic advection plays a key role modifying the vertical extent of in-cloud mixing and likewise the depth of in-cloud stable layers. Furthermore, longwave atmospheric opacity above the cloud top is generally enhanced during cases with optically thinner clouds. Thermodynamic advection, cloud condensate distribution within the stable layer, and enhanced atmospheric radiation above the cloud are found to introduce a thermodynamic-radiative feedback that potentially modifies the extent of LWP and subsequent in-cloud mixing.

  • 8. Sedlar, Joseph
    et al.
    Tjernström, Michael
    Stockholm University, Faculty of Science, Department of Meteorology .
    A Process-Based Climatological Evaluation of AIRS Level 3 Tropospheric Thermodynamics over the High-Latitude Arctic2019In: Journal of Applied Meteorology and Climatology, ISSN 1558-8424, E-ISSN 1558-8432, Vol. 58, no 8, p. 1867-1886Article in journal (Refereed)
    Abstract [en]

    Measurements from spaceborne sensors have the unique capacity to fill spatial and temporal gaps in ground-based atmospheric observing systems, especially over the Arctic, where long-term observing stations are limited to pan-Arctic landmasses and infrequent field campaigns. The AIRS level 3 (L3) daily averaged thermodynamic profile product is widely used for process understanding across the sparsely observed Arctic atmosphere. However, detailed investigations into the accuracy of the AIRS L3 thermodynamic profiles product using in situ observations over the high-latitude Arctic are lacking. To address this void, we compiled a wealth of radiosounding profiles from long-term Arctic land stations and included soundings from intensive icebreaker-based field campaigns. These are used to evaluate daily mean thermodynamic profiles from the AIRS L3 product so that the community can understand to what extent such data records can be applied in scientific studies. Results indicate that, while the mid- to upper-troposphere temperature and specific humidity are captured relatively well by AIRS, the lower troposphere is susceptible to specific seasonal, and even monthly, biases. These differences have a critical influence on the lower-tropospheric stability structure. The relatively coarse vertical resolution of the AIRS L3 product, together with infrared radiation through persistent low Arctic cloud layers, leads to artificial thermodynamic structures that fail to accurately represent the lower Arctic atmosphere. These thermodynamic errors are likely to introduce artificial errors in the boundary layer structure and analysis of associated physical processes.

  • 9.
    Tjernström, Michael
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology .
    Sedlar, Joseph
    Stockholm University, Faculty of Science, Department of Meteorology .
    Shupe, Matthew D.
    How well do regional climate models reproduce radiation and clouds in the Arctic?: An evolution of ARCMIP simulations2008In: Journal of Applied Meteorology and Climatology, ISSN 1558-8424, E-ISSN 1558-8432, Vol. 47, no 9, p. 2405-2422Article in journal (Refereed)
    Abstract [en]

    Downwelling radiation in six regional models from the Arctic Regional Climate Model Intercomparison (ARCMIP) project is systematically biased negative in comparison with observations from the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment, although the correlations with observations are relatively good. In this paper, links between model errors and the representation of clouds in these models are investigated. Although some modeled cloud properties, such as the cloud water paths, are reasonable in a climatological sense, the temporal correlation of model cloud properties with observations is poor. The vertical distribution of cloud water is distinctly different among the different models; some common features also appear. Most models underestimate the presence of high clouds, and, although the observed preference for low clouds in the Arctic is present in most of the models, the modeled low clouds are too thin and are displaced downward. Practically all models show a preference to locate the lowest cloud base at the lowest model grid point. In some models this happens also to be where the observations show the highest occurrence of the lowest cloud base; it is not possible to determine if this result is just a coincidence. Different factors contribute to model surface radiation errors. For longwave radiation in summer, a negative bias is present both for cloudy and clear conditions, and intermodel differences are smaller when clouds are present. There is a clear relationship between errors in cloud-base temperature and radiation errors. In winter, in contrast, clear-sky cases are modeled reasonably well, but cloudy cases show a very large intermodel scatter with a significant bias in all models. This bias likely results from a complete failure in all of the models to retain liquid water in cold winter clouds. All models overestimate the cloud attenuation of summer solar radiation for thin and intermediate clouds, and some models maintain this behavior also for thick clouds.

  • 10.
    Vercauteren, Nikki
    et al.
    Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
    Destouni, Georgia
    Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
    Dahlberg, Carl Johan
    Stockholm University, Faculty of Science, Department of Ecology, Environment and Plant Sciences.
    Hylander, Kristoffer
    Stockholm University, Faculty of Science, Department of Ecology, Environment and Plant Sciences.
    Fine-Resolved, Near-Coastal Spatiotemporal Variation of Temperature in Response to Insolation2013In: Journal of Applied Meteorology and Climatology, ISSN 1558-8424, E-ISSN 1558-8432, Vol. 52, no 5, p. 1208-1220Article in journal (Refereed)
    Abstract [en]

    This study uses GIS-based modeling of incoming solar radiation to quantify fine-resolved spatiotemporal responses of monthly average temperature, and diurnal temperature variation, at different times and locations within a field study area located on the eastern coast of Sweden. Near-surface temperatures are measured by a network of temperature sensors during the spring and summer of 2011 and then used as the basis for model development and testing. The modeling of finescale spatiotemporal variation considers topography, distance from the sea, and observed variations in atmospheric conditions, accounting for site latitude, elevation, surface orientation, daily and seasonal shifts in sun angle, and effects of shadows from surrounding topography. The authors find a lag time between insolation and subsequent temperature response that follows an exponential decay from coastal to inland locations. They further develop a linear regression model that accounts for this lag time in quantifying fine-resolved spatiotemporal temperature evolution. This model applies in the considered growing season for spatial distribution across the studied near-coastal landscape.

  • 11.
    Vercauteren, Nikki
    et al.
    Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology. Free University of Berlin, Germany.
    Lyon, Steve W.
    Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
    Destouni, Georgia
    Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
    Seasonal Influence of Insolation on Fine-Resolved Air Temperature Variation and Snowmelt2014In: Journal of Applied Meteorology and Climatology, ISSN 1558-8424, E-ISSN 1558-8432, Vol. 53, no 2, p. 323-332Article in journal (Refereed)
    Abstract [en]

    This study uses GIS-based modeling of incoming solar radiation to quantify fine-resolved spatiotemporal responses of year-round monthly average temperature within a field study area located on the eastern coast of Sweden. A network of temperature sensors measures surface and near-surface air temperatures during a year from June 2011 to June 2012. Strong relationships between solar radiation and temperature exhibited during the growing season (supporting previous work) break down in snow cover and snowmelt periods. Surface temperature measurements are here used to estimate snow cover duration, relating the timing of snowmelt to low performance of an existing linear model developed for the investigated site. This study demonstrates that linearity between insolation and temperature 1) may only be valid for solar radiation levels above a certain threshold and 2) is affected by the consumption of incoming radiation during snowmelt.

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