| 1. |
- Bender, Frida A. -M., et al.
(author)
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Quantification of Monthly Mean Regional-Scale Albedo of Marine Stratiform Clouds in Satellite Observations and GCMs
- 2011
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In: Journal of Applied Meteorology and Climatology. - 1558-8424 .- 1558-8432. ; 50:10, s. 2139-2148
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Journal article (peer-reviewed)abstract
- 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.
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| 2. |
- Bengtsson, Lisa, 1981-, et al.
(author)
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Impact of flow-dependent horizontal diffusion on resolved convectionin AROME.
- 2012
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In: Journal of Applied Meteorology and Climatology. - 1558-8424 .- 1558-8432. ; 51:1, s. 54-67
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Journal article (peer-reviewed)abstract
- 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.
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| 3. |
- Di Napoli, Claudia, et al.
(author)
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Verification of Heat Stress Thresholds for a Health-Based Heat-Wave Definition
- 2019
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In: Journal of Applied Meteorology and Climatology. - : AMER METEOROLOGICAL SOC. - 1558-8424 .- 1558-8432. ; 58:6, s. 1177-1194
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Journal article (peer-reviewed)abstract
- Heat waves represent a threat to human health and excess mortality is one of the associated negative effects. A health-based definition for heat waves is therefore relevant, especially for early warning purposes, and it is here investigated via the universal thermal climate index (UTCI). The UTCI is a bioclimate index elaborated via an advanced model of human thermoregulation that estimates the thermal stress induced by air temperature, wind speed, moisture, and radiation on the human physiology. Using France as a test bed, the UTCI was computed from meteorological reanalysis data to assess the thermal stress conditions associated with heat-attributable excess mortality in five cities. UTCI values at different climatological percentiles were defined and evaluated in their ability to identify periods of excess mortality (PEMs) over 24 years. Using verification metrics such as the probability of detection (POD), the false alarm ratio (FAR), and the frequency bias (FB), daily minimum and maximum heat stress levels equal to or above corresponding UTCI 95th percentiles (15 degrees +/- 2 degrees C and 34.5 degrees +/- 1.5 degrees C, respectively) for 3 consecutive days are demonstrated to correlate to PEMs with the highest sensitivity and specificity (0.69 <= POD <= 1, 0.19 <= FAR <= 0.46, 1 <= FB <= 1.48) than minimum, maximum, and mean heat stress level singularly and other bioclimatological percentiles. This finding confirms the detrimental effect of prolonged, unusually high heat stress at day- and nighttime and suggests the UTCI 95th percentile as a health-meaningful threshold for a potential heat-health watch warning system.
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| 4. |
- Garcia-Carreras, Luis, et al.
(author)
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The Impact of Parameterized Convection on the Simulation of Crop Processes
- 2015
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In: Journal of Applied Meteorology and Climatology. - 1558-8424 .- 1558-8432. ; 54:6, s. 1283-1296
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Journal article (peer-reviewed)abstract
- 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.
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| 5. |
- Guttorp, P., et al.
(author)
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Assessing the Uncertainty in Projecting Local Mean Sea Level from Global Temperature
- 2014
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In: Journal of Applied Meteorology and Climatology. - : American Meteorological Society. - 1558-8424 .- 1558-8432. ; 53:9, s. 2163-2170
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Journal article (peer-reviewed)abstract
- The process of moving from an ensemble of global climate model temperature projections to local sea level projections requires several steps. Sea level was estimated in Olympia, Washington (a city that is very concerned with sea level rise because parts of downtown are barely above mean highest high tide), by relating global mean temperature to global sea level; relating global sea level to sea levels at Seattle, Washington; and finally relating Seattle to Olympia. There has long been a realization that accurate assessment of the precision of projections is needed for science-based policy decisions. When a string of statistical and/or deterministic models is connected, the uncertainty of each individual model needs to be accounted for. Here the uncertainty is quantified for each model in the described system and the total uncertainty is assessed in a cascading effect throughout the system. The projected sea level rise over time and its total estimated uncertainty are visualized simultaneously for the years 2000-2100, the increased uncertainty due to each of the component models at a particular projection year is identified, and estimates of the time at which a certain sea level rise will first be reached are made.
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| 6. |
- Hu, Yumei, et al.
(author)
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Modeling Road Surface Temperature from Air Temperature and Geographical Parameters-Implication for the Application of Floating Car Data in a Road Weather Forecast Model
- 2019
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In: Journal of Applied Meteorology and Climatology. - : American Meteorological Society. - 1558-8424 .- 1558-8432. ; 58:5, s. 1023-1038
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Journal article (peer-reviewed)abstract
- Precise forecasts of road surface temperature (RST) and road conditions allow winter roads to be maintained efficiently. The upcoming "big data" application known as "floating car data" (FCD) provides the opportunity to improve road weather forecasts with measurements of air temperature T-a from in-car sensors. The research thus far with regard to thermal mapping has mainly focused on clear and calm nights, which occur rarely and during low traffic intensity. It is expected that more than 99% of the FCD will be collected during conditions other than clear and calm nights. Utilizing 32 runs of thermal mapping and controlled T-a surveys carried out on mostly busy roads over one winter season, it was possible to simulate the use of T-a and geographical parameters to reflect the variation of RST. The results show that the examined route had several repeatable thermal fingerprints during times of relatively high traffic intensity and with different weather patterns. The measurement time, real-time weather pattern, and previous weather patterns influenced the spatial pattern of thermal fingerprints. The influence of urban density and altitude on RST can be partly seen in their relationship with T-a, whereas the influence of shading and sky-view factor was only seen for RST. The regression models with T-a included explained up to 82% of the RST distribution and outperformed models that are based only on the geographical parameters by as much as 30%. The performance of the models denotes the possible utility of T-a from FCD, but further investigation is needed before moving from controlled T-a measurements to T-a from FCD.
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| 7. |
- Janzon, Erik, et al.
(author)
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Modelling the flow response to surface heterogeneity during a semi-idealized diurnal cycle
- 2023
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In: Journal of Applied Meteorology and Climatology. - : American Meteorological Society. - 1558-8424 .- 1558-8432. ; 62:4, s. 511-527
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Journal article (peer-reviewed)abstract
- To characterize the effects of subgrid surface heterogeneity, the blending height concept has been developed as a coupling strategy for surface parameterization schemes used in numerical weather prediction (NWP) models. Previous modelling studies have tested this concept using stationary conditions with one-dimensional strips of surface roughness. Here, Large Eddy Simulations (LES) are used to examine the response of the blending height and effective surface roughness to \reva{tiled land cover heterogeneity, or a two-dimensional chessboard pattern }of alternating high and low vegetation given a diurnal cycle of solar irradiance \revg{in subarctic conditions}. In each experiment, the length scale of the roughness elements is increased while the total domain fraction of each vegetation type is kept constant. The effective surface roughness was found to decrease with increasing length scale of surface cover heterogeneity, which is shown to have a significant impact on estimated wind turbine power calculated from logarithmic wind profiles. In stable conditions, the blending height in cases with large heterogeneity length scales was found to exist well above the surface layer. As the behavior of the blending height has implications for coupled models, a simple model for the blending height as a function of heterogeneity length scale is introduced.
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| 8. |
- Karlsson, Johannes, 1978-, et al.
(author)
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Subtropical cloud regime transitions : boundary layerdepth and cloud-top height evolution
- 2010
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In: Journal of Applied Meteorology and Climatology. - 1558-8424 .- 1558-8432. ; 49:9, s. 1845-1858
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Journal article (peer-reviewed)abstract
- 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.
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| 9. |
- Kumar, Vijayant, et al.
(author)
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Impact of Surface Flux Formulations and Geostrophic Forcing on Large-Eddy Simulations of Diurnal Atmospheric Boundary Layer Flow
- 2010
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In: Journal of Applied Meteorology and Climatology. - 1558-8424 .- 1558-8432. ; 49:7, s. 1496-1516
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Journal article (peer-reviewed)abstract
- 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.
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| 10. |
- Linden, J., et al.
(author)
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Using Land Cover, Population, and Night Light Data for Assessing Local Temperature Differences in Mainz, Germany
- 2015
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In: Journal of Applied Meteorology and Climatology. - : American Meteorological Society. - 1558-8424 .- 1558-8432. ; 54:3, s. 658-670
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Journal article (peer-reviewed)abstract
- Urban areas are believed to affect temperature readings, thereby biasing the estimation of twentieth-century warming at regional to global scales. The precise effect of changes in the surroundings of meteorological stations, particularly gradual changes due to urban growth, is difficult to determine. In this paper, data from 10 temperature stations within 15 km of the city of Mainz (Germany) over a period of 842 days are examined to assess the connection between temperature and the properties of the station surroundings, considering (i) built/paved area surface coverage, (ii) population, and (iii) night light intensity. These properties were examined in circles with increasing radii from the stations to identify the most influential source areas. Daily maximum temperatures T-max, as well as daily average temperatures, are shown to be significantly influenced by elevation and were adjusted before the analysis of anthropogenic surroundings, whereas daily minimum temperatures T-min were not. Significant correlations (p < 0.1) between temperature and all examined properties of station surroundings up to 1000 m are found, but the effects are diminished at larger distance. Other factors, such as slope and topographic position (e.g., hollows), were important, especially to T-min. Therefore, properties of station surroundings up to 1000 m from the stations are most suitable for the assessment of potential urban influence on T-max and T-min in the temperate zone of central Europe.
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