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  • Other Sources  (82)
  • 551.5  (80)
  • Biology
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  • 2020-2022  (82)
  • 1
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    Formation and maintenance of subsiding shells around non‐precipitating and precipitating cumulus clouds (2021)
    John Wiley & Sons, Ltd | Chichester, UK
    Details
    Publication Date: 2021-07-20
    Description: A shell of subsiding air is generally known to develop around cumulus clouds and shield them from their environment. We seek here to improve our understanding of such shells by (a) revealing the detailed vertical and horizontal structure of shells surrounding both shallow and deeper clouds, and (b) identifying the mechanisms responsible for in‐shell subsidence generation and maintenance. To that end, a high‐resolution Cloud Resolving Model simulation of the shallow‐to‐deep convection transition over a tropical land surface is analysed with an emphasis on the cloud's near environment. Shells surrounding shallow and deep clouds are found to possess surprisingly similar characteristics. However important differences are observed near cloud top where the deepest clouds are associated with stronger subsidence and broader shells. In the convective outflow region, stronger in‐shell subsidence coincides with strong buoyancy reversal, but also with strong pressure gradients naturally generated by cloud‐top vortex dynamics. A more delicate balance between various processes takes place below, and in‐shell subsidence is only barely sustained as buoyancy reversal is largely compensated by pressure gradients. Finally, while evaporation is clearly the main source of buoyancy reversal everywhere around cloud edges, it is also shown that the downward transport of warmer air from aloft through the subsiding shells may compensate for evaporative cooling to slowly bring in‐shell buoyancy to a near‐neutral state. Overall, while it cannot be denied that evaporative cooling and buoyancy reversal play important roles in generating and sustaining in‐shell subsidence, the present results also emphasise that mechanical forcing at cloud top and downward transport within the shells should not be overlooked.
    Description: Narrow “shells” of subsiding air generally form around cumulus clouds, but the mechanisms responsible for their formation and maintenance are still debated. In this study, the dynamics of these shells is investigated using a high‐resolution simulation of idealized tropical convection. It is shown that in‐shell subsiding motions are generally driven by buoyancy reversal. However, mechanical forcing contributes at least equally at the top of all convective clouds. In addition, it is found that buoyancy reversal due to evaporative cooling may be offset by the downward transport of warmer air from aloft through the subsiding shells.
    Keywords: 551.5 ; cloud dynamics ; near‐cloud environment ; subsiding shells ; tropical convection
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  • 2
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    An application of WKBJ theory for triad interactions of internal gravity waves in varying background flows (2021)
    John Wiley & Sons, Ltd | Chichester, UK
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    Publication Date: 2021-07-20
    Description: Motivated by the question of whether and how wave–wave interactions should be implemented into atmospheric gravity‐wave parametrizations, the modulation of triadic gravity‐wave interactions by a slowly varying and vertically sheared mean flow is considered for a non‐rotating Boussinesq fluid with constant stratification. An analysis using a multiple‐scale WKBJ (Wentzel–Kramers–Brillouin–Jeffreys) expansion identifies two distinct scaling regimes, a linear off‐resonance regime, and a nonlinear near‐resonance regime. Simplifying the near‐resonance interaction equations allows for the construction of a parametrization for the triadic energy exchange which has been implemented into a one‐dimensional WKBJ ray‐tracing code. Theory and numerical implementation are validated for test cases where two wave trains generate a third wave train while spectrally passing through resonance. In various settings, of interacting vertical wavenumbers, mean‐flow shear, and initial wave amplitudes, the WKBJ simulations are generally in good agreement with wave‐resolving simulations. Both stronger mean‐flow shear and smaller wave amplitudes suppress the energy exchange among a resonantly interacting triad. Experiments with mean‐flow shear as strong as in the vicinity of atmospheric jets suggest that internal gravity‐wave dynamics are dominated in such regions by wave modulation. However, triadic gravity‐wave interactions are likely to be relevant in weakly sheared regions of the atmosphere.
    Description: This study explores wave–wave interactions of modulated internal gravity waves (GWs) in varying background flows using WKBJ techniques. The resulting ray‐tracing model (b) is compared to wave‐resolving LES (a). As a key result, we find that wave modulation partially suppresses the energy exchange in triadic GW interactions, and thus triadic GW interactions are likely to be relevant in weakly sheared regions of the atmosphere.
    Description: German Research Foundation (DFG) US National Science Foundation
    Keywords: 551.5 ; internal gravity waves ; parametrization ; ray‐tracing ; triadic wave–wave interaction ; wave modulation
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  • 3
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    Water temperature control on CO2 flux and evaporation over a subtropical seagrass meadow revealed by atmospheric eddy covariance (2021)
    John Wiley & Sons, Inc. | Hoboken, USA
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    Publication Date: 2021-07-01
    Description: Subtropical seagrass meadows play a major role in the coastal carbon cycle, but the nature of air–water CO2 exchanges over these ecosystems is still poorly understood. The complex physical forcing of air–water exchange in coastal waters challenges our ability to quantify bulk exchanges of CO2 and water (evaporation), emphasizing the need for direct measurements. We describe the first direct measurements of evaporation and CO2 flux over a calcifying seagrass meadow near Bob Allen Keys, Florida. Over the 78‐d study, CO2 emissions were 36% greater during the day than at night, and the site was a net CO2 source to the atmosphere of 0.27 ± 0.17 μmol m−2 s−1 (x̅ ± standard deviation). A quarter (23%) of the diurnal variability in CO2 flux was caused by the effect of changing water temperature on gas solubility. Furthermore, evaporation rates were ~ 10 times greater than precipitation, causing a 14% increase in salinity, a potential precursor of seagrass die‐offs. Evaporation rates were not correlated with solar radiation, but instead with air–water temperature gradient and wind shear. We also confirm the role of convective forcing on night‐time enhancement and day‐time suppression of gas transfer. At this site, temperature trends are regulated by solar heating, combined with shallow water depth and relatively consistent air temperature. Our findings indicate that evaporation and air–water CO2 exchange over shallow, tropical, and subtropical seagrass ecosystems may be fundamentally different than in submerged vegetated environments elsewhere, in part due to the complex physical forcing of coastal air–sea gas transfer.
    Description: Deutscher Akademischer Austauschdienst http://dx.doi.org/10.13039/501100001655
    Description: National Science Foundation http://dx.doi.org/10.13039/100000001
    Keywords: 551.5 ; Florida ; Bob Allen Keys ; seagrass meadows ; air–water CO2 exchanges ; biometeorological measurements
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  • 4
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    SAD: Verifying the scale, anisotropy and direction of precipitation forecasts (2021)
    John Wiley & Sons, Ltd | Chichester, UK
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    Publication Date: 2021-07-20
    Description: One important attribute of meteorological forecasts is their representation of spatial structures. While several existing verification methods explicitly measure a structure error, they mostly produce a single value with no simple interpretation. Extending a recently developed wavelet‐based verification method, this study separately evaluates the predicted spatial scale, orientation and degree of anisotropy. The scale component has been rigorously tested in previous work and is known to assess the quality of a forecast similar to other, established methods. However, directional aspects of spatial structure are less frequently considered in the verification literature. Since important weather phenomena related to fronts, coastlines and orography have distinctly anisotropic signatures, their representation in meteorological models is clearly of interest. The ability of the new wavelet approach to accurately evaluate directional properties is demonstrated using idealized and realistic test cases from the MesoVICT project. A comparison of precipitation forecasts from several forecasting systems reveals that errors in scale and direction can occur independently and should be treated as separate aspects of forecast quality. In a final step, we use the inverse wavelet transform to define a simple post‐processing algorithm that corrects the structural errors. The procedure improves visual similarity with the observations, as well as the objective scores.
    Description: Forecasts of precipitation fields are difficult to evaluate due to their complex, intermittent spatial structure. The SAD forecast verification method uses wavelets to compare the scale (colours in the top row), anisotropy (bottom, arrow length) and preferred direction (bottom, arrow angles) of simulated and observed fields. The new approach is successfully tested using data from the MesoVICT community project.
    Description: German Research Foundation (DFG)
    Keywords: 551.5 ; MesoVICT ; precipitation forecasts ; structure error ; verification ; wavelets
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  • 5
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    Spatiotemporal Variability of the Southern Annular Mode and its Influence on Antarctic Surface Temperatures (2021)
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    Publication Date: 2021-07-03
    Description: The Southern Annular Mode (SAM) is the predominant atmospheric variability mode in the Southern Hemisphere. In this paper, we present the spatial variability results of the SAM pattern for the period 1979–2018. The SAM‐intrinsic pattern variability analysis is based on the principal component analysis (PCA), which is carried out for the ERA‐Interim 500 hPa geopotential height (GPH) data set. A spatiotemporally resolved data set of SAM pattern maps (PCA loadings) is derived by projecting monthly shifted sub‐sequences of SAM index values (PCA scores) on the corresponding GPH anomalies. The dominant SAM structure within single pattern fields is mapped automatically and can be interpreted as the Southern Hemisphere polar front. This data set allows an analysis of the geographical positions of the characteristic circumpolar SAM structure over four decades and shows considerable variability over space and time. Five different states of SAM patterns, which are associated with characteristic circulation anomalies during different phases of the study period, are identified. Station‐based Antarctic temperature anomalies can be synoptically explained by these circulation anomalies. The overall latitudinal trend of the SAM pattern indicates an intensification of the meridional structure, especially over the East Antarctic Southern Ocean. Furthermore, we show that the SAM pattern variability is significantly correlated with the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation. Composites of 500 hPa GPH anomalies during the positive and negative phases of the respective indices indicate teleconnections with Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation, and this can explain latitudinal trends of the SAM pattern.
    Description: Key Points: We present a new approach to examine the spatiotemporal Southern Annular Mode pattern variability. Station‐based Antarctic temperature anomalies are related to different structures of the Southern Annular Mode. The trend pattern shows an increasing meridional structure and correlations with Pacific and Atlantic multidecadal oscillations.
    Description: DLR Management Board: Young Investigator Group Leader Program
    Keywords: 551.5 ; Southern Annular Mode ; SAM pattern variability ; Antarctic circulation variability ; Antarctic station temperature ; PDO ; AMO
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  • 6
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    Influence of Radiation on Evaporation Rates: A Numerical Analysis (2021)
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    Publication Date: 2021-07-03
    Description: We present a fully coupled soil‐atmosphere model that includes radiation in the energy balance of the coupling conditions between the two domains. The model is able to describe evaporation processes under the influence of turbulence, surface roughness, and soil heterogeneities and focuses specifically on the influence of radiation on the mass and energy transport across the soil‐atmosphere interface. It is shown that evaporation rates are clearly dominated by the diurnal cycle of solar irradiance. During Stage‐I evaporation maximum temperatures are regulated due to evaporative cooling, but after a transition into Stage‐II evaporation, temperatures rise tremendously. We compare two different soil types, a coarser, sandy soil and a finer, silty soil, and analyze evaporation rates, surface temperatures, and net radiation for three different wind conditions. The influence of surface undulations on radiation and evaporation is analyzed and shows that radiation can lead to different local drying patterns in the hills and the valleys of the porous medium, depending on the height of the undulations and on the direction of the Sun. At last a comparison of lysimeter measurement data to the numerical examples shows a good match for measured and calculated radiation values but evaporation rates are still overestimated in the model. Possible reasons for the discrepancy between measurement and model data are analyzed and are found to be uncertainties about the parameters close to the interface, which are decisive for determining evaporation rates.
    Description: Key Points: We demonstrate the influence of radiation on evaporation rates. The influence of surface undulations on radiation and evaporation is analyzed. Comparison with experimental data shows the importance of interface processes.
    Description: Deutsche Forschungsgemeinschaft (DFG) http://dx.doi.org/10.13039/501100001659
    Keywords: 551.5 ; fully coupled soil‐atmosphere model ; evaporation and radiation ; turbulence
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  • 7
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    Clouds, radiation, and atmospheric circulation in the present‐day climate and under climate change (2021)
    John Wiley & Sons, Inc. | Hoboken, USA
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    Publication Date: 2021-07-03
    Description: By interacting with radiation, clouds modulate the flow of energy through the Earth system, the circulation of the atmosphere, and regional climate. We review the impact of cloud‐radiation interactions for the atmospheric circulation in the present‐day climate, its internal variability and its response to climate change. After summarizing cloud‐controlling factors and cloud‐radiative effects, we clarify the scope and limits of the Clouds On‐Off Klimate Model Intercomparison Experiment (COOKIE) and cloud‐locking modeling methods. COOKIE showed that the presence of cloud‐radiative effects shapes the circulation in the present‐day climate in many important ways, including the width of the tropical rain belts and the position of the extratropical storm tracks. Cloud locking, in contrast, identified how clouds affect internal variability and the circulation response to global warming. This includes strong, but model‐dependent, shortwave and longwave cloud impacts on the El‐Nino Southern Oscillation, and the finding that most of the poleward circulation expansion in response to global warming can be attributed to radiative changes in clouds. We highlight the circulation impact of shortwave changes from low‐level clouds and longwave changes from rising high‐level clouds, and the contribution of these cloud changes to model differences in the circulation response to global warming. The review in particular draws attention to the role of cloud‐radiative heating within the atmosphere. We close by raising some open questions which, among others, concern the need for studying the cloud impact on regional scales and opportunities created by the next generation of global storm‐resolving models. This article is categorized under: Climate Models and Modeling 〉 Knowledge Generation with Models
    Description: Clouds interact with radiation. We review the role of cloud‐radiation interactions in shaping the atmospheric circulation and thus regional climate and climate change. Figure from Blue Marble Collection of NASA Visible Earth.
    Description: U.S. Department of Energy's Office of Biological & Environmental Research
    Description: U.S. National Science Foundation
    Description: NERC CIRCULATES project
    Description: FONA: Research for Sustainable Development
    Description: German Ministry of Education and Research (BMBF) http://dx.doi.org/10.13039/501100002347
    Keywords: 551.5 ; circulation ; climate and climate change ; clouds ; global models ; radiation
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  • 8
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    Impact of Volcanic Aerosols on the Hydrology of the Asian Monsoon and Westerlies‐Dominated Subregions: Comparison of Proxy and Multimodel Ensemble Means (2021)
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    Publication Date: 2021-07-03
    Description: Proxy‐model comparisons show large discrepancies in the impact of volcanic aerosols on the hydrology of the Asian monsoon region (AMR). This was mostly imputed to uncertainties arising from the use of a single model in previous studies. Here we compare two groups of CMIP5 multimodel ensemble mean (MMEM) with the tree‐ring‐based reconstruction Monsoon Asia Drought Atlas (MADA PDSI), to examine their reliability in reproducing the hydrological effects of the volcanic eruptions in 1300–1850 CE. Time series plots indicate that the MADA PDSI and the MMEMs agree on the significant drying effect of volcanic perturbation over the monsoon‐dominated subregion, while disparities exist over the westerlies‐dominated subregion. Comparisons of the spatial patterns suggest that the MADA PDSI and the MMEMs show better agreement 1 year after the volcanic eruption than in the eruption year and in subregions where more tree‐ring chronologies are available. The MADA PDSI and the CMIP5 MMEMs agree on the drying effect of volcanic eruptions in western‐East Asia, South Asian summer monsoon, and northern East Asian summer monsoon (EASM) regions. Model results suggest significant wetting effect in southern EASM and western‐South Asia, which agrees with the observed hydrological response to the 1991 Mount Pinatubo eruption. Analysis on model output from the Last Millennium Ensemble project shows similar hydrological responses. These results suggest that the CMIP5 MMEM is able to reproduce the impact of volcanic eruptions on the hydrology of the southern AMR.
    Description: Key Points: Proxy and multimodel ensemble means agree (disagree) on post volcanic hydro‐responses over the Asian monsoon (westerlies)‐dominated subregion. Better agreement of spatial hydrological patterns is suggested 1 year after the eruption and in subregions with more tree‐ring data. Multimodel ensemble means can reproduce the hydrological response to volcanic perturbations in the southern Asian monsoon region.
    Keywords: 551.5 ; volcanic aerosol ; monsoon‐dominated subregion ; westerlies‐dominated subregion ; proxy data ; multimodel ensemble mean ; hydrological index
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  • 9
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    Machine Learning‐Based Prediction of Spatiotemporal Uncertainties in Global Wind Velocity Reanalyses (2021)
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    Publication Date: 2021-07-03
    Description: The characterization of uncertainties in geophysical quantities is an important task with widespread applications for time series prediction, numerical modeling, and data assimilation. In this context, machine learning is a powerful tool for estimating complex patterns and their evolution through time. Here, we utilize a supervised machine learning approach to dynamically predict the spatiotemporal uncertainty of near‐surface wind velocities over the ocean. A recurrent neural network (RNN) is trained with reanalyzed 10 m wind velocities and corresponding precalculated uncertainty estimates during the 2012–2016 time period. Afterward, the neural network's performance is examined by analyzing its prediction for the subsequent year 2017. Our experiments show that a recurrent neural network can capture the globally prevalent wind regimes without prior knowledge about underlying physics and learn to derive wind velocity uncertainty estimates that are only based on wind velocity trajectories. At single training locations, the RNN‐based wind uncertainties closely match with the true reference values, and the corresponding intra‐annual variations are reproduced with high accuracy. Moreover, the neural network can predict global lateral distribution of uncertainties with small mismatch values after being trained only at a few isolated locations in different dynamic regimes. The presented approach can be combined with numerical models for a cost‐efficient generation of ensemble simulations or with ensemble‐based data assimilation to sample and predict dynamically consistent error covariance information of atmospheric boundary forcings.
    Description: Plain Language Summary: Machine learning is increasingly used for a wide range of applications in geosciences. In this study, we use an artificial neural network in the context of time series prediction. In particular, the goal is to use a neural network for learning spatial and temporal uncertainties that are associated with globally estimated wind velocities. Three well‐known wind velocity products are used for the time period 2012–2016 in different training, validation, and prediction scenarios. Our experiments show that a neural network can learn the prevailing global wind regimes and associate these with corresponding uncertainty estimates. Such a trained neural network can be used for different applications, for example, a cost‐efficient generation of ensemble simulations or for improving traditional data assimilation schemes.
    Description: Key Points: A recurrent neural network is set up to predict spatiotemporal uncertainties in wind velocity reanalyses. Global uncertainty maps can be derived from only few individual training locations. This method has benefits for time series prediction, ensemble simulations, and data assimilation.
    Keywords: 551.5 ; machine learning ; artificial neural network ; wind velocity ; atmospheric reanalysis ; ensemble simulation ; data assimilation
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  • 10
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    Probabilistic Models Significantly Reduce Uncertainty in Hurricane Harvey Pluvial Flood Loss Estimates (2021)
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    Publication Date: 2021-04-22
    Description: Pluvial flood risk is mostly excluded in urban flood risk assessment. However, the risk of pluvial flooding is a growing challenge with a projected increase of extreme rainstorms compounding with an ongoing global urbanization. Considered as a flood type with minimal impacts when rainfall rates exceed the capacity of urban drainage systems, the aftermath of rainfall‐triggered flooding during Hurricane Harvey and other events show the urgent need to assess the risk of pluvial flooding. Due to the local extent and small‐scale variations, the quantification of pluvial flood risk requires risk assessments on high spatial resolutions. While flood hazard and exposure information is becoming increasingly accurate, the estimation of losses is still a poorly understood component of pluvial flood risk quantification. We use a new probabilistic multivariable modeling approach to estimate pluvial flood losses of individual buildings, explicitly accounting for the associated uncertainties. Except for the water depth as the common most important predictor, we identified the drivers for having loss or not and for the degree of loss to be different. Applying this approach to estimate and validate building structure losses during Hurricane Harvey using a property level data set, we find that the reliability and dispersion of predictive loss distributions vary widely depending on the model and aggregation level of property level loss estimates. Our results show that the use of multivariable zero‐inflated beta models reduce the 90% prediction intervalsfor Hurricane Harvey building structure loss estimates on average by 78% (totalling U.S.$3.8 billion) compared to commonly used models.
    Description: Key Points Recent severe pluvial flood events highlight the need to integrate pluvial flooding in urban flood risk assessment Probabilistic models provide reliable estimation of pluvial flood loss across spatial scales Beta distribution model reduces the 90% prediction interval for Hurricane Harvey building loss by U.S.$3.8 billion or 78%
    Description: Bundesministerium für Bildung und Forschung (BMBF) http://dx.doi.org/10.13039/501100002347
    Description: NSF GRFP
    Description: Fulbright Doctoral Program
    Keywords: 551.5 ; pluvial flooding ; loss modeling ; urban flooding ; probabilistic ; Hurricane Harvey ; climate change adaptation
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