Maintenance of tropical tropopause layer cirrus Dinh, T. P.; Durran, D. R.; Ackerman, T. P.
Journal of Geophysical Research. B. Solid Earth,
27 January 2010, Letnik:
115, Številka:
D2
Journal Article
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A two‐dimensional cloud resolving model with explicit bin microphysics is used to study the maintenance of tropical tropopause layer (TTL) cirrus. Numerical simulations using this model show that a ...TTL cirrus with a maximum radiative heating rate of 3 K/day is able to self‐maintain for as long as 2 days if it contains ice crystals whose initial mean radius is smaller than about 5 μm. The key to the maintenance of the cloud is the circulation thermally forced by the cloud radiative heating. When the cloud layer is at ice saturation and temperature decreases with height, advection of water vapor by the thermally forced circulation results in water vapor flux convergence in the cloud. This leads to growth of ice crystals despite the diabatic warming produced by the radiative heating. The source of water vapor for the growth of ice crystals is outside the cloud lateral edge, which is outside the vertical column that contains the initial cloud. The conversion of water vapor into ice in the simulated TTL cirrus indicates its potential to dehydrate the surrounding environment. This dehydration mechanism does not involve adiabatic cooling associated with external large‐scale uplift.
Satellite observations and their corresponding instrument simulators are used to document global cloud biases in the Community Atmosphere Model (CAM) versions 4 and 5. The model–observation ...comparisons show that, despite having nearly identical cloud radiative forcing, CAM5 has a much more realistic representation of cloud properties than CAM4. In particular, CAM5 exhibits substantial improvement in three long-standing climate model cloud biases: 1) the underestimation of total cloud, 2) the overestimation of optically thick cloud, and 3) the underestimation of midlevel cloud. While the increased total cloud and decreased optically thick cloud in CAM5 result from improved physical process representation, the increased midlevel cloud in CAM5 results from the addition of radiatively active snow. Despite these improvements, both CAM versions have cloud deficiencies. Of particular concern, both models exhibit large but differing biases in the subtropical marine boundary layer cloud regimes that are known to explain intermodel differences in cloud feedbacks and climate sensitivity. More generally, this study demonstrates that simulator-facilitated evaluation of cloud properties, such as amount by vertical level and optical depth, can robustly expose large and at times radiatively compensating climate model cloud biases.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Saharan dust storms have often been observed from space, but the full impact on the Earth's radiation balance has been difficult to assess, due to limited observations from the surface. We present ...the first simultaneous observations from space and from a comprehensive new mobile facility in Niamey, Niger, of a major dust storm in March 2006. The results indicate major perturbations to the radiation balance both at the top of the atmosphere and at the surface. Combining the satellite and surface data, we also estimate the impact on the radiation balance of the atmosphere itself. Using independent data from the mobile facility, we derive the optical properties of the dust and input these and other information into two radiation models to simulate the radiative fluxes. We show that the radiation models underestimate the observed absorption of solar radiation in the dusty atmosphere.
Relative Energy Deficiency in Sport (REDs) has various different risk factors, numerous signs and symptoms and is heavily influenced by one's environment. Accordingly, there is no singular validated ...diagnostic test. This 2023 International Olympic Committee's REDs Clinical Assessment Tool-V.2 (IOC REDs CAT2) implements a three-step process of: (1) initial screening; (2) severity/risk stratification based on any identified REDs signs/symptoms (primary and secondary indicators) and (3) a physician-led final diagnosis and treatment plan developed with the athlete, coach and their entire health and performance team. The CAT2 also introduces a more clinically nuanced four-level traffic-light (green, yellow, orange and red) severity/risk stratification with associated sport participation guidelines. Various REDs primary and secondary indicators have been identified and 'weighted' in terms of scientific support, clinical severity/risk and methodological validity and usability, allowing for objective scoring of athletes based on the presence or absence of each indicator. Early draft versions of the CAT2 were developed with associated athlete-testing, feedback and refinement, followed by REDs expert validation via voting statements (ie, online questionnaire to assess agreement on each indicator). Physician and practitioner validity and usability assessments were also implemented. The aim of the IOC REDs CAT2 is to assist qualified clinical professionals in the early and accurate diagnosis of REDs, with an appropriate clinical severity and risk assessment, in order to protect athlete health and prevent prolonged and irreversible outcomes of REDs.
The Atmosphere Radiation Measurements Program's Ancillary Facility (AAF/SMART‐COMMIT) was deployed to Zhangye (39.082°N, 100.276°E), which is located in a semidesert area of northwest China, during ...the period of late April to mid June in 2008. We selected 11 cases to retrieve dust aerosol optical depth (AOD), Angstrom exponent, size distribution, single‐scattering albedo (SSA) and asymmetry parameter (ASY) from multifilter rotating shadowband radiometer (MFRSR) measurements. These cases are dominated by large particles with Angstrom exponent values ranging from 0.34 to 0.93. The values of AOD at 0.67 μm range from 0.07 to 0.25. The mean SSA value increases with wavelength from 0.76 ± 0.02 at 0.415 μm to 0.86 ± 0.01 at 0.870 μm, while the mean ASY value decreases from 0.74 ± 0.04 to 0.70 ± 0.02. Before estimating dust aerosol direct radiative forcing, a radiative closure experiment was performed to verify that the retrieved aerosol optical properties and other input parameters to the radiative transfer model appropriately represent atmospheric conditions. The daytime‐averaged differences between model simulations and ground observations are −8.5, −2.9, and −2.1 W m−2 for the total, diffuse, and direct normal fluxes, respectively. The mean difference in the instantaneous reflected solar fluxes at the top of atmosphere (TOA) between the model and CERES observations is 8.0 W m−2. The solar aerosol direct radiative forcing (ARF), averaged over a 24 h period, at the surface is −22.4 ± 8.9 W m−2, while the TOA ARF is small and has an average value of only 0.52 ± 1.69 W m−2. The daily averaged surface aerosol radiative forcing efficiency at 0.5 μm is −95.1 ± 10.3 W m−2τ−1. Our results illustrate that the primary role of dust aerosol is to alter the distribution of solar radiation within the climate system rather than to reflect solar energy to space. We assess the satellite aerosol optical depth products from Mutiangle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) observations by comparing them with our ground‐based retrievals. Reasonable agreements with the ground‐based observations are found for the MISR product and MODIS Deep Blue product.
We outline a methodology for estimating fractional sky cover for an effective 160° field of view from an analysis of surface measurements of downwelling total and diffuse shortwave (SW) irradiance. ...The data are screened for optically thicker overcast cases, after which an empirically derived formulation is used to estimate the fractional sky cover for the remaining data. The retrieved fractional sky cover time series is then evaluated to mitigate times of anomalous behavior caused by the thick overcast screening. The resultant sky cover estimates show a high degree of repeatability given nominally well maintained and operated radiometer systems and the use of the Long and Ackerman (2000) methodology for estimating the clear‐sky total and diffuse SW. Thus the resultant fractional sky‐cover estimates appear to be fairly independent of the particular climate regime and model of radiometers used, at least for the climate regimes we have tested so far. The sky‐cover estimates agree to better than 10% root mean square sky cover amount with sky imager retrievals and human observations, which is as good as the agreement between sky imaging systems and observers themselves. As such, this methodology becomes a powerful tool for satellite and model validations and climatological analyses including the study of trends in cloud amount. Analysis shows that the technique also produces realistic frequency distributions, showing that the continental midlatitude regimes included in the study are typified by clear‐sky occurring about 1/3 of the time, overcast about 1/3 of the time, and partly cloudy skies to varying extent occurring the remaining 1/3 of the time. By contrast, the tropical western Pacific oceanic regime during the Nauru99 field experiment exhibits far more frequent occurrence of partly cloudy skies, with sky cover amounts of 20% to 50% occurring about half the time.
Pervasive cirrus clouds in the upper troposphere and tropical tropopause layer (TTL) influence the climate by altering the top‐of‐atmosphere radiation balance and stratospheric water vapor budget. ...These cirrus are often associated with deep convection, which global climate models must parameterize and struggle to accurately simulate. By comparing high‐resolution global storm‐resolving models from the Dynamics of the Atmospheric general circulation Modeled On Non‐hydrostatic Domains (DYAMOND) intercomparison that explicitly simulate deep convection to satellite observations, we assess how well these models simulate deep convection, convectively generated cirrus, and deep convective injection of water into the TTL over representative tropical land and ocean regions. The DYAMOND models simulate deep convective precipitation, organization, and cloud structure fairly well over land and ocean regions, but with clear intermodel differences. All models produce frequent overshooting convection whose strongest updrafts humidify the TTL and are its main source of frozen water. Intermodel differences in cloud properties and convective injection exceed differences between land and ocean regions in each model. We argue that, with further improvements, global storm‐resolving models can better represent tropical cirrus and deep convection in present and future climates than coarser‐resolution climate models. To realize this potential, they must use available observations to perfect their ice microphysics and dynamical flow solvers.
Plain Language Summary
High‐altitude tropical cirrus (ice) clouds influence the earth's climate by reflecting sunlight, trapping upwelling radiative energy from the earth's surface, and affecting the temperature and humidity of the upper atmosphere. These clouds are initiated by systems of strong thunderstorms, whose most vigorous updrafts loft water vapor and ice high into the atmosphere. Computer models used to study the global climate struggle to accurately represent tropical thunderstorms because their updrafts are far narrower than the width of a modeled grid cell. Models with very fine grids can better represent the air flows that form these clouds. We investigate how well several fine‐grid models reproduce observed characteristics of tropical thunderstorm systems and cirrus. We find generally good agreement but also substantial differences between individual models, mainly because of their diverse ways of representing ice and snow formation and their evolution. With further observationally motivated improvements, such fine‐grid models should enable more reliable simulations of the role of tropical cirrus in our changing climate.
Key Points
Characteristics of tropical cirrus over land and ocean in nine global storm‐resolving models (GSRMs) scatter around observational ranges
Most GSRMs reasonably simulate convective organization and rainfall, but with diverse vertical cloud structure through the upper troposphere
Deep convection supplies most water to the tropical tropopause layer, with intermodel differences due to updraft speeds and microphysics
We present an automated method to identify periods of clear skies for a 160° field of view using only 1‐min measurements of surface downwelling total and diffuse shortwave irradiance. The clear‐sky ...detection method is verified using Whole Sky Imager and lidar data, observer reports, and model comparisons. Identified clear‐sky irradiance measurements are then used to empirically fit clear‐sky irradiance functions using the cosine of the solar zenith angle as the independent variable. These fitted functions produce continuous estimates of clear‐sky total, diffuse, and direct component shortwave irradiances. While this method ignores diurnal changes in such variables as column water vapor and aerosol amounts and changes between clear‐sky days, it is shown that the resultant clear‐sky irradiance estimates have RMS uncertainty comparable to the uncertainty of the measuring instruments themselves. The estimated clear‐sky irradiances are used to estimate the effect of clouds on the downwelling shortwave irradiance as a difference between the measured and clear‐sky amounts. We show that the cloud effect calculations from this method appear to decrease the uncertainty due to systematic pyranometer offsets and cosine response errors. Thus any data set that includes downwelling diffuse and total shortwave measurements can be processed to identify clear‐sky periods and produce estimates of clear‐sky irradiance and cloud effects.
Cirrus clouds of various thicknesses and radiative characteristics extend over much of the tropics, especially around deep convection. They are difficult to observe due to their high altitude and ...sometimes small optical depths. They are also difficult to simulate in conventional global climate models, which have coarse grid spacings and simplified parameterizations of deep convection and cirrus formation. We investigate the representation of tropical cirrus in global storm‐resolving models (GSRMs), which have higher spatial resolution and explicit convection and could more accurately represent cirrus cloud processes. This study uses GSRMs from the DYnamics of the Atmospheric general circulation Modeled On Non‐hydrostatic Domains (DYAMOND) project. The aggregate life cycle of tropical cirrus is analyzed using joint albedo and outgoing longwave radiation (OLR) histograms to assess the fidelity of models in capturing the observed cirrus cloud populations over representative tropical ocean and land regions. The proportions of optically thick deep convection, anvils, and cirrus vary across models and are portrayed in the vertical distribution of cloud cover and top‐of‐atmosphere radiative fluxes. Model differences in cirrus populations, likely driven by subgrid processes such as ice microphysics, dominate over regional differences between convectively active tropical land and ocean locations.
Plain Language Summary
Cirrus (ice) clouds vary in thickness and so have a wide range of impacts on Earth's energy budget. Unlike other clouds, thin cirrus reduce the amount of energy escaping to space, slightly warming the Earth. It is important to understand the differences in tropical cirrus cloud life cycles between models because tropical cirrus are a major source of uncertainty in the prediction of future climates. Cirrus clouds cover a large area in space and can last up to several days, yet they are difficult to measure with satellites and ground‐based instruments. We instead use computer models to simulate tropical cirrus, specifically global storm‐resolving models (GSRMs) which are able provide a level of detail not possible through observations. Unfortunately, most models have large biases in cloud properties. These differences arise from the imperfect representation of ice in the models. Our goal is to understand the model differences in representation of ice clouds using statistical analysis of the life cycle of cirrus in each model.
Key Points
Statistics of tropical cirrus in 40‐day high‐resolution model simulations scatter around observational estimates
The joint albedo‐OLR histogram is a good observationally testable diagnostic of cirrus life cycle
Large differences between models are driven by ice microphysics and model dynamics
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