Temperature and Water Vapor Variance Scaling in Global Models: Comparisons to Satellite and Aircraft Data

Kahn, Brian H.; Teixeira, J.; Fetzer, Eric J.; Gettelman, Andrew; Hristova-Veleva, S. M.; Huang, Xianglei; Kochanski, Adam K.; Köhler, Martin; Krueger, Steven K.; Wood, R.; Zhao, Ming

doi:10.1175/2011jas3737.1

Cited by 58 publications

(68 citation statements)

References 55 publications

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“…The extratropical scaling exponents of 0.42 and 0.44 are similar to, but slightly in excess of the classic Kolmogorov scaling of 1/3 (−5/3 in the power spectral domain). The tropical scaling exponent of 0.62 is in excess of the classic Kolmogorov scaling of 1/3 but is consistent with tropical cloud reflectance variability reported in Barker et al (2017) and mid-tropospheric water vapor mixing ratio in the tropics from the AIRS instrument, e.g., Kahn et al (2011). At finer spatial resolutions there is also evidence of scale breaks dependent on altitude.…”

Section: Resultssupporting

confidence: 82%

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Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005–2015

et al. 2018

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Abstract. The distribution of ice, liquid, and mixed phase clouds is important for Earth's planetary radiation budget, impacting cloud optical properties, evolution, and solar reflectivity. Most remote orbital thermodynamic phase measurements observe kilometer scales and are insensitive to mixed phases. This under-constrains important processes with outsize radiative forcing impact, such as spatial partitioning in mixed phase clouds. To date, the fine spatial structure of cloud phase has not been measured at global scales. Imaging spectroscopy of reflected solar energy from 1.4 to 1.8 µm can address this gap: it directly measures ice and water absorption, a robust indicator of cloud top thermodynamic phase, with spatial resolution of tens to hundreds of meters. We report the first such global high spatial resolution survey based on data from 2005 to 2015 acquired by the Hyperion imaging spectrometer onboard NASA's Earth Observer 1 (EO-1) spacecraft. Seasonal and latitudinal distributions corroborate observations by the Atmospheric Infrared Sounder (AIRS). For extratropical cloud systems, just 25 % of variance observed at GCM grid scales of 100 km was related to irreducible measurement error, while 75 % was explained by spatial correlations possible at finer resolutions.

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Section: Resultssupporting

confidence: 82%

“…At finer spatial resolutions there is also evidence of scale breaks dependent on altitude. Consequently the scaling exponent is dependent on the length scale range calculated (Kahn et al, 2011).…”

Section: Resultsmentioning

confidence: 99%

Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005–2015

et al. 2018

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“…We combine this with the scale-dependence of precipitation to show how resolved precipitation should change with resolution. Numerous studies demonstrate the scale-invariance of various other atmospheric quantities, including momentum (Nastrom and Gage, 1985), temperature (Kahn et al, 2011), humidity (Kahn et al, 2011;Pressel and Collins, 2012), cloud water (Davis et al, 1996), and other variables. We expect that the results from such studies can be used to constrain or even develop scale-aware parameterizations.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, to the extent that a model maintains a constant radiative divergence as resolution changes, then the global-mean precipitation rate should not change either. However, for aspects of climatology that are inherently scale dependent, such as the variance of atmospheric state variables, clouds, and precipitation (Pressel and Collins, 2012;Kahn et al, 2011;Nastrom and Gage, 1985;Wilcox and Ramanathan, 2001;Lovejoy et al, 2008), model statistics should almost certainly depend on resolution. Observations of scale dependence are key to understanding resolution dependence in models and ultimately key to building model schemes that are properly scale-aware.…”

Section: Introductionmentioning

confidence: 99%

Observed Scaling in Clouds and Precipitation and Scale Incognizance in Regional to Global Atmospheric Models

O’Brien¹,

Li²,

Collins

et al. 2013

J. Climate

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We use observations of robust scaling behavior in clouds and precipitation to derive constraints on how partitioning of precipitation should change with model resolution. Our analysis indicates that 90-99% of stratiform precipitation should occur in clouds that are resolvable by contemporary climate models (e.g., with 200 km or finer grid spacing). Furthermore, this resolved fraction of stratiform precipitation should increase sharply with resolution, such that effectively all stratiform precipitation should be resolvable above scales of ∼50 km. We show that the Community Atmosphere Model (CAM) and the Weather Research and Forecasting (WRF) model also exhibit the robust cloud and precipitation scaling behavior that is present in observations, yet the resolved fraction of stratiform precipitation actually decreases with increasing model resolution. A suite of experiments with multiple dynamical cores provides strong evidence that this 'scale-incognizant' behavior originates in one of the CAM4 parameterizations. An additional set of sensitivity experiments rules out both convection parameterizations, and by a process of elimination these results implicate the stratiform cloud and precipitation parameterization. Tests with the CAM5 physics package show improvements in the resolution-dependence of resolved cloud fraction and resolved stratiform precipitation fraction.

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“…Kahn et al (2011) compare the integrated water vapour (IWV) variability in NWP and climate models with those directly observed by Atmospheric InfraRed Sounder (AIRS) observations and airborne measurements with a focus on stratocumulus regions over ocean. They find large differences in the magnitude of IWV variance, leading to the conclusion that in the future satellite observations are needed with a higher resolution than currently planned (10-30 km).…”

Section: Rsmentioning

confidence: 99%

Assessment of small-scale integrated water vapour variability during HOPE

et al. 2015

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Abstract. The spatio-temporal variability of integrated water vapour (IWV) on small scales of less than 10 km and hours is assessed with data from the 2 months of the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP) 2 ) Observational Prototype Experiment (HOPE). The statistical intercomparison of the unique set of observations during HOPE (microwave radiometer (MWR), Global Positioning System (GPS), sun photometer, radiosondes, Raman lidar, infrared and near-infrared Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellites Aqua and Terra) measuring close together reveals a good agreement in terms of random differences (standard deviation ≤ 1 kg m −2 ) and correlation coefficient (≥ 0.98). The exception is MODIS, which appears to suffer from insufficient cloud filtering.For a case study during HOPE featuring a typical boundary layer development, the IWV variability in time and space on scales of less than 10 km and less than 1 h is investigated in detail. For this purpose, the measurements are complemented by simulations with the novel ICOsahedral Nonhydrostatic modelling framework (ICON), which for this study has a horizontal resolution of 156 m. These runs show that differences in space of 3-4 km or time of 10-15 min induce IWV variabilities on the order of 0.4 kg m −2 . This model finding is confirmed by observed time series from two MWRs approximately 3 km apart with a comparable temporal resolution of a few seconds.Standard deviations of IWV derived from MWR measurements reveal a high variability (> 1 kg m −2 ) even at very short time scales of a few minutes. These cannot be captured by the temporally lower-resolved instruments and by operational numerical weather prediction models such as COSMO-DE (an application of the Consortium for Small-scale Modelling covering Germany) of Deutscher Wetterdienst, which is included in the comparison. However, for time scales larger than 1 h, a sampling resolution of 15 min is sufficient to capture the mean standard deviation of IWV. The present study shows that instrument sampling plays a major role when climatological information, in particular the mean diurnal cycle of IWV, is determined.

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Temperature and Water Vapor Variance Scaling in Global Models: Comparisons to Satellite and Aircraft Data

Cited by 58 publications

References 55 publications

Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005–2015

Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005–2015

Observed Scaling in Clouds and Precipitation and Scale Incognizance in Regional to Global Atmospheric Models

Assessment of small-scale integrated water vapour variability during HOPE

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