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- Author or Editor: Gerald L. Potter x
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Abstract
The Oregon State University/Lawrence Livermore National Laboratory general circulation model has been employed as a vehicle for suggesting and exploring various means of converting narrow-band measurements of reflected solar radiation from the earth-atmosphere system to broad-band quantities. For purely illustrative purposes we have adapted, within the model's solar radiation routine, a narrow-band filter function consisting of a square-wave window extending from 0.5 to 0.9 μm. A limitation of the model, for this sort of endeavor, is that it does not include the wavelength dependence of surface albedos. Nevertheless the model simulations tend to mimic the calibration of a narrow-band instrument, utilizing reflected solar radiation from the earth-atmosphere system as simultaneously measured by a collocated broad-band instrument; for the model, however, this is done in terms of fluxes, in contrast to instrument-measured radiances. The model results suggest that it might be preferable to perform narrow- to broad-band conversions in terms of planetary albedo (or an equivalent quantity), rather than in terms of reflected fluxes or radiances. Further improvement is achieved if, for instruments that can differentiate between clear and overcast conditions, separate clear and overcast calibrations are performed.
Abstract
The Oregon State University/Lawrence Livermore National Laboratory general circulation model has been employed as a vehicle for suggesting and exploring various means of converting narrow-band measurements of reflected solar radiation from the earth-atmosphere system to broad-band quantities. For purely illustrative purposes we have adapted, within the model's solar radiation routine, a narrow-band filter function consisting of a square-wave window extending from 0.5 to 0.9 μm. A limitation of the model, for this sort of endeavor, is that it does not include the wavelength dependence of surface albedos. Nevertheless the model simulations tend to mimic the calibration of a narrow-band instrument, utilizing reflected solar radiation from the earth-atmosphere system as simultaneously measured by a collocated broad-band instrument; for the model, however, this is done in terms of fluxes, in contrast to instrument-measured radiances. The model results suggest that it might be preferable to perform narrow- to broad-band conversions in terms of planetary albedo (or an equivalent quantity), rather than in terms of reflected fluxes or radiances. Further improvement is achieved if, for instruments that can differentiate between clear and overcast conditions, separate clear and overcast calibrations are performed.
Abstract
In order to better identify and more fully understand the differences in sensitivity among climate models, two quite different models are systematically compared in terms of their seasonal response. The two-dimensional statistical dynamical model (SDM) developed at the Lawrence Livermore National Laboratory and the Oregon State University three-dimensional general circulation model (GCM) were integrated using as closely comparable boundary conditions and forcing as possible. Comparison of the seasonal anomaly (defined as the departure of the monthly zonal average from the zonal annual mean at each latitude) shows that the models agree quite well in terms of the seasonal phase and amplitude of net radiation simulated at the top of the atmosphere, the tropospheric average temperature and surface temperature and the precipitation. The models also resemble the observed seasonal anomalies of these variables to a reasonable degree, although there are significant errors in each formulation.
Abstract
In order to better identify and more fully understand the differences in sensitivity among climate models, two quite different models are systematically compared in terms of their seasonal response. The two-dimensional statistical dynamical model (SDM) developed at the Lawrence Livermore National Laboratory and the Oregon State University three-dimensional general circulation model (GCM) were integrated using as closely comparable boundary conditions and forcing as possible. Comparison of the seasonal anomaly (defined as the departure of the monthly zonal average from the zonal annual mean at each latitude) shows that the models agree quite well in terms of the seasonal phase and amplitude of net radiation simulated at the top of the atmosphere, the tropospheric average temperature and surface temperature and the precipitation. The models also resemble the observed seasonal anomalies of these variables to a reasonable degree, although there are significant errors in each formulation.
Abstract
The ability of the ECMWF model (cycle 33) to simulate the Indian and East Asian summer monsoons is evaluated at four different horizontal resolutions: T21, T42, T63, and T1O6. Generally, with respect to the large-scale features of the circulation, the largest differences among the simulations occur at T42 relative to T21. However, on regional scales, important differences among the high-frequency temporal variability serve as a further critical rest of the model's ability to simulate the monsoon.
T106 best captures both the spatial and temporal characteristics of the Indian and East Asian monsoons, whereas T42 fails to correctly simulate the sequence and development of synoptic-scale milestones that characterize the monsoon flow. In particular, T106 is superior at simulating the development and migration of the monsoon trough over the Bay of Bengal. In the T42 simulation, the development of the monsoon occurs one month earlier than typically observed. At this time the trough is incorrectly located adjacent to the east coast of India, which results in an underestimate of precipitation over the Burma-Thailand region. This early establishment of the monsoon trough affects the evolution of the East Asian monsoon and yields excessive preseason rainfall over the Mei-yu region. EOF analysis of precipitation over China indicates that T106 best simulates the Mei-yu mode of variability, which is associated with an oscillation of the rainband that gives rise to periods of enhanced rainfall over the Yangtze River valley. The coarse resolution of T21 precludes simulation of the aforementioned regional-scale monsoon flows.
Abstract
The ability of the ECMWF model (cycle 33) to simulate the Indian and East Asian summer monsoons is evaluated at four different horizontal resolutions: T21, T42, T63, and T1O6. Generally, with respect to the large-scale features of the circulation, the largest differences among the simulations occur at T42 relative to T21. However, on regional scales, important differences among the high-frequency temporal variability serve as a further critical rest of the model's ability to simulate the monsoon.
T106 best captures both the spatial and temporal characteristics of the Indian and East Asian monsoons, whereas T42 fails to correctly simulate the sequence and development of synoptic-scale milestones that characterize the monsoon flow. In particular, T106 is superior at simulating the development and migration of the monsoon trough over the Bay of Bengal. In the T42 simulation, the development of the monsoon occurs one month earlier than typically observed. At this time the trough is incorrectly located adjacent to the east coast of India, which results in an underestimate of precipitation over the Burma-Thailand region. This early establishment of the monsoon trough affects the evolution of the East Asian monsoon and yields excessive preseason rainfall over the Mei-yu region. EOF analysis of precipitation over China indicates that T106 best simulates the Mei-yu mode of variability, which is associated with an oscillation of the rainband that gives rise to periods of enhanced rainfall over the Yangtze River valley. The coarse resolution of T21 precludes simulation of the aforementioned regional-scale monsoon flows.
No Abstract available.
No Abstract available.
Abstract
The Modern-Era Retrospective Analysis for Research and Application (MERRA) is a reanalysis designed to produce an improved representation of the Earth’s hydrologic cycle. This study examines the representation of deep convective clouds in MERRA, comparing analyzed liquid and ice clouds with deep convective cloud objects observed by instruments on the Tropical Rainfall Measuring Mission satellite. Results show that MERRA contains deep convective cloud in 98.1% of the observed cases. MERRA-derived probability density functions (PDFs) of cloud properties have a similar form as the observed PDFs and exhibit a similar trend with changes in object size. Total water path, optical depth, and outgoing shortwave radiation (OSR) in MERRA are found to match the cloud object observations quite well; however, there appears to be a bias toward higher-than-observed cloud tops in the MERRA. The reanalysis fits the observations most closely for the largest class of convective systems, with performance generally decreasing with a transition to smaller convective systems. Comparisons of simulated total water path, optical depth, and OSR are found to be highly sensitive to the assumed subgrid distribution of condensate and indicate the need for caution when interpreting model-data comparisons that require disaggregation of grid-scale cloud to satellite pixel scales.
Abstract
The Modern-Era Retrospective Analysis for Research and Application (MERRA) is a reanalysis designed to produce an improved representation of the Earth’s hydrologic cycle. This study examines the representation of deep convective clouds in MERRA, comparing analyzed liquid and ice clouds with deep convective cloud objects observed by instruments on the Tropical Rainfall Measuring Mission satellite. Results show that MERRA contains deep convective cloud in 98.1% of the observed cases. MERRA-derived probability density functions (PDFs) of cloud properties have a similar form as the observed PDFs and exhibit a similar trend with changes in object size. Total water path, optical depth, and outgoing shortwave radiation (OSR) in MERRA are found to match the cloud object observations quite well; however, there appears to be a bias toward higher-than-observed cloud tops in the MERRA. The reanalysis fits the observations most closely for the largest class of convective systems, with performance generally decreasing with a transition to smaller convective systems. Comparisons of simulated total water path, optical depth, and OSR are found to be highly sensitive to the assumed subgrid distribution of condensate and indicate the need for caution when interpreting model-data comparisons that require disaggregation of grid-scale cloud to satellite pixel scales.
Abstract
A method is described for analyzing the feedback and synergistic contributions of temperature, water vapor, cloud cover, surface albedo and CO2 to the change in the radiation balance at the top of the atmosphere due to a perturbation in an annual-averaged zonal atmospheric climate model. The method is illustrated through analysis of a doubled CO2 experiment with the Lawrence Livermore. National Laboratory Statistical Dynamical Model (LLNL SDM). The method provides insight into the sensitivity of the model to feedback changes in individual parameters and how each parameter influences the effects of the others.
Abstract
A method is described for analyzing the feedback and synergistic contributions of temperature, water vapor, cloud cover, surface albedo and CO2 to the change in the radiation balance at the top of the atmosphere due to a perturbation in an annual-averaged zonal atmospheric climate model. The method is illustrated through analysis of a doubled CO2 experiment with the Lawrence Livermore. National Laboratory Statistical Dynamical Model (LLNL SDM). The method provides insight into the sensitivity of the model to feedback changes in individual parameters and how each parameter influences the effects of the others.
Abstract
The sensitivity of outgoing longwave flux to changes in cloud cover (∂F/∂A c) as defined by Cess (1976) must be evaluated carefully to avoid discrepancies arising from the interchange of averaging conventions. In a recent zonal atmospheric model experiment the global value of ∂F/∂A c was different in sign than in other calculations. This difference in behavior was traced to a latitudinal redistribution of cloud amount and height that occurred in the doubled CO2 experiment. However, when ∂F/∂A c was evaluated at individual latitudes and then weighted globally, the value of this parameter was consistent with those found by Cess (1976) and Budyko (1974).
Abstract
The sensitivity of outgoing longwave flux to changes in cloud cover (∂F/∂A c) as defined by Cess (1976) must be evaluated carefully to avoid discrepancies arising from the interchange of averaging conventions. In a recent zonal atmospheric model experiment the global value of ∂F/∂A c was different in sign than in other calculations. This difference in behavior was traced to a latitudinal redistribution of cloud amount and height that occurred in the doubled CO2 experiment. However, when ∂F/∂A c was evaluated at individual latitudes and then weighted globally, the value of this parameter was consistent with those found by Cess (1976) and Budyko (1974).
ABSTRACT
We introduce a simple method for detecting changes, both transient and persistent, in reanalysis and merged satellite products due to both natural climate variability and changes to the data sources/analyses used as input. This note demonstrates this Histogram Anomaly Time Series (HATS) method using tropical ocean daily precipitation from MERRA-2 and from GPCP One-Degree Daily (1DD) precipitation estimates. Rather than averaging over space or time, we create a time series display of histograms for each increment of data (such as a day or month). Regional masks such as land–ocean can be used to isolate particular domains. While the histograms reveal subtle structures in the time series, we can amplify the signal by computing the histogram’s anomalies from its climatological seasonal cycle. The qualitative analysis provided by this scheme can then form the basis for more quantitative analyses of specific features, both real and analysis induced. As an example, in the tropical oceans the analysis clearly identifies changes in the time series of both reanalysis and observations that may be related to changing inputs.
ABSTRACT
We introduce a simple method for detecting changes, both transient and persistent, in reanalysis and merged satellite products due to both natural climate variability and changes to the data sources/analyses used as input. This note demonstrates this Histogram Anomaly Time Series (HATS) method using tropical ocean daily precipitation from MERRA-2 and from GPCP One-Degree Daily (1DD) precipitation estimates. Rather than averaging over space or time, we create a time series display of histograms for each increment of data (such as a day or month). Regional masks such as land–ocean can be used to isolate particular domains. While the histograms reveal subtle structures in the time series, we can amplify the signal by computing the histogram’s anomalies from its climatological seasonal cycle. The qualitative analysis provided by this scheme can then form the basis for more quantitative analyses of specific features, both real and analysis induced. As an example, in the tropical oceans the analysis clearly identifies changes in the time series of both reanalysis and observations that may be related to changing inputs.
