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- Author or Editor: Thomas J. Greenwald x
- Journal of Applied Meteorology and Climatology x
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Abstract
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Abstract
Synthetic infrared brightness temperatures (BTs) derived from a high-resolution Weather Research and Forecasting (WRF) model simulation over the contiguous United States are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) observations to assess the accuracy of the model-simulated cloud field. A sophisticated forward radiative transfer model (RTM) is used to compute the synthetic MODIS observations. A detailed comparison of synthetic and real MODIS 11-μm BTs revealed that the model simulation realistically depicts the spatial characteristics of the observed cloud features. Brightness temperature differences (BTDs) computed for 8.5–11 and 11–12 μm indicate that the combined numerical model–RTM system realistically treats the radiative properties associated with optically thin cirrus clouds. For instance, much larger 11–12-μm BTDs occurred within thin clouds surrounding optically thicker, mesoscale cloud features. Although the simulated and observed BTD probability distributions for optically thin cirrus clouds had a similar range of positive values, the synthetic 11-μm BTs were much colder than observed. Previous studies have shown that MODIS cloud optical thickness values tend to be too large for thin cirrus clouds, which contributed to the apparent cold BT bias in the simulated thin cirrus clouds. Errors are substantially reduced after accounting for the observed optical thickness bias, which indicates that the thin cirrus clouds are realistically depicted during the model simulation.
Abstract
Synthetic infrared brightness temperatures (BTs) derived from a high-resolution Weather Research and Forecasting (WRF) model simulation over the contiguous United States are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) observations to assess the accuracy of the model-simulated cloud field. A sophisticated forward radiative transfer model (RTM) is used to compute the synthetic MODIS observations. A detailed comparison of synthetic and real MODIS 11-μm BTs revealed that the model simulation realistically depicts the spatial characteristics of the observed cloud features. Brightness temperature differences (BTDs) computed for 8.5–11 and 11–12 μm indicate that the combined numerical model–RTM system realistically treats the radiative properties associated with optically thin cirrus clouds. For instance, much larger 11–12-μm BTDs occurred within thin clouds surrounding optically thicker, mesoscale cloud features. Although the simulated and observed BTD probability distributions for optically thin cirrus clouds had a similar range of positive values, the synthetic 11-μm BTs were much colder than observed. Previous studies have shown that MODIS cloud optical thickness values tend to be too large for thin cirrus clouds, which contributed to the apparent cold BT bias in the simulated thin cirrus clouds. Errors are substantially reduced after accounting for the observed optical thickness bias, which indicates that the thin cirrus clouds are realistically depicted during the model simulation.
Abstract
In this study, the accuracy of a simulated infrared brightness temperature dataset derived from a unique large-scale, high-resolution Weather Research and Forecasting (WRF) Model simulation is evaluated through a comparison with Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations. Overall, the analysis revealed that the simulated brightness temperatures realistically depict many of the observed features, although several large discrepancies were also identified. The similar shapes of the simulated and observed probability distributions calculated for each infrared band indicate that the model simulation realistically depicted the cloud morphology and relative proportion of clear and cloudy pixels. A traditional error analysis showed that the largest model errors occurred over central Africa because of a general mismatch in the locations of deep tropical convection and intervening regions of clear skies and low-level cloud cover. A detailed inspection of instantaneous brightness temperature difference (BTD) imagery showed that the modeling system realistically depicted the radiative properties associated with various cloud types. For instance, thin cirrus clouds along the edges of deep tropical convection and within midlatitude cloud shields were characterized by much larger 10.8 − 12.0-μm BTD than optically thicker clouds. Simulated ice clouds were effectively discriminated from liquid clouds and clear pixels by the close relationship between positive 8.7 − 10.8-μm BTD and the coldest 10.8-μm brightness temperatures. Comparison of the simulated and observed BTD probability distributions revealed that the liquid and mixed-phase cloud-top properties were consistent with the observations, whereas the narrower BTD distributions for the colder 10.8-μm brightness temperatures indicated that the microphysics scheme was unable to simulate the full dynamic range of ice clouds.
Abstract
In this study, the accuracy of a simulated infrared brightness temperature dataset derived from a unique large-scale, high-resolution Weather Research and Forecasting (WRF) Model simulation is evaluated through a comparison with Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations. Overall, the analysis revealed that the simulated brightness temperatures realistically depict many of the observed features, although several large discrepancies were also identified. The similar shapes of the simulated and observed probability distributions calculated for each infrared band indicate that the model simulation realistically depicted the cloud morphology and relative proportion of clear and cloudy pixels. A traditional error analysis showed that the largest model errors occurred over central Africa because of a general mismatch in the locations of deep tropical convection and intervening regions of clear skies and low-level cloud cover. A detailed inspection of instantaneous brightness temperature difference (BTD) imagery showed that the modeling system realistically depicted the radiative properties associated with various cloud types. For instance, thin cirrus clouds along the edges of deep tropical convection and within midlatitude cloud shields were characterized by much larger 10.8 − 12.0-μm BTD than optically thicker clouds. Simulated ice clouds were effectively discriminated from liquid clouds and clear pixels by the close relationship between positive 8.7 − 10.8-μm BTD and the coldest 10.8-μm brightness temperatures. Comparison of the simulated and observed BTD probability distributions revealed that the liquid and mixed-phase cloud-top properties were consistent with the observations, whereas the narrower BTD distributions for the colder 10.8-μm brightness temperatures indicated that the microphysics scheme was unable to simulate the full dynamic range of ice clouds.
Abstract
Refinements and improvements of an earlier technique to retrieve the cloud liquid water path (LWP) of nonprecipitating clouds over land surfaces using Special Sensor Microwave/Imager (SSM/I) 85.5-GHz measurements are presented. These techniques require estimates of the microwave surface emissivity, which are derived in clear-sky regions from SSM/I measurements and window infrared measurements from the Visible and Infrared Spin Scan Radiometer on GOES-7. A comparison of forward model calculations with SSM/I measurements in clear regions demonstrates that over a 7-day period the surface emissivities are stable.
To overcome limitations in the single-channel retrieval method under certain situations, a new method is developed that uses a normalized polarization difference (NPD) of the brightness temperatures. This method has the advantages of providing estimates of the LWP for low clouds and being extremely insensitive to the surface skin temperature. Radiative transfer simulations also show that the polarization difference at 37 GHz may be useful for retrievals in high water vapor environments and for large cloud LWP.
An intercomparison of the different retrieval methods over Platteville, Colorado, reveals large discrepancies for certain cases, but the NPD method is found to agree best with coincident ground-based microwave radiometer measurements of cloud LWP. This success is primarily due to the larger than average surface polarization differences near the Platteville site. While the NPD method shows promise in distinguishing between low, moderate, and high values of cloud LWP, a comprehensive validation effort is required to further evaluate its accuracy and limitations.
Abstract
Refinements and improvements of an earlier technique to retrieve the cloud liquid water path (LWP) of nonprecipitating clouds over land surfaces using Special Sensor Microwave/Imager (SSM/I) 85.5-GHz measurements are presented. These techniques require estimates of the microwave surface emissivity, which are derived in clear-sky regions from SSM/I measurements and window infrared measurements from the Visible and Infrared Spin Scan Radiometer on GOES-7. A comparison of forward model calculations with SSM/I measurements in clear regions demonstrates that over a 7-day period the surface emissivities are stable.
To overcome limitations in the single-channel retrieval method under certain situations, a new method is developed that uses a normalized polarization difference (NPD) of the brightness temperatures. This method has the advantages of providing estimates of the LWP for low clouds and being extremely insensitive to the surface skin temperature. Radiative transfer simulations also show that the polarization difference at 37 GHz may be useful for retrievals in high water vapor environments and for large cloud LWP.
An intercomparison of the different retrieval methods over Platteville, Colorado, reveals large discrepancies for certain cases, but the NPD method is found to agree best with coincident ground-based microwave radiometer measurements of cloud LWP. This success is primarily due to the larger than average surface polarization differences near the Platteville site. While the NPD method shows promise in distinguishing between low, moderate, and high values of cloud LWP, a comprehensive validation effort is required to further evaluate its accuracy and limitations.
