Evaluation of cloud microphysics schemes in simulations of a winter storm using radar and radiometer measurements

Han, Mei; Braun, Scott A.; Matsui, Toshihisa; Williams, C. R.

doi:10.1002/jgrd.50115

Cited by 61 publications

(59 citation statements)

References 52 publications

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“…Meanwhile, the Goddard scheme tended to underestimate fall speeds for all sizes (Molthan et al 2010). Whereas the Goddard scheme tended to underestimate fall speeds in Molthan et al (2010), Han et al (2013) found it provided the best agreement with observations acquired in snowfall located above the melting layer of a broader region of stratiform rainfall, which preceded a cold front affecting western California. Shi et al (2010) evaluated the performance of the Goddard scheme for lake-effect snow observed during C3VP through comparisons of observed and simulated C-and W-band radar reflectivities and AMSU-B brightness temperatures.…”

Section: Introductionmentioning

confidence: 52%

Comparisons of Modeled and Observed Reflectivities and Fall Speeds for Snowfall of Varied Riming Degrees during Winter Storms on Long Island, New York

Molthan

Colle

Yuter

et al. 2016

Monthly Weather Review

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Derived radar reflectivities and fall speeds for four Weather Research and Forecasting (WRF) Model bulk microphysical parameterizations (BMPs) run at 1.33-km grid spacing are compared with ground-based, vertically pointing Ku-band radar, scanning S-band radar, and in situ measurements at Stony Brook, New York. Simulations were partitioned into periods of observed riming degree as determined manually using a stereo microscope and camera during nine winter storms. Simulations were examined to determine whether the selected BMPs captured the effects of varying riming intensities, provided a reasonable match to the vertical structure of radar reflectivity or fall speed, and whether they produced reasonable surface fall speed distributions. Schemes assuming nonspherical mass-diameter relationships yielded reflectivity distributions closer to observed values. All four schemes examined in this study provided a better match to the observed, vertical structure of reflectivity during moderate riming than light riming periods. The comparison of observed and simulated snowfall speeds had mixed results. One BMP produced episodes of excessive cloud water at times, resulting in fall speeds that were too large. However, most schemes had frequent periods of little or no cloud water during moderate riming periods and thus underpredicted the snowfall speeds at lower levels. Short, 1-4-h periods with relatively steady snow conditions were used to compare BMP and observed size and fall speed distributions. These limited data suggest the examined BMPs underpredict fall speeds of coldtype snow habits and underrepresent aggregates larger than 4-mm diameter.

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Section: Introductionmentioning

confidence: 52%

Comparisons of Modeled and Observed Reflectivities and Fall Speeds for Snowfall of Varied Riming Degrees during Winter Storms on Long Island, New York

Molthan

Colle

Yuter

et al. 2016

Monthly Weather Review

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“…Since Morcrette (1991) first compared synthetic satellite imagery from NWP models with observed satellite BTs using a ''model-to-satellite approach,'' many studies have utilized satellite BTs to evaluate model performance (Chaboureau and Pinty 2006;Han et al 2013;Jankov et al 2010;Keil et al 2003;Otkin and Greenwald 2008;Otkin et al 2009;Ringer et al 2003;Sun and Rikus 2004). These studies have demonstrated the advantage of using satellite data and a model-to-satellite approach to validate numerical model results.…”

Section: Introductionmentioning

confidence: 95%

“…Satellite measurements, however, contain much higher spatial resolution with global coverage that permits a more comprehensive evaluation of the simulated cloud fields. Many prior studies have utilized satellite observations to evaluate the performance of NWP simulations (e.g., Chaboureau and Pinty 2006;Greenwald et al 2010;Han et al 2013;Jankov et al 2010;Keil et al 2003;Lopez et al 2003;Morcrette 1991;Nam and Quaas 2012;Otkin and Greenwald 2008;Otkin et al 2009;Ringer et al 2003;Satoh et al 2010;Sun and Rikus 2004;Tselioudis and Jakob 2002;Yu et al 1996;Zhang et al 2001).…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Accuracy of a High-Resolution Model Simulation through Comparison with MODIS Observations

Lee

Otkin

Greenwald

2014

Journal of Applied Meteorology and Climatology

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Synthetic infrared brightness temperatures (BTs) derived from a high-resolution Weather Research andForecasting (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-mm 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 mm 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-mm 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-mm 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.

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“…For example, Han et al [2013] used satellite microwave brightness temperature (Tb) and ground-based Doppler radar signals for evaluating different bulk microphysics schemes in the Weather Research and Forecasting (WRF) model. Hashino et al [2013] used satellite radar and lidar signals to evaluate cloud microphysics simulation from a global storm-resolving model.…”

Section: Introductionmentioning

confidence: 99%

Introducing multisensor satellite radiance-based evaluation for regional Earth System modeling

Matsui

Santanello

Shi

et al. 2014

J. Geophys. Res. Atmos.

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Earth System modeling has become more complex, and its evaluation using satellite data has also become more difficult due to model and data diversity. Therefore, the fundamental methodology of using satellite direct measurements with instrumental simulators should be addressed especially for modeling community members lacking a solid background of radiative transfer and scattering theory. This manuscript introduces principles of multisatellite, multisensor radiance-based evaluation methods for a fully coupled regional Earth System model: NASA-Unified Weather Research and Forecasting (NU-WRF) model. We use a NU-WRF case study simulation over West Africa as an example of evaluating aerosol-cloud-precipitation-land processes with various satellite observations. NU-WRF-simulated geophysical parameters are converted to the satellite-observable raw radiance and backscatter under nearly consistent physics assumptions via the multisensor satellite simulator, the Goddard Satellite Data Simulator Unit. We present varied examples of simple yet robust methods that characterize forecast errors and model physics biases through the spatial and statistical interpretation of various satellite raw signals: infrared brightness temperature (Tb) for surface skin temperature and cloud top temperature, microwave Tb for precipitation ice and surface flooding, and radar and lidar backscatter for aerosol-cloud profiling simultaneously. Because raw satellite signals integrate many sources of geophysical information, we demonstrate user-defined thresholds and a simple statistical process to facilitate evaluations, including the infrared-microwave-based cloud types and lidar/radar-based profile classifications.

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Evaluation of cloud microphysics schemes in simulations of a winter storm using radar and radiometer measurements

Cited by 61 publications

References 52 publications

Comparisons of Modeled and Observed Reflectivities and Fall Speeds for Snowfall of Varied Riming Degrees during Winter Storms on Long Island, New York

Comparisons of Modeled and Observed Reflectivities and Fall Speeds for Snowfall of Varied Riming Degrees during Winter Storms on Long Island, New York

Evaluating the Accuracy of a High-Resolution Model Simulation through Comparison with MODIS Observations

Introducing multisensor satellite radiance-based evaluation for regional Earth System modeling

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