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Ronald M. Errico, George Ohring, Fuzhong Weng, Peter Bauer, Brad Ferrier, Jean-François Mahfouf, and Joe Turk

skill (using standard measures) is initially neutral; 5) developing new forecast skill measures to evaluate the performance of NWP models regarding the presence of clouds and precipitation and their effects on other fields; and 6) conducting well-designed and carefully interpreted predictability experiments to determine what increase of precipitation and cloud forecast skill is a realistic target and what specific kinds of improvements are required to attain that skill. 6. Overarching recommendation

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Christopher W. O’Dell, Peter Bauer, and Ralf Bennartz

much higher than this, N IC = 100 with maximum-random overlap is taken to be a suitable reference model. As a side study, tests (not shown) comparing a 100-IC model using MR versus MAX cloud overlap schemes were performed in order to evaluate the microwave radiance differences produced between these two cloud overlap schemes. While some profiles had differences of several kelvin, the overall RMS difference ranged from 0.011 K at 19 GHz to 0.20 K at 85 GHz, indicating that in general, the

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K. Franklin Evans

.001) SHDOMPPDA offers comparable performance to DISORT for solar reflectance from optically thick clouds. In the thermal infrared SHDOMPPDA is five times faster than DISORT for 0.1-K rms accuracy. Further optimization of the SHDOMPPDA performance might be made by adjusting the layer splitting accuracy, which was not done here. b. Tangent linear and adjoint testing The SHDOMPPDA tangent linear and adjoint models are validated by comparison to finite differencing of the forward model. This testing has been

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Fuzhong Weng, Tong Zhu, and Banghua Yan

observations, many attempts were made to improve hurricane analyses for forecasts. Krishnamurti et al. (1991) developed a method to physically initialize the Florida State University global cumulus parameterization spectral model, which mainly depends upon the surface rain rates derived from the Special Sensor Microwave Imager (SSM/I). A comparison study was conducted by Tibbetts and Krishnamurti (2000) to evaluate the performance of four different rain-rate algorithms in hurricane track forecast using

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Chinnawat Surussavadee and David H. Staelin

cloud-resolving NWP model-based simulations for developing and evaluating microwave precipitation retrieval methods is motivated by the lack of trustworthy ground truth coincident with microwave observations. For example, there is no practical method for accurately observing the three-dimensional density, size, and habit distributions of various hydrometeor species at the same time their microwave emission spectrum is being continuously mapped from above. Although multifrequency Doppler radar

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Philippe Lopez

a limited-area model with increasing resolution. Quart. J. Roy. Meteor. Soc. , 131 , 2293 – 2312 . Gregory , D. , and P. R. Rowntree , 1990 : A mass flux convection scheme with representation of cloud ensemble characteristics and stability-dependent closure. Mon. Wea. Rev. , 118 , 1483 – 1506 . Grell , G. A. , 1993 : Prognostic evaluation of assumptions used by cumulus parameterizations. Mon. Wea. Rev. , 121 , 746 – 787 . Hollingsworth , A. , and P. Lönnberg , 1986

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Peter M. Norris and Arlindo M. da Silva

overprediction of low cloud fraction in winter high latitudes by both the climate run and the analysis, and the somewhat more complicated comparison between climate run, analysis, and data in the Tropics. The overall poor performance of the model both in climate mode and even more so in assimilation mode was the motivation for our efforts to assimilate observational cloud fraction data into the GEOS-4 DAS. b. Overview and design of the cloud parameter estimation system From the beginning we attempted to

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Ronald M. Errico, Peter Bauer, and Jean-François Mahfouf

fields evaluated for particular regions and pressure surfaces. At least one forecast center includes metrics obtained using adjoints of the assimilation and forecast model systems ( Langland and Baker 2004 ). In as complex a computational environment as data assimilation, methods such as the latter are necessary for sorting and making sense of the vast sets of information that can be produced. Forecasts, particularly at day 5, are often used rather than examination of analyses themselves because

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Graeme L. Stephens and Christian D. Kummerow

useful first step to any application of such data, including the assimilation of data into local-scale, regional, or global models. The following two sections provide a general background for discussion of satellite observing systems and provide the context for the rest of the paper. Section 3 provides the common framework used to critique the different methods. Sections 4 and 5 then critiques a selection of more popular cloud and precipitation methods. The intent is not to provide an

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Qing Yue, K. N. Liou, S. C. Ou, B. H. Kahn, P. Yang, and G. G. Mace

1. Introduction Satellite data assimilation in numerical weather prediction models requires an efficient and accurate radiative transfer model for the computation of radiances and Jacobians. Present thermal infrared radiative transfer models for satellite data assimilation have been developed primarily for clear conditions (i.e., pure absorbing atmospheres). However, many studies have found that a great majority of satellite observations is “contaminated” by clouds. For example, Saunders (2000

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