CLOUDS AND MORE: ARM Climate Modeling Best Estimate Data

By S. Xie, R. McCoy, Stephen A. Klein, R. Cederwall, W. Wiscombe, M. Jensen, Karen L. Johnson, Eugene E. Clothiaux, K. Gaustad, C. Long and 9 more. 2010

146 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/1fb3fb379af4f627dd4f5acb5a82c40cce868aa7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Baike Xi
2. S. Xie
3. Xiquan Dong
4. Richard G. Forbes
5. M. Ahlgrimm
6. Guang J. Zhang
7. Tongwen Wu

In Global and Planetary Change

1. Baike Xi
2. S. Xie
3. Xiquan Dong
4. Richard G. Forbes
5. M. Ahlgrimm
6. Guang J. Zhang
7. Tongwen Wu

Citations in the corpus

• A Comparison of MERRA and NARR Reanalyses with the DOE ARM SGP Data (2011, methodology): “The ARM SGP site is representative of a continental climate in the midlatitudes, and it has been used successfully in the past to evaluate a variety of model simulations, including the NCEP Eta Model (Hinkelman et al. 1999), ECMWF (Xie et al. 2004), and the NCEP Global Forecast System (GFS) (Yang et”
• On the Representation of High-Latitude Boundary Layer Mixed-Phase Cloud in the ECMWF Global Model (2014, methodology): “The cloud fraction is derived from themillimeter wavelength cloud radar (MMCR) and the micropulse lidar (MPL) and is available as part of the Cloud Modeling Best Estimate (CMBE) value-added product (Xie et al. 2010).”