ARM Diagnostics for Climate Model Evaluation

Dataset · Fri Jan 01 04:00:00 EST 1999

DOI:https://doi.org/10.5439/1646838· OSTI ID:1646838

Zhang, Chengzhu ^[1]; Xie, Shaocheng

---

1. ORNL

A Python-based diagnostics package is currently being developed by the ARM Infrastructure Team to facilitate the use of long-term high-frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, and precipitation. This diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison. The ARM observational data constitute the core content of the diagnostics package. These data products include two types of data sets: 1. Observational data: we use long-term data sets available at SGP, NSA, and TWP  to build representative climatology. 2. CMIP5 climate model simulation data sets: these are auxiliary data sets for climate model evaluation. The Python-based diagnostics package is available at: https://github.com/ARM-DOE/arm-gcm-diagnostics 

• Research Organization: Atmospheric Radiation Measurement (ARM) Archive, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US); ARM Data Center, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER)
• Contributing Organization: PNNL, BNL, ANL, ORNL
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1646838
• Availability: ORNL
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
ARM
Cloud fraction
DOE.
Liquid water path
Longwave broadband downwelling irradiance
Longwave broadband upwelling irradiance
Precipitable water
Precipitation
Sensible heat flux
Shortwave broadband total downwelling irradiance
Shortwave broadband total upwelling irradiance
latent heat flux
surface air temperature
surface relative humidity