This data product, formerly known as Climate Modeling Best Estimate (CMBE) dataset, was created to encourage greater use of ARM data in climate studies and model development by the climate community. It assembles a best estimate of cloud, radiation, atmospheric quantities, and surface/land properties that are both well observed by ARM and commonly used in model evaluation into one single dataset. Most of these quantities are measured by ARM ground-based instruments for over two decades, including cloud radars, micropulse lidars (MPLs), laser ceilometers, microwave radiometers (MWRs), solar and infrared radiation stations (SIRSs), etc. The ARMBE data product is specifically tailored to climate modelers for use in the evaluation of global climate models, with hourly temporal resolution comparable to a typical resolution used in climate model output. It also includes standard deviations within the averaged hour and quality control flags for the selected quantities to indicate the temporal variability and data quality.
ARMBE provides detailed observations of clouds and their associated large-scale environment in different climate regimes and is widely applied in process studies to improve cloud parameterization in climate models. Additionally, the long-term ARMBE dataset of cloud observations from ground-based radars and lidars, with hourly resolution and high vertical resolution, makes it a great fit to examine climate variability and change, as well as to statistically evaluate climate models. The ARMBE data product also serves as input to many ARM value-added products (VAPs), such as the ARM Diagnostics for Climate Model Evaluation (ADCME), the large-scale forcing data from constrained variational analysis (VARANAL) and etc.
The ARMBE data product includes ARMBEATM and ARMBECLDRAD. ARMBEATM contains basic atmospheric quantities, and ARMBECLDRAD provides cloud and radiation quantities.
ARMBE represents single-point measurements. Statistics are recommended for comparing with climate model output, which often represents a grid-box mean of 100 km. In addition, although stringent QCs are applied, ARMBE still suffers most data quality issues in the VAPs that are used to produce ARMBE. These include Active Remote Sensing of Clouds (ARSCL), Data Quality Assessment for ARM Radiation DATA (QCRAD), and Microwave Radiometer Retrievals (MWRRET).