Meetings > PI / Science Team Meeting > Posters

Update on LLNL ARM Value-Added Products and Tools for Cloud Modeling Studies

 
Poster PDF

Authors

Shaocheng Xie — Lawrence Livermore National Laboratory
Xiao Chen — Lawrence Livermore National Laboratory
Qi Tang — Lawrence Livermore National Laboratory
Shuaiqi Tang — Pacific Northwest National Laboratory
Chengzhu Zhang — Lawrence Livermore National Laboratory
Yunyan Zhang — Lawrence Livermore National Laboratory
Yuying Zhang — Lawrence Livermore National Laboratory

Category

ARM infrastructure

Description

The goal of the Lawrence Livermore National Laboratory (LLNL) ARM Infrastructure Project is to provide necessary ARM Value-Added Products (VAPs) and develop useful tools for cloud modeling studies. This poster provides an update on recent ARM infrastructure and research activities conducted by the LLNL ARM project. Specifically, we will report the progress on 1) ARM Best Estimate (ARMBE) Data developments; 2) exploring forcing strategies for LASSO by using data from the newly established ARM boundary-layer profiling network and with the 3D variational analysis approach; 3) developing new land-atmosphere coupling strength diagnostics using ARM surface/land data at SGP; 4) developing ARM metrics and diagnostics including an ARM radar simulator for cloud evaluation with ARM detailed cloud observations. In addition, the idea of developing a data-centric uncertainty quantification framework through machine learning for quantifying ARM data uncertainty will be discussed. Examples of using these data and tools in cloud/climate modeling studies will be given. (This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-716499)