Research plan and progress in HyARL

Hydrospheric Atmospheric Research Laboratory (HyARL) , Center for Orbital and Suborbital Observations is mainly conducting case study-based researches for cloud and precipitation systems. HyARC owns two polarimetric radars and is developing a cloud-resolving model referred to as “Cloud Resolving Storm Simulator (CReSS).” Using these tools, we study to clarify structures and formation/development processes of cloud and precipitation systems. For the VL research, we continuously improve CReSS based on validations using the radars and other observation instruments. The following items are research planning for the VL research in HyARL.

 1. Introduction of new processes and schemes into CReSS

The following processes and schemes are planned to be incorporated into CReSS.

  • Introduction of prognostic equations for the number densities in the liquid phase
  • Introduction of a hail category
  • Re-examination of ice nucleation processes
  • Introduction of atmospheric and cloud radiation processes
  • Introduction of the semi-Lagrangian time integration method

     2. Establishment of the validation methods for cloud-resolving simulations

    We are performing simulations using CReSS every day for around the Japanese Islands and over tropical oceanic regions. We are making a validation system for the simulation results using available routine observation data. In addition, Satellite Data Simulator Unit (SDSU) is applied to the CReSS simulation results, and then the SDSU retrievals are quantitatively compared with the quantities such as cloud top height and precipitable water derived from actual satellites. For this analysis, we are collaborating with CEReS of Chiba University. From these validation studies, we are accumulating effective information to improve the cloud microphysical processes in CReSS.

     3. Introduction of a data assimilation process into CReSS

    We plan to assimilate water vapor retrieved from horizontal distribution of satellite-derived precipitable water into CReSS. For precipitation, a nudging method has been already incorporated. In addition, introduction of assimilation methods using Ensemble Kalman Filter and variational methods is under consideration. The HyARC polarimetric radar data is expected to be utilized for the assimilations.

     4. Validation of parameterizations in GCMs

    In order to validate the parameters employed in a grid-scale condensation process incorporated in global circulation models (GCMs), statistical characteristics of those parameters are studied. Japanese university researchers are developing prediction schemes of cloud ice or the other parameters employed in a grid-scale condensation process. Using CReSS, we calculated quantities corresponding to those parameters appearing in GCMs. At present, the output data was prepared for only one case. We plan to increase cases and then to generalize concepts and quantities. Furthermore, quantities to validate vertical diabatic heating profiles in GCMs will be prepared from cloud-resolving simulation results

     5. Development of a GCM-CReSS coupling model with a tiling domain technique

    To improve GCM simulations, we developed a two-way nesting technique between a GCM and CReSS embedded into specified grids in a GCM. This technique is referred to as “super parameterization.” In our method, arbitrary grids in a GCM can be available for CReSS to be embedded. When CReSS is one-way nested in a GCM, the GCM-CReSS coupling model provides down-scaling simulations. Using this technique, we performed some simulations for a low-pressure system and the Baiu front. Furthermore, we are planning to simulate some phenomena, such as typhoon and MJO, in the present climate and precipitation systems in a global warming situation.