Fine-Scale Seasonal Climate Prediction

Background

Figure 1. The framework for fine-scale seasonal climate prediction
Figure 1. The framework for fine-scale seasonal climate prediction

Global seasonal climate predictions at about 100~200 km resolution issued by national climate centers provide reliable perspectives of the general circulation about six months in advance. Such forecasts, however, lack of the fine scale details that are critical to regional and local climate-sensitive business and decision-makers. To fill that need, we are developing a fine-scale seasonal climate prediction capability through dynamical downscaling. A framework for fine-scale seasonal climate prediction has been set up. In this framework, the global large-scale seasonal forecasts issued by the Weather Service’s Climate Forecast System (CFS) are applied to force the Weather Research and Forecasting (WRF) model. The version of the WRF model we use has been specially customized and configured for climate purpose.  Both deterministic and ensemble predictions can be performed. Techniques from Artificial Intelligence such as Principal Component Analysis and Self Organizing Map analysis are used to extract the relevant climate information.

PLANS

We will rely on the NCEP Climate Forecast System version 2 (CFSv2) operational run outputs for this task. For CFSv2, the real-time analysis is carried out by an atmospheric model at T574 (roughly 27 km grid spacing) in the horizontal and 64 sigma-pressure hybrid levels in the vertical. The real-time forecasts are carried out by the same atmospheric model but at T126 horizontal resolution (roughly 100 km grid spacing) and 64 sigma-pressure hybrid vertical levels. The CFSv2 system includes the interactive NOAH land surface model with 4 soil levels, the interactive Modular Ocean Model version 3 (MOM3), and the interactive 3-layer GFDL (Geophysical Fluid Dynamics Laboratory) Sea Ice Simulator sea ice model. A global ocean data assimilation system (GODAS) provides the ocean initial conditions for the CFSv2 analysis and forecasts. The real-time CFSv2 outputs include 7-month forecasts initialized at 00Z, 06Z, 12Z, and 18Z of each day as shown in Figure 1, as well as a single one season forecasts initialized at 00Z of each day and three 45-day forecasts initialized at 06Z, 12Z and 18Z of each day. We will utilize the 7-month forecasts.

Figure 1 Schematic of NCEP CFSv2 7-month forecasts.
Figure 1 Schematic of NCEP CFSv2 7-month forecasts.

The strategy is to first extensively evaluate the CFSv2 real-time forecasts focused on the CONUS domain. The evaluated variables will include  2-m temperature, 2-m relative humidity, 10-m wind speed, and wind direction, surface pressure, planetary boundary layer height (PBLH), precipitation, and 500-mb geopotential height. Low-level winds and PBLH are especially important for pollutant dispersion and transport. The observations will come from the NCEP Meteorological Assimilation Data Ingest System (MADIS). PBLH could be computed from the atmospheric soundings. The forecast lead time considered will range from one month, two months, one season to two seasons. Both spatial distributions and temporal evolution will be examined. On August 18, 2018, we started downloading and archiving the 4-times-daily 7-month CFSv2 forecasts. The downloaded files include the surface files (i.e., pgbf files) and the flux files (i.e., flxf files) initialized at 00Z, 06Z, 12Z and 18Z each day. The downloading has been continuing and, so far, we have downloaded nearly two months’ data files. With these data files, we can examine the climatic conditions out to 7 months. For example, Figure 2 shows the monthly mean 2-m temperature for March 2019. Clearly, there are similarities and differences in the simulated 2-m temperature valid for the same month between the different initialization times.

Figure 2 CFSv2 7-month forecasted 2-m temperature (degrees C) valid for March 2019 initialized at 00Z (top left), 06Z (top right), 12Z (bottom left) and 18Z (bottom right) on September 1, 2018.
Figure 2 CFSv2 7-month forecasted 2-m temperature (degrees C) valid for March 2019 initialized at 00Z (top left), 06Z (top right), 12Z (bottom left) and 18Z (bottom right) on September 1, 2018.

We are also in the process of downloading and archiving all of the conventional observations from MADIS for the months of September - December 2018 and January - May 2019. The observations will be used to evaluate the performance of the CFSv2 forecasts which will reveal the strengths and weaknesses of the CFSv2 monthly and seasonal forecasts.

For ensemble consideration, using the 4 times daily 7-month forecasts, we will create 4 ensemble members (e.g., 4 times same day forecasts), 8 ensemble members (e.g., 2-day forecasts), 12 and 16 ensemble members or a higher number of ensemble members that deems necessary. The optimum number of ensemble members will be based on examinations of performance statistics including ensemble means and ensemble spreading. Computational requirement and data volume will also be considered.