Warm Season Forecast Experiments with Different Treatments on Ground Water and Evaporative Parameterizations in the NCEP Coupled Forecast System

Skillful short-term weather forecasts, which rely heavily on quality atmospheric initial conditions, have a fundamental limit of about two weeks owing to the chaotic nature of the atmosphere. Useful forecasts at subseasonal to seasonal time scales, on the other hand, require well-simulated large-scale atmospheric response to slowly varying lower boundary forcings from both ocean and land surface. The critical importance of ocean has been recognized, the ocean indices have been used in a variety of climate applications. In contrast, impact of land surface anomalies, especially soil moisture and associated evaporation, has been proven notably difficult to demonstrate.

The Noah Land Surface Model (LSM) is the land component of NCEP CFS used for seasonal predictions. The Noah LSM originates from the Oregon State University (OSU) LSM. The evaporation control in the Noah LSM is based on the empirical Penman-Monteith equation, which takes into account the solar radiation, relative humidity, and soil moisture effects. The Noah LSM is configured with four soil layers with a fixed depth of 2 meters and free drainage at the bottom soil layer. This treatment assumes that the soil water table depth is well within the specified range. The treatment also potentially misrepresents the soil moisture memory effects at seasonal time scales.

To overcome ground water treatment limitation, an enhanced version of Noah Multiple Parameterization (Noah MP) LSM was developed. In the Noah MP LSM, an unconfined aquifer is attached to the bottom of the soil to allow the water table move freely up and down. In addition, an alternative Ball-Berry photosynthesis-based evaporation parameterization is available to examine the impact using a different evaporation control methodology.

To examine the impact of the physics treatments in the Noah LSMs on seasonal predictions, warm season ensemble CFS experiments were carried out for selected nine years comprising three ENSO warm, cold, and neutral years, the CFS skills in predicting SST, precipitation and T2m anomalies are compared. In addition, focusing on the 2011 and 2012 intense summer droughts in the central US, seasonal ensemble forecast experiments with early May initial conditions are also carried out for the two years. The differences in predicting precipitation and T2m anomalies with different parameterization treatments will be presented and reasons will be discussed.