Contribution to the 4th USWRP Science Symposium

The NCEP Environmental Modeling Center Activities

for Developing Improved Quantitative Precipitation Forecasts

Stephen J. Lord1

Geoff DiMego1

Brad Ferrier2

Ying Lin1

Kenneth Mitchell1

M. Steven Tracton1

Zoltan Toth2

Yuejian Zhu2

1 - NCEP Environmental Modeling Center

2 - SAIC/GSC at the NCEP Environmental Modeling Center

The National Centers for Environmental Prediction, Environmental Modeling Center (EMC) is heavily involved in developing improved numerical forecast systems for Quantitative Precipitation Forecasts (QPFs). Recent developments have concentrated in three major areas: ensemble forecasting, data assimilation and upgrades to model physics. Work in these areas is described below.

EMC has developed, and is now running routinely in real time, a Short Range Ensemble Forecast (SREF) system. The current system is currently composed of 10 members composed of five

members from both the Eta and Regional Spectral Model (RSM) with 48 km horizontal resolution. Initial state perturbations are provided by "breeding", as for the NCEP global ensemble system, but in the context of the respective regional models. Perturbations to physics, as well as initial conditions, and inclusion of additional models are anticipated. Future SREF system and derived product upgrades will be discussed, with emphasis on how these advances relate to the skill and utility of the ensemble based probabilities in forecasting significant weather events, such as winter storms and associated sensible weather and warm season mesoscale convective systems.

Calibrated, ensemble based, probabilistic QPFs (PQPFs) are now produced from NCEP's operational global ensemble system. The PQPF forecasts are based on the relative frequency of ensemble members indicating a particular event. Since neither the numerical weather prediction model nor the ensemble generation technique is perfect, these probability values are not necessarily reliable. A calibration algorithm has been developed to reduce the bias in the first moment of the ensemble based probability distribution. The calibration technique compares the frequency distributions of observed and forecast precipitation amounts over the continental US over the preceding 2-3 month period. Verification results indicate that the reliability and skill of the calibrated forecasts is significantly enhanced. Further improvement is expected from an additional adjustment of the second moment of precipitation amounts. It is expected that the PQPF calibration procedure will be implemented operationally and will provide reliable and more skillful PQPF forecasts to the hydrologic and other user communities. This calibration technique can also be applied to the SREF system.

Assimilation of an operational, multi-sensor (radar+gauges) hourly precipitation analysis was implemented into the NCEP Eta Data Assimilation System (EDAS) on 24 Jul 2001. The model forecast precipitation is compared to precipitation analysis at each time step during the 12-hour pre-forecast data assimilation period, and adjustments are made to the model's temperature, moisture and hydrometeor fields to make them more consistent with the observed precipitation. The precipitation assimilation improved the model's soil moisture field and contributed to a marked improvement in the model's 24 h precipitation forecast skills.

On 27 Nov 2001 a second EDAS upgrade included an increase in resolution from 22km to 12km and a complete upgrade to the cloud and precipitation microphysics scheme, called the EGCP01 (Eta grid-scale cloud and precipitation scheme of 2001) . The precipitation assimilation scheme also underwent an overhaul to be consistent with the new cloud microphysics. EGCP01 predicts various types of condensate in the form of cloud water, small ice crystals, rain, and precipitating ice. Precipitating ice is in the form of snow, graupel, or sleet depending on the bulk density of the ice, which is explicitly calculated. Precipitation sedimentation is parameterized using a top-down integration of precipitation fluxes, but with the novel extension of partitioning the downward fluxes between local storage in the grid box and fall out through the bottom of the box. A single prognostic variable, total condensate, is advected in the model, where its decomposition into individual species is maintained by local storage arrays. The formulations of the microphysical processes are more sophisticated than in the previously operational scheme (Zhao et al., 1997), particularly with respect to freezing and melting. Extensive lookup tables are used to represent the results of computationally expensive and complex calculations so that the scheme is computationally efficient for use in a wide range of NWP models.

Parallel tests show improvements in the Eta quantitative precipitation forecasts (QPF) using the EGCP01 through higher equitable threat scores and reduced bias when compared with an extensive precipitation verification network of gauges. Field forecasters for the first time reported seeing the Eta correctly forecast precipitation on the lee slopes of mountain ranges and there is improved QPF associated with lake-effect snows. There are specific, tunable parameters in the EGCP01 that are strongly dependent on grid resolution, most notably the threshold cloud water mixing ratio for autoconversion (self collection) to rain, as well as the grid-averaged relative humidity for the onset of condensation. It is hypothesized that these thresholds will vary for many different reasons. Based on casual inspection and evaluation of retrospective forecasts and comments from forecasters, we speculate that the presence or absence of convective instability in the grid box may be one of the biggest factors. A major challenge to field programs is to develop strategies to transform observations taken in very local conditions (e.g., along a flight line for microphysics measurements) to volume integrated quantities as represented in models. From a NWP perspective, translating results from field programs into improved QPF will require analyzing the observations consistent with the rudimentary aspects of numerical models.

QPF skill over the CONUS in the warm season is strongly dependent on the mesoscale model's ability to simulate and predict the evolution of convective instability regimes, and temperature and water vapor structure in the lower half of the troposphere. The latter in turn is heavily dependent of the model's ability to capture the structure and diurnal cycle of the planetary boundary layer. However, the growing sophistication and vertical resolution of PBL schemes in modern mesoscale models has been outstripping such models' ability to properly model the underlying land-surface sensible and latent heat fluxes that force the PBL evolution. Since the mid-1990's, NCEP/EMC has focused efforts on improving these land-surface heat fluxes in first the mesoscale Eta model (and global MRF model), and now also the WRF model, by upgrading the physics and initialization of the land-surface processes in these models. These land-surface initiatives have been accomplished via advancements in the NCEP "NOAH" land surface model (NOAH LSM) and its companion NOAH-based land data assimilation systems (LDAS). The LDAS capabilities at NCEP include both coupled (Eta/NOAH EDAS) and uncoupled (–LDAS) approaches. We will describe and present examples of both 1) the NOAH LSM physics advancements (especially warm-season related) and 2) LDAS initialization approaches (e.g. for soil moisture), plus show the impacts of these on Eta model predictions of a) surface heat fluxes, b) PBL development, and c) QPF. Lastly, we will describe the collaboration between NCEP, NCAR, and AFWA, via the WRF Land-surface Working Group, to support a community version (to be renamed) of the NOAH LSM for the WRF model, as well as for the Eta and MM5 models.