H. M. van den Dool

The NCEP Climate Forecast System

Abstract The Climate Forecast System (CFS), the fully coupled ocean–land–atmosphere dynamical seasonal prediction system, which became operational at NCEP in August 2004, is described and evaluated in this paper. The CFS provides important advances in operational seasonal prediction on a number of fronts. For the first time in the history of U.S. operational seasonal prediction, a dynamical modeling system has demonstrated a level of skill in forecasting U.S. surface temperature and precipitation that is comparable to the skill of the statistical methods used by the NCEP Climate Prediction Center (CPC). This represents a significant improvement over the previous dynamical modeling system used at NCEP. Furthermore, the skill provided by the CFS spatially and temporally complements the skill provided by the statistical tools. The availability of a dynamical modeling tool with demonstrated skill should result in overall improvement in the operational seasonal forecasts produced by CPC. The atmospheric compon...

Analysis of Model-Calculated Soil Moisture over the United States (1931–1993) and Applications to Long-Range Temperature Forecasts

Abstract A long time series of monthly soil moisture data during the period of 1931–1993 over the entire U.S. continent has been created with a one-layer soil moisture model. The model is based on the water budget in the soil and uses monthly temperature and monthly precipitation as input. The data are for 344 U.S. climate divisions during the period of 1931–1993. The main goals of this paper are 1) to improve our understanding of soil moisture and its effects on the atmosphere and 2) to apply the calculated soil moisture toward long-range temperature forecasts. In this study, the model parameters are estimated using observed precipitation, temperature, and runoff in Oklahoma (1960–1989) and applied to the entire United States. The comparison with the 8-yr (1984–1991) observed soil moisture in Illinois indicates that the model gives a reasonable simulation of soil moisture with both climatology and interannual variability. The analyses of the calculated soil moisture show that the climatological soil mois...

Empirical orthogonal teleconnections

Abstract A new variant is proposed for calculating functions empirically and orthogonally from a given space–time dataset. The method is rooted in multiple linear regression and yields solutions that are orthogonal in one direction, either space or time. In normal setup, one searches for that point in space, the base point (predictor), which, by linear regression, explains the most of the variance at all other points (predictands) combined. The first spatial pattern is the regression coefficient between the base point and all other points, and the first time series is taken to be the time series of the raw data at the base point. The original dataset is next reduced; that is, what has been accounted for by the first mode is subtracted out. The procedure is repeated exactly as before for the second, third, etc., modes. These new functions are named empirical orthogonal teleconnections (EOTs). This is to emphasize the similarity of EOT to both teleconnections and (biorthogonal) empirical orthogonal function...

A New Look at Weather Forecasting through Analogues

Abstract In the literature, the use of analogues for short-range weather forecasting has practically been discarded. This is because no good matches for todays extratropical large-scale flow patterns can be found in a 30-year data library. We propose here a limited-area model approach for Analogue-Forecasting (AF). In order to make a 12-hour AF valid at a target point, we require analogy in initial states only over a circle with radius of about 900 km. On a limited area there are usually several good analogues, sometimes to within observational error. Different historical analogues may be used at different target points. The usefulness of the limited area approach is first demonstrated with some examples. We then present verification statistics of 3000 12-hour 500-mb height point forecasts in the Northern Hemisphere winter at 38°N, 80°W (over West Virginia, U.S.A.). In order to beat persistence at 12 hours at this point we need an analogue which differs by about 40 geopotential meters or less from the ba...

Long-Lead Seasonal Temperature Prediction Using Optimal Climate Normals

Abstract This study is intended to determine the spatially varying optimal time periods for calculating seasonal climate normals over the entire United States based on temperature data at 344 Unite...

Monthly Precipitation-Temperature Relations and Temperature Prediction over the United States

Abstract The monthly mean precipitation-air temperature (MMP-MMAT) relation over the United States has been examined by analyzing the observed MMP and MMAT during the period of 1931–87. The authors’ main purpose is to examine the possibility of using MMP as a second predictor in addition to the MMAT itself in predicting the next months MMAT and to shed light on the physical relationship between MMP and MMAT. Both station and climate division data are used. It was found that the lagged MMP-MMAT correlation with MMP leading by a month is generally negative, with the strongest negative correlation in summer and in the interior United States continent. Over large areas of the interior United States in summer, predictions of MMAT based on either antecedent MMP alone or on a combination of antecedent MMP and MMAT are better than a Prediction scheme based on MMAT alone. On the whole, even in the interior United States though, including MMP as a second predictor does not improve the skill of MMAT forecasts on ei...

On the Level and Origin of Seasonal Forecast Skill in Northern Europe

Abstract This study examines the level and origin of seasonal forecast skill of surface air temperature in northern Europe. The forecasts are based on an empirical methodology, canonical correlation analysis (CCA), which is a method designed to find correlated patterns between predictor and predictand fields. A modified form of CCA is used where a prefiltering step precedes the CCA as proposed by T. P. Barnett and R. Preisendorfer. The predictive potential of four fields is investigated, namely, (a) surface air temperature (i.e., the predictand field itself), (b) local sea surface temperature (SST) in the northern European area on a dense grid, (c) Northern Hemisphere 700-hPa geopotential height, and (d) quasi-global SST on a coarse grid. The design is such that four contiguous predictor periods (of 3 months each) are followed by a lead time and then a single predictand period (3 months long). The shortest lead time is 1 month and the longest is 15 months. The skill of the CCA- based forecasts is estimate...

Frequency Dependence in Forecast Skill

Abstract A method is proposed to calculate measures of forecast skill for high, medium and low temporal frequency variations in the atmosphere. This method is applied to a series of 128 consecutive 1 to 10-day forecasts produced at NMC with their operational global medium-range-forecast model during 1 May–5 September 1988. It is found that over this period, more than 50% of the variance in observed 500 mb height fields is found at periods of 18 days or longer. The. intuitive notion that the predictability time of a phenomenon should be proportional to its lifetime is found to be qualitatively correct; i.e., the low frequencies are predicted (at a given skill level) over a longer time than high frequencies. However, the current prediction skill in low frequencies is far below its potential if one assumes that for any frequency the predictability time scale ought to be equal to the lifetime scale. In the high frequencies, however, the current prediction skill has already reached its potential; i.e., cyclone...

On the weights for an ensemble-averaged 6-10-day forecast

Abstract A scheme to optimally weight the members of an ensemble of forecasts is discussed in the framework of calculating an as accurate as possible ensemble average. Results show, relative to a single member, a considerably improved 500-mb height forecast in the 6–10-day range for the Northern Hemisphere. The improvement is nontrivial and cannot be explained from simple smoothing. This method is used in operations at the National Meteorological Center.

1948–98 U.S. Hydrological Reanalysis by the Noah Land Data Assimilation System

Abstract Land surface variables, such as soil moisture, are among the most important components of memory for the climate system. A more accurate and long time series of land surface data is very important for real-time drought monitoring, for understanding land surface–atmosphere interaction, and for improving weather and climate prediction. Thus, the ultimate goal of the present work is to produce a long-term “land reanalysis” with 1) retrospective and 2) real-time update components that are both generated in a manner that remains temporally homogeneous throughout the record. As the first step of the above goal, the retrospective component is reported here. Specifically, a 51-yr (1948–98) set of hourly land surface meteorological forcing is produced and used to execute the Noah land surface model, all on the 1/8° grid of the North American Land Data Assimilation System (NLDAS). The surface forcing includes air temperature, air humidity, surface pressure, wind speed, and surface downward shortwave and lo...