Suranjana Saha

The NCEP/NCAR 40-Year Reanalysis Project

The NCEP and NCAR are cooperating in a project (denoted “reanalysis”) to produce a 40-year record of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involves the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data; quality controlling and assimilating these data with a data assimilation system that is kept unchanged over the reanalysis period 1957–96. This eliminates perceived climate jumps associated with changes in the data assimilation system. The NCEP/NCAR 40-yr reanalysis uses a frozen state-of-the-art global data assimilation system and a database as complete as possible. The data assimilation and the model used are identical to the global system implemented operationally at the NCEP on 11 January 1995, except that the horizontal resolution is T62 (about 210 km). The database has been enhanced with many sources of observations not available in real time for operations, provided by differe...

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...

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...

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...

A temporal interpolation method to obtain hourly atmospheric surface pressure tides in Reanalysis 1979–1995

The diurnal cycle in climatology as revealed in National Centers for Environmental Predictions Reanalysis 1979–1995 has been studied for global gridded data at 0000, 0600, 1200 and 1800 UT. Climatologies have been prepared for each of the four time levels separately. There are substantial differences in, for instance, the 00002md 0600 UT climatologies, owing to a diurnal cycle and/or what is referred to commonly as atmospheric tides. The semidiurnal tide is quite strong in the mass fields, but with sampling every 6 hours at the Nyquist frequency, some aspects cannot be studied properly. However, a method of interpolation based on spatial harmonic waves moving at an empirically determined speed can be called upon to make an educated guess about the atmospheric tides at any times in between. This interpolation technique is similar to the one published by Van den Dool and Qin [1996], but the wave speeds are not like the slow Rossby modes but roughly 15° westward per hour. We present the global tides in surface pressure thus obtained for every hour of the day for January.

Systematic Tendency Error in Budget Calculations

Abstract Atmospheric budget calculations suffer from various observational and numerical errors. This paper demonstrates that all budget calculations applied to a large number of samples suffer from additional errors originating from systematic tendency errors of the budget equation used. Quantitative evaluation of this systematic tendency error for various types of budget computations showed that the systematic tendency errors are generally comparable in magnitude to the leading terms in the budget equations. Because of this error, the calculated budget does not satisfy conservation properties under steady conditions.