Search Results

You are looking at 1 - 7 of 7 items for :

  • Author or Editor: Gerald D. Bell x
  • Journal of Climate x
  • Refine by Access: All Content x
Clear All Modify Search
Muthuvel Chelliah
and
Gerald D. Bell

Abstract

The leading tropical multidecadal mode (TMM) and tropical interannual (ENSO) mode in the 52-yr (1949– 2000) NCEP–NCAR reanalysis are examined for the December–February (DJF) and June–August (JJA) seasons based on seasonal tropical convective rainfall variability and tropical surface (land + ocean) temperature variability. These combined modes are shown to capture 70%–80% of the unfiltered variance in seasonal 200-hPa velocity potential anomalies in the analysis region of 30°N–30°S. The TMM is the dominant mode overall, accounting for 50%–60% of the total unfiltered variance in both seasons, compared to the 22%–24% for ENSO.

The robustness of the tropical multidecadal mode is addressed, and the results are shown to compare favorably with observed station data and published results of decadal climate variability in the key loading regions. The temporal and spatial characteristics of this mode are found to be distinct from ENSO.

The TMM captures the global climate regimes observed during the 1950s–60s and 1980s–90s, and the 1970s transition between these regimes. It provides a global-scale perspective for many known aspects of this decadal climate variability (i.e., surface temperature, precipitation, and atmospheric circulation) and links them to coherent multidecadal variations in tropical convection and surface temperatures in four core regions: the West African monsoon region, the central tropical Pacific, the Amazon basin, and the tropical Indian Ocean.

During JJA, two distinguishing features of the tropical multidecadal mode are its link to West African monsoon variability and the pronounced zonal wavenumber-1 structure of the 200-hPa streamfunction anomalies in the subtropics of both hemispheres. During DJF a distinguishing feature is its link between anomalous tropical convection and multidecadal variations in the North Atlantic Oscillation (NAO). For the linear combination of the TMM and ENSO the strongest regressed values of the wintertime NAO index are found when their principal component (PC) time series are out of phase.

In the Tropics and subtropics the linearly combined signal for the TMM and ENSO is strongest when their PC time series are in phase and is weakest when they are out of phase. This result suggests a substantial modulation of the ENSO teleconnections by the background flow. It indicates stronger La Niña teleconnections during the 1950s–60s, compared to stronger El Niño teleconnections during the 1980s–90s. Although this study addresses the linear ENSO–TMM interference, the results also suggest that interactions between the two modes may help to explain the stronger El Niño episodes observed during the 1980s–90s compared to the 1950s–60s.

Full access
Gerald D. Bell
and
Muthuvel Chelliah

Abstract

Interannual and multidecadal extremes in Atlantic hurricane activity are shown to result from a coherent and interrelated set of atmospheric and oceanic conditions associated with three leading modes of climate variability in the Tropics. All three modes are related to fluctuations in tropical convection, with two representing the leading multidecadal modes of convective rainfall variability, and one representing the leading interannual mode (ENSO).

The tropical multidecadal modes are shown to link known fluctuations in Atlantic hurricane activity, West African monsoon rainfall, and Atlantic sea surface temperatures, to the Tropics-wide climate variability. These modes also capture an east–west seesaw in anomalous convection between the West African monsoon region and the Amazon basin, which helps to account for the interhemispheric symmetry of the 200-hPa streamfunction anomalies across the Atlantic Ocean and Africa, the 200-hPa divergent wind anomalies, and both the structure and spatial scale of the low-level tropical wind anomalies, associated with multidecadal extremes in Atlantic hurricane activity.

While there are many similarities between the 1950–69 and 1995–2004 periods of above-normal Atlantic hurricane activity, important differences in the tropical climate are also identified, which indicates that the above-normal activity since 1995 does not reflect an exact return to conditions seen during the 1950s–60s. In particular, the period 1950–69 shows a strong link to the leading tropical multidecadal mode (TMM), whereas the 1995–2002 period is associated with a sharp increase in amplitude of the second leading tropical multidecadal mode (TMM2). These differences include a very strong West African monsoon circulation and near-average sea surface temperatures across the central tropical Atlantic during 1950–69, compared with a modestly enhanced West African monsoon and exceptionally warm Atlantic sea surface temperatures during 1995–2004.

It is shown that the ENSO teleconnections and impacts on Atlantic hurricane activity can be substantially masked or accentuated by the leading multidecadal modes. This leads to the important result that these modes provide a substantially more complete view of the climate control over Atlantic hurricane activity during individual seasons than is afforded by ENSO alone. This result applies to understanding differences in the “apparent” ENSO teleconnections not only between the above- and below-normal hurricane decades, but also between the two sets of above-normal hurricane decades.

Full access
Michael S. Halpert
and
Gerald D. Bell

Abstract

No Abstract Available

Full access
Michael S. Halpert
and
Gerald D. Bell

Abstract

No Abstract Available

Full access
Gerald D. Bell
and
Alan N. Basist

Abstract

Abstract not available

Full access
Alan Basist
,
Gerald D. Bell
, and
Vernon Meentemeyer

Abstract

Statistical relationships between topography and the spatial distribution of mean annual precipitation are developed for ten distinct mountainous regions. These relationships are derived through linear bivariate and multivariate analyses, using six topographic variables as predictors of precipitation. These predictors are elevation, slope, orientation, exposure, the product (or interaction) of slope and orientation, and the product of elevation and exposure.

The two interactive terms are the best overall bivariate predictors of mean annual precipitation, whereas orientation and exposure are the strongest noninteractive bivariate predictors. The regression equations in many of the climatically similar regions tend to have similar slope coefficients and similar y-intercept values, indicating that local climatic conditions strongly influence the relationship between topography and the spatial distribution of precipitation. In contrast, the regression equations for the tropical and extratropical regions exhibit distinctly different slope coefficients and y-intercept values, indicating that topography influences the spatial distribution of precipitation differently in convective versus nonconvective environments.

The multivariate equations contain between one and three significant topographic predictors. The best overall predictors in these models are exposure and the interaction of elevation and exposure, indicating that exposure to the prevailing wind is perhaps the single most important feature relating topography to the spatial distribution of precipitation in the mountainous regimes studied. The strongest (weakest) multivariate relationships between topography and precipitation are found in the four middle- and high-latitude west coast regions (in the tropical regions), where more than 70% (less than 50%) of the spatial variability of mean annual precipitation is explained. These results suggest that in certain regions, one can estimate the spatial distribution of mean annual precipitation from a limited network of raingauges using topographically based regression equations.

Full access
Hui Wang
,
Jae-Kyung E. Schemm
,
Arun Kumar
,
Wanqiu Wang
,
Lindsey Long
,
Muthuvel Chelliah
,
Gerald D. Bell
, and
Peitao Peng

Abstract

A hybrid dynamical–statistical model is developed for predicting Atlantic seasonal hurricane activity. The model is built upon the empirical relationship between the observed interannual variability of hurricanes and the variability of sea surface temperatures (SSTs) and vertical wind shear in 26-yr (1981–2006) hindcasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS).

The number of Atlantic hurricanes exhibits large year-to-year fluctuations and an upward trend over the 26 yr. The latter is characterized by an inactive period prior to 1995 and an active period afterward. The interannual variability of the Atlantic hurricanes significantly correlates with the CFS hindcasts for August–October (ASO) SSTs and vertical wind shear in the tropical Pacific and tropical North Atlantic where CFS also displays skillful forecasts for the two variables. In contrast, the hurricane trend shows less of a correlation to the CFS-predicted SSTs and vertical wind shear in the two tropical regions. Instead, it strongly correlates with observed preseason SSTs in the far North Atlantic. Based on these results, three potential predictors for the interannual variation of seasonal hurricane activity are constructed by averaging SSTs over the tropical Pacific (TPCF; 5°S–5°N, 170°E–130°W) and the Atlantic hurricane main development region (MDR; 10°–20°N, 20°–80°W), respectively, and vertical wind shear over the MDR, all of which are from the CFS dynamical forecasts for the ASO season. In addition, two methodologies are proposed to better represent the long-term trend in the number of hurricanes. One is the use of observed preseason SSTs in the North Atlantic (NATL; 55°–65°N, 30°–60°W) as a predictor for the hurricane trend, and the other is the use of a step function that breaks up the hurricane climatology into a generally inactive period (1981–94) and a very active period (1995–2006). The combination of the three predictors for the interannual variation, along with the two methodologies for the trend, is explored in developing an empirical forecast system for Atlantic hurricanes.

A cross validation of the hindcasts for the 1981–2006 hurricane seasons suggests that the seasonal hurricane forecast with the TPCF SST as the only CFS predictor is more skillful in inactive hurricane seasons, while the forecast with only the MDR SST is more skillful in active seasons. The forecast using both predictors gives better results. The most skillful forecast uses the MDR vertical wind shear as the only CFS predictor. A comparison with forecasts made by other statistical models over the 2002–07 seasons indicates that this hybrid dynamical–statistical forecast model is competitive with the current statistical forecast models.

Full access