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Muthuvel Chelliah

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Muthuvel Chelliah

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Muthuvel Chelliah and Phillip Arkin

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The objective of this study is to examine the broad aspects of large-scale interannual and long-term variability in the monthly mean outgoing longwave radiation (OLR) data over the global tropics. These data, derived from NOAA's polar-orbiting satellites, cover a period of more than 15 years. Rotated principal component analysis (RPCA) has been performed on monthly OLR anomalies over the global tropics (30°N–30°S) on a 10° longitude by 5° latitude grid for the period from June 1974 through March 1989, excluding calendar year 1978. The leading rotated principal components to be discussed below have been tested for robustness and reproducibility.

The spatial-loading pattern and the time series for the first principal component (termed the “canonical ENSO” mode) represent the major large-scale features in the tropics during the typical phase of the major warm and cold events in the tropical Pacific during the analysis period. The characteristics of the dramatic 1982/83 warm event that were different from the canonical ENSO mode completely dominate the second RPC (termed the 1982/83 mode). The third and fourth leading RPCs appear to describe the changes in the satellite-observing system. Specifically, the third RPC is clearly associated with the different equator crossing times of the various NOAA satellites, while the fourth eigenmode may be related to the three major changes in the spectral windows of the different NOAA satellites. Of the six leading modes considered, the “nonphysical” modes (3 and 4) accounted for more than 40% of the explained variance over North Africa and northeastern South America. The physical modes (1, 2, 5, and 6) explained more than 70% of the variance in the central equatorial and eastern Pacific Ocean.

It is demonstrated that while the eigenmodes that result from unrotated principal component analysis are sensitive to small changes in analysis domain and period, those of the rotated analysis are fairly stable. However, note that the “1982/83 mode,” as the name implies, is unique to the analysis period (1974–89). The results of the sensitivity analysis do not provide strong support of the claim by other authors that the decade of the 1980s, as compared to the 1970s, experienced enhanced levels of convective activity in the tropical Pacific and Indian oceans.

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Alan N. Basist and Muthuvel Chelliah

The Climate Prediction Center has used atmospheric temperatures for data analysis from the National Centers for Environmental Prediction (NCEP) model since 1979. Unfortunately, model changes have adversely affected the stability of the climatologic fields, introducing time-varying biases in the anomaly patterns of the Climate Diagnostic Data Base (CDDB). Fortunately, NCEP has addressed this issue by rerunning a state-of-the-art model using fixed assimilation, parameterization, and physics in order to derive a true climatology and anomalies. The authors compare the previous CDDB temperatures with those derived from the stable reanalysis. Results show major improvements for climate diagnostics and monitoring. Also compared are the reanalysis temperatures with brightness temperature Tb observed by the Microwave Sounding Units (MSU), flown aboard the National Oceanic and Atmospheric Administration (NOAA) series of polar-orbiting satellites (TIROS-N to NOAA-14). This MSU dataset has a precision of about 0.02°C globally, and it is available from December 1978. Therefore, the 17 levels of the reanalysis level temperature were weighted to simulate the MSU Tb in order to measure its precision over the 17-yr record. Global time series of the spatial correlations between full fields approach 1.0 throughout the entire record, whereas correlations for the anomaly fields can drop below 0.8 during the high sun season in the Northern Hemisphere. In 1994 the correlations drop below 0.65, which is the largest difference between the two datasets. An EOF on the global Tb differences from both datasets identified a relative drift beginning in 1991. The maximum loading was in the tropical Pacific, although it also extended over the tropical Indian Ocean and the Asian landmass. Results indicate that the reanalysis anomalies are getting progressively colder, relative to the MSU, during the early 1990s. The authors associate this drift with the changes in satellite retrievals and a reduction of Soviet Union data during its breakup. Additional sources of bias may be associated with aerosol contamination after the Mt. Pinotuba eruption and/or drift in the NOAA-11 sensor. Although there is a relative offset in the anomalies, the reanalysis temperatures have a better correspondence with the radiosonde network after 1990. Therefore it appears that the bias is associated with an improvement in the reanalysis input data during the last several years. Since changes in the datasets assimilated into the model can introduce a slight bias, new procedures should be developed to minimizes these effects in any future reanalysis. Finally, although the reanalysis has a slight drift in the later years, the comparison with the MSU spatial anomalies generally showed excellent results. The reanalysis represents a substantial improvement over the CDDB for monitoring climate variability.

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Gerald D. Bell and Muthuvel Chelliah

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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.

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Kingtse C. Mo and Muthuvel Chelliah

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A 32-km high-resolution modified Palmer drought severity index (MPDSI) based on the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (RR) from 1979 to 2004 is presented. The assumptions of Palmer, such as the water balance equation, the difference between observed precipitation and the climatologically expected precipitation over the maximum conditions, and the changes of the index as a function of the current index, are preserved. Many deficiencies of the original PDSI are eliminated by taking fields directly from the RR or by making better estimates. For example, fields such as potential evapotranspiration, evaporation, runoff, total soil moisture, and soil moisture change in a given month are obtained directly from the RR. The potential recharge is defined as the total soil moisture needed to reach the maximum total soil moisture at each grid point for each calendar month. The potential precipitation is defined as the maximum precipitation at each grid point for a given calendar month. The underground volumetric soil moisture includes both frozen and liquid form. Therefore, the contribution of snowmelt is taken into account inexplicitly. The questionable assumptions of two-layer soil model and the available soil moisture capacity are no longer needed. Overall, the MPDSI, when averaged over a large area and long time, often resembles the traditional PDSI based on the Palmer formula and the climate-division data. The MPDSI obeys Gaussian distribution, and so it can also be used to assess the potential for floods. Together with a consistent suite of soil moisture, surface energy, and atmospheric terms from the RR, the MPDSI can be used to monitor and diagnose drought and floods.

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Thomas M. Smith and Muthuvel Chelliah

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An analysis of the tropical Pacific Ocean from January 1983 to December 1992 is used to describe the annual cycle, with the main focus on subsurface temperature variations. Some analysis of ocean-current variations are also considered. Monthly mean fields are generated by assimilation of surface and subsurface temperature data into an ocean general circulation model. Data used in the analysis include satellite sea surface temperature observations and surface and subsurface temperature observations from ships and buoys. Comparisons with observations show that the analysis reasonably describes large-scale ocean thermal variations. Ocean currents are not assimilated and do not compare as well with observations. However, the ocean-current variations in the analysis are qualitatively similar to the known variations given by others. The authors use harmonic analysis to separate the mean annual cycle and estimate its contribution to total variance.

The analysis shows that in most regions the annual cycle of subsurface thermal variations is larger than surface variations and that these variations are associated with changes in the depth of the thermocline. The annual cycle accounts for most of the total surface variance poleward of about 10° latitude but accounts for much less surface and subsurface total variance near the equator. Large subsurface annual cycles occur near 10°N associated with shifts of the intertropical convergence zone and along the equator associated with the annual cycle of equatorial wind stress. The hemispherically asymmetric depths of the 20°C isotherms indicate that the large Southern Hemisphere warm pool, which extends to near the equator, may play an important role in thermal variations on the equator.

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Muthuvel Chelliah and C. F. Ropelewski

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Uncertainties in estimates of tropospheric mean temperature were investigated in the context of climate change detection through comparisons of the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) 40-yr reanalysis (1958–97), the National Aeronautics and Space Administration Data Assimilation Office (NASA/DAO) 14-yr reanalysis (1980–93), the European Centre for Medium-Range Weather Forecasts Reanalysis Project (ERA) 15-yr reanalysis (1979–94), and the satellite microwave sounding unit channel 2 (MSU Ch2) (1979–97) temperature data. The maximum overlap period for comparison among these datasets is the 14 full years January 1980 to December 1993. This study documents similar shifts in the relative bias between the MSU Ch2 and the ERA and the NCEP–NCAR reanalyses in the 1991–97 period suggesting changes in the satellite analysis. However, the intercomparisons were not able to rule out the changes in the reanalysis systems and/or the input data on which the reanalyses are based as prime factors for the changes in the relative bias between the MSU and ERA and NCEP–NCAR reanalyses.

These temporal changes in the relative bias among the reanalyses suggest their limitations for global change studies. Nonetheless, the analysis also shows that the pattern correlations (r) between the MSU Ch2 monthly mean fields and each of the reanalyses are very high, r > 0.96, and remain relatively high for the anomaly fields, r > 0.8, generally >0.9. This result suggests that reanalysis may be used for comparisons to numerical model–generated forecast fields (from GCM simulation runs) and in conjunction with “fingerprint” techniques to identify climate change.

In comparisons of the simple linear trends present in each dataset for the 1980–90 period, each of the reanalyses had spatial patterns similar to MSU Ch2 except that the NCEP–NCAR reanalysis showed smaller “positive” (warming) trends in comparison with the MSU while the ERA reanalysis showed larger positive trends. The NASA/DAO reanalysis showed a mixed pattern. Many regions of the globe are identified that showed consistent warming/cooling patterns among the major reanalyses and MSU, even though there were disagreements in the exact magnitude among the analyses. The spatial patterns of linear trends changed, however, with the addition of three years of data to extend the trend analysis to the 1980–93 period. This result suggests that such simple linear trend analyses are very sensitive to the temporal span in these relatively short datasets and thus are of limited usefulness in the context of climate change detection except, however, when the signal is large and shows consistency among all datasets.

The long record (1958–96) of seasonal mean 2-m temperature anomalies from NCEP–NCAR reanalysis is well correlated with gridded analyses of station-based observed surface temperature, with correlations between 0.65 and 0.85. It is argued that these correlations might suggest an upper limit to the magnitudes of the pattern correlations that might be obtained by correlating observed surface temperature analyses with those from multiyear GCM simulation runs made in the context of fingerprint climate change detection.

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Muthuvel Chelliah and Gerald D. Bell

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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.

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