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John R. Lanzante

Abstract

A long historical record (∼100 years) of monthly sea surface temperature anomalies from the Comprehensive Ocean–Atmosphere Data Set was used to examined the lag relationships between different locations in the global Tropics. Application of complex principal component (CPC) analysis revealed that the leading mode captures ENSO-related quasi-cyclical warming and cooling in the tropical Pacific Ocean. The dominant features of this mode indicate that SST anomalies in the eastern Pacific lead those of the central Pacific. However, a somewhat weaker aspect of this mode also indicates that SST anomalies in the tropical Indian and western tropical North Atlantic Oceans vary roughly in concert with each other but lag behind those in the central and eastern Pacific. The stability of these lag relationships is indicated by the fact that the leading mode is quite similar in three different 30-year time periods.

In order to further examine these relationships some simple indexes were formed as the average over several grid points in each of the four key areas suggested by the CPC analyses. Several different types of analyses including lag correlation, checking the correspondence between extrema, and visual examination of time series plots were used to confirm the relationships implied by the CPC spatial patterns. By aggregating the lag correlations over the three 30-year time periods and performing a Monte Carlo simulation the relationships were found to be statistically significant at the 1% level. Reasonable agreement in the pattern of lag correlations was found using a different SST dataset.

Without aggregation of the lag correlations (i.e., considering each 30-year period separately) the area in the Pacific and Indian were consistently well related, but those involving the North Atlantic were more variable. The weaker correlations involving the Atlantic Ocean underscore the more tenuous nature of this remote relationship. While major ENSO-related swings in tropical Pacific SST are often followed by like variations in a portion of the Atlantic, there are times when there is either no obvious association or one of opposite sign. It may be that while ENSO variability tends to have an impact in the Atlantic, more localized factors can override this tendency. This may explain some of the contradictory statements found in the literature regarding such remote associations.

In comparing the findings of this project with some studies that utilize very recent data (since about 1982) some discrepancies were noted. In particular, some studies have reported evidence of 1) an inverse relationship between SST anomalies in the tropical Pacific and those in the eastern tropical South Atlantic and 2) the appearance of ENSO-related SST anomalies in the central tropical Pacific prior to those in the eastern tropical Pacific. From a historical perspective both of these characteristics are unusual. Thus, the recent time period may merit special attention. However, it is important to stress that caution should be exercised in generalizing findings based only on this recent time period.

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Melissa Free and John Lanzante

Abstract

Both observed and modeled upper-air temperature profiles show the tropospheric cooling and tropical stratospheric warming effects from the three major volcanic eruptions since 1960. Detailed comparisons of vertical profiles of Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC) and Hadley Centre Atmospheric Temperatures, version 2 (HadAT2), radiosonde temperatures with output from six coupled GCMs show good overall agreement on the responses to the 1991 Mount Pinatubo and 1982 El Chichón eruptions in the troposphere and stratosphere, with a tendency of the models to underestimate the upper-tropospheric cooling and overestimate the stratospheric warming relative to observations. The cooling effect at the surface in the tropics is amplified with altitude in the troposphere in both observations and models, but this amplification is greater for the observations than for the models. Models and observations show a large disagreement around 100 mb for Mount Pinatubo in the tropics, where observations show essentially no change, while models show significant warming of ∼0.7 to ∼2.6 K. This difference occurs even in models that accurately simulate stratospheric warming at 50 mb. Overall, the Parallel Climate Model is an outlier in that it simulates more volcanic-induced stratospheric warming than both the other models and the observations in most cases.

From 1979 to 1999 in the tropics, RATPAC shows a trend of less than 0.1 K decade−1 at and above 300 mb before volcanic effects are removed, while the mean of the models used here has a trend of more than 0.3 K decade−1, giving a difference of ∼0.2 K decade−1. At 300 mb, from 0.02 to 0.10 K decade−1 of this difference may be due to the influence of volcanic eruptions, with the smaller estimate appearing more likely than the larger. No more than ∼0.03 K of the ∼0.1-K difference in trends between the surface and troposphere at 700 mb or below in the radiosonde data appears to be due to volcanic effects.

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John R. Lanzante

Abstract

Climate studies often involve comparisons between estimates of some parameter derived from different observed and/or model-generated datasets. It is common practice to present estimates of two or more statistical quantities with error bars about each representing a confidence interval. If the error bars do not overlap, it is presumed that there is a statistically significant difference between them. In general, such a procedure is not valid and usually results in declaring statistical significance too infrequently. Simple examples that demonstrate the nature of this pitfall, along with some formulations, are presented. It is recommended that practitioners use standard hypothesis testing techniques that have been derived from statistical theory rather than the ad hoc approach involving error bars.

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John R. Lanzante

Abstract

Measurements from radiosonde temperatures have been used in studies that seek to identify the human influence on climate. However, such measurements are known to be contaminated by artificial inhomogeneities introduced by changes in instruments and recording practices that have occurred over time. Some simple diagnostics are used to compare vertical profiles of temperature trends from the observed data with simulations from a GCM driven by several different sets of forcings. Unlike most earlier studies of this type, both raw (i.e., fully contaminated) as well as adjusted observations (i.e., treated to remove some of the contamination) are utilized. The comparisons demonstrate that the effect of observational data adjustment can be as important as the inclusion of some major climate forcings in the model simulations. The effects of major volcanic eruptions critically influence temperature trends, even over a time period nearly four decades in length.

In addition, it is seen that the adjusted data show consistently better agreement than the unadjusted data, with simulations from a climate model for 1959–97. Particularly noteworthy is the fact that the adjustments supply missing warming in the tropical upper troposphere that has been attributed to model error in a number of earlier studies.

Finally, an evaluation of the fidelity of the model’s temperature response to major volcanic eruptions is conducted. Although the major conclusions of this study are unaffected by shortcomings of the simulations, they highlight the fact that even using a fairly long period of record (∼40 yr), any such shortcomings can have an important impact on trends and trend comparisons.

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John R. Lanzante and Melissa Free

Abstract

In comparisons of radiosonde vertical temperature trend profiles with comparable profiles derived from selected Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) general circulation models (GCMs) driven by major external forcings of the latter part of the twentieth century, model trends exhibit a positive bias relative to radiosonde trends in the majority of cases for both time periods examined (1960–99 and 1979–99). Homogeneity adjustments made in the Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC) and Hadley Centre Atmospheric Temperatures, version 2 (HadAT2), radiosonde datasets, which are applied by dataset developers to account for time-varying biases introduced by historical changes in instruments and measurement practices, reduce the relative bias in most cases. Although some differences were found between the two observed datasets, in general the observed trend profiles were more similar to one another than either was to the GCM profiles.

In the troposphere, adjustment has a greater impact on improving agreement of the shapes of the trend profiles than on improving agreement of the layer mean trends, whereas in the stratosphere the opposite is true. Agreement between the shapes of GCM and radiosonde trend profiles is generally better in the stratosphere than the troposphere, with more complexity to the profiles in the latter than the former. In the troposphere the tropics exhibit the poorest agreement between GCM and radiosonde trend profiles, but also the largest improvement in agreement resulting from homogeneity adjustment.

In the stratosphere, radiosonde trends indicate more cooling than GCMs. For the 1979–99 period, a disproportionate amount of this discrepancy arises several months after the eruption of Mount Pinatubo, at which time temperatures in the radiosonde time series cool abruptly by ∼0.5 K compared to those derived from GCMs, and this difference persists to the end of the record.

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John R. Lanzante and Gregory E. Gahrs

Abstract

A temporal sampling bias may be introduced due to the inability of a measurement system to produce a valid observation during certain types of situations. In this study the temporal sampling bias in satellite-derived measures of upper-tropospheric humidity (UTH) was examined through the utilization of similar humidity measures derived from radiosonde data. This bias was estimated by imparting the temporal sampling characteristics of the satellite system onto the radiosonde observations. This approach was applied to UTH derived from Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder radiances from the NOAA-10 satellite from the period 1987–91 and from the “Angell” network of 63 radiosonde stations for the same time period. Radiative modeling was used to convert both the satellite and radiosonde data to commensurate measures of UTH.

Examination of the satellite temporal sampling bias focused on the effects of the “clear-sky bias” due to the inability of the satellite system to produce measurements when extensive cloud cover is present. This study indicates that the effects of any such bias are relatively small in the extratropics (about several percent relative humidity) but may be ∼5%–10% in the most convectively active regions in the Tropics. Furthermore, there is a systematic movement and evolution of the bias pattern following the seasonal migration of convection, which reflects the fact that the bias increases as cloud cover increases. The bias is less noticeable for shorter timescales (seasonal values) but becomes more obvious as the averaging time increases (climatological values); it may be that small-scale noise partially obscures the bias for shorter time averages. Based on indirect inference it is speculated that the bias may lead to an underestimate of the magnitude of trends in satellite UTH in the Tropics, particularly in the drier regions.

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Brian J. Soden and John R. Lanzante

Abstract

This study compares radiosonde and satellite climatologies of upper-tropospheric water vapor for the period 1979–1991. Comparison of the two climatologies reveals significant differences in the regional distribution of upper-tropospheric relative humidity. These discrepancies exhibit a distinct geopolitical dependence that is demonstrated to result from international differences in radiosonde instrumentation. Specifically, radiosondes equipped with goldbeater's skin humidity sensors (found primarily in the former Soviet Union, China, and eastern Europe) report a systematically moister upper troposphere relative to the satellite observations, whereas radiosondes equipped with capacitive or carbon hygristor sensors (found at most other locations) report a systematically drier upper troposphere. The bias between humidity sensors is roughly 15%–20% in terms of the relative humidity, being slightly greater during summer than during winter and greater in the upper troposphere than in the midtroposphere. However, once the instrumentation bias is accounted for, regional variations of satellite and radiosonde upper-tropospheric relative humidity are shown to be in good agreement. Additionally, temporal variations in radiosonde upper-tropospheric humidity agree reasonably well with the satellite observations and exhibit much less dependence upon instrumentation.

The impact that the limited spatial coverage of the radiosonde network has upon the moisture climatology is also examined and found to introduce systematic errors of 10%–20% relative humidity over data-sparse regions of the Tropics. It is further suggested that the present radiosonde network lacks sufficient coverage in the eastern tropical Pacific to adequately capture ENSO-related variations in upper-tropospheric moisture. Finally, we investigate the impact of the clear-sky sampling restriction upon the satellite moisture climatology. Comparison of clear-sky and total-sky radiosonde observations suggests the clear-sky sampling limitation introduces a modest dry bias (<10% relative humidity) in the satellite climatology.

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John R. Lanzante, Stephen A. Klein, and Dian J. Seidel

Abstract

Trends in radiosonde-based temperatures and lower-tropospheric lapse rates are presented for the time periods 1959–97 and 1979–97, including their vertical, horizontal, and seasonal variations. A novel aspect is that estimates are made globally of the effects of artificial (instrumental or procedural) changes on the derived trends using data homogenization procedures introduced in a companion paper (Part I). Credibility of the data homogenization scheme is established by comparison with independent satellite temperature measurements derived from the microwave sounding unit (MSU) instruments for 1979–97. The various analyses are performed using monthly mean temperatures from a near–globally distributed network of 87 radiosonde stations.

The severity of instrument-related problems, which varies markedly by geographic region, was found, in general, to increase from the lower troposphere to the lower stratosphere, although surface data were found to be as problematic as data from the stratosphere. Except for the surface, there is a tendency for changes in instruments to artificially lower temperature readings with time, so that adjusting the data to account for this results in increased tropospheric warming and decreased stratospheric cooling. Furthermore, the adjustments tend to enhance warming in the upper troposphere more than in the lower troposphere; such sensitivity may have implications for “fingerprint” assessments of climate change. However, the most sensitive part of the vertical profile with regard to its shape was near the surface, particularly at regional scales. In particular, the lower-tropospheric lapse rate was found to be especially sensitive to adjustment as well as spatial sampling. In the lower stratosphere, instrument-related biases were found to artificially inflate latitudinal differences, leading to statistically significantly more cooling in the Tropics than elsewhere. After adjustment there were no significant differences between the latitude zones.

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Mike Bauer, Anthony D. Del Genio, and John R. Lanzante

Abstract

Recent studies have demonstrated that the correlation between interannual variations of large-scale average temperature and water vapor is stronger and less height dependent in one GCM than in an objective analysis of radiosonde observations. To address this discrepancy, a GCM with a different approach to cumulus parameterization is used to explore the model dependence of this result, the effect of sampling biases, and the analysis scheme applied to the data.

It is found that the globally complete data from the two GCMs produce similar patterns of correlation despite their fundamentally different moist convection schemes. While this result concurs with earlier studies, it is also shown that this apparent model–observation discrepancy is significantly reduced (although not eliminated) by sampling the GCM in a manner more consistent with the observations, and especially if the objective analysis is not then applied to the sampled data. Furthermore, it is found that spatial averages of the local temperature–humidity correlations are much weaker, and show more height dependence, than correlations of the spatially averaged quantities for both model and observed data. The results of the previous studies are thus inconclusive and cannot therefore be interpreted to mean that GCMs greatly overestimate the water vapor feedback.

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John R. Lanzante, Stephen A. Klein, and Dian J. Seidel

Abstract

Historical changes in instrumentation and recording practices have severely compromised the temporal homogeneity of radiosonde data, a crucial issue for the determination of long-term trends. Methods developed to deal with these homogeneity problems have been applied to a near–globally distributed network of 87 stations using monthly temperature data at mandatory pressure levels, covering the period 1948–97. The homogenization process begins with the identification of artificial discontinuities through visual examination of graphical and textual materials, including temperature time series, transformations of the temperature data, and independent indicators of climate variability, as well as ancillary information such as station history metadata. To ameliorate each problem encountered, a modification was applied in the form of data adjustment or data deletion. A companion paper (Part II) reports on various analyses, particularly trend related, based on the modified data resulting from the method presented here.

Application of the procedures to the 87-station network revealed a number of systematic problems. The effects of the 1957 global 3-h shift of standard observation times (from 0300/1500 to 0000/1200 UTC) are seen at many stations, especially near the surface and in the stratosphere. Temperatures from Australian and former Soviet stations have been plagued by numerous serious problems throughout their history. Some stations, especially Soviet ones up until ∼1970, show a tendency for episodic drops in temperature that produce spurious downward trends. Stations from Africa and neighboring regions are found to be the most problematic; in some cases even the character of the interannual variability is unreliable. It is also found that temporal variations in observation time can lead to inhomogeneities as serious as the worst instrument-related problems.

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