Utility of Radiosonde Wind Data in Representing Climatological Variations of Tropospheric Temperature and Baroclinicity in the Western Tropical Pacific

Allen, Robert J.; Sherwood, Steven C.

doi:10.1175/2007jcli1526.1

Cited by 17 publications

(14 citation statements)

References 36 publications

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“…We should also consider additional independent evidence (either physical or statistical) that might be placed on the estimation of break points. One example may be the thermal wind relation (Allen and Sherwood 2007).…”

Section: Discussionmentioning

confidence: 99%

Assessing Bias and Uncertainty in the HadAT-Adjusted Radiosonde Climate Record

et al. 2008

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Uncertainties in observed records of atmospheric temperature aloft remain poorly quantified. This has resulted in considerable controversy regarding signals of climate change over recent decades from temperature records of radiosondes and satellites. This work revisits the problems associated with the removal of inhomogeneities from the historical radiosonde temperature records, and provides a method for quantifying uncertainty in an adjusted radiosonde climate record due to the subjective choices made during the data homogenization.This paper presents an automated homogenization method designed to replicate the decisions made by manual judgment in the generation of an earlier radiosonde dataset [i.e., the Hadley Centre radiosonde temperature dataset (HadAT)]. A number of validation experiments have been conducted to test the system performance and impact on linear trends.Using climate model data to simulate biased radiosonde data, the authors show that limitations in the homogenization method are sufficiently large to explain much of the tropical trend discrepancy between HadAT and estimates from satellite platforms and climate models. This situation arises from the combination of systematic (unknown magnitude) and random uncertainties (of order 0.05 K decade Ϫ1 ) in the radiosonde data. Previous assessment of trends and uncertainty in HadAT is likely to have underestimated the systematic bias in tropical mean temperature trends. This objective assessment of radiosonde homogenization supports the conclusions of the synthesis report of the U.S. Climate Change Science Program (CCSP), and associated research, regarding potential bias in tropospheric temperature records from radiosondes.

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Section: Discussionmentioning

confidence: 99%

Assessing Bias and Uncertainty in the HadAT-Adjusted Radiosonde Climate Record

et al. 2008

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“…Mears et al (2006) suspect that especially the lower stratospheric time series from radiosondes are biased and Sherwood et al (2005) and Randel and Wu (2006) have described pervasive daytime biases in the tropics. Allen and Sherwood (2007) have further shown that the apparent cooling in tropical radiosonde temperatures is not consistent with wind shear changes in this region. However, all this evidence has been fragmentary so far and the radiosonde biases have yet to be removed in a comprehensive manner.…”

Section: Introductionmentioning

confidence: 89%

Toward Elimination of the Warm Bias in Historic Radiosonde Temperature Records—Some New Results from a Comprehensive Intercomparison of Upper-Air Data

2008

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The apparent cooling trend in observed global mean temperature series from radiosonde records relative to Microwave Sounding Unit (MSU) radiances has been a long-standing problem in upper-air climatology. It is very likely caused by a warm bias of radiosonde temperatures in the 1980s, which has been reduced over time with better instrumentation and correction software. The warm bias in the MSU-equivalent lower stratospheric (LS) layer is estimated as 0.6 Ϯ 0.3 K in the global mean and as 1.0 Ϯ 0.3 K in the tropical (20°S-20°N) mean. These estimates are based on comparisons of unadjusted radiosonde data, not only with MSU data but also with background forecast (BG) temperature time series from the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and with two new homogenized radiosonde datasets. One of the radiosonde datasets [Radiosonde Observation Correction using Reanalyses (RAOBCORE) version 1.4] employs the BG as reference for homogenization, which is not strictly independent of MSU data. The second radiosonde dataset uses the dates of the breakpoints detected by RAOBCORE as metadata for homogenization. However, it relies only on homogeneous segments of neighboring radiosonde data for break-size estimation. Therefore, adjustments are independent of satellite data.Both of the new adjusted radiosonde time series are in better agreement with satellite data than comparable published radiosonde datasets, not only for zonal means but also at most single stations. A robust warming maximum of 0.2-0.3K (10 yr)Ϫ1 for the 1979-2006 period in the tropical upper troposphere could be found in both homogenized radiosonde datasets. The maximum is consistent with mean temperatures of a thick layer in the upper troposphere and upper stratosphere (TS), derived from M3U3 radiances. Inferred from these results is that it is possible to detect and remove most of the mean warm bias from the radiosonde records, and thus most of the trend discrepancy compared to MSU LS and TS temperature products.The comprehensive intercomparison also suggests that the BG is temporally quite homogeneous after 1986. Only in the early 1980s could some inhomogeneities in the BG be detected and quantified.

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“…Here we briefly discuss further tests of this method and present the results of applying it to the global radiosonde network. Another advance on previous work is the use of observed wind shear fluctuations to help identify natural temperature variability, as recommended by Allen and Sherwood (2007).…”

Section: Introductionmentioning

confidence: 99%

Robust Tropospheric Warming Revealed by Iteratively Homogenized Radiosonde Data

et al. 2008

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Results are presented from a new homogenization of data since 1959 from 527 radiosonde stations. This effort differs from previous ones by employing an approach specifically designed to minimize systematic errors in adjustment, by including wind shear as well as temperature, by seasonally resolving adjustments, and by using neither satellite information nor station metadata. Relatively few artifacts were detected in wind shear, and associated adjustments were indistinguishable from random adjustments. Temperature artifacts were detected most often in the late 1980s-early 1990s. Uncertainty was characterized from variations within an ensemble of homogenizations and used to test goodness of fit with satellite data using reduced chi squared.The meridional variations of zonally aggregated temperature trend since 1979 moved significantly closer to those of the Microwave Sounding Unit (MSU) after data adjustment. Adjusted data from 5°S to 20°N continue to show relatively weak warming, but the error is quite large, and the trends are inconsistent with those at other latitudes. Overall, the adjusted trends are close to those of MSU for the temperature of the lower troposphere (TLT). For channel 2, they are consistent with two analyses (Remote Sensing Systems, p ϭ 0.54, and the University of Maryland, p ϭ 0.32) showing the strongest warming but not with the University of Alabama dataset ( p ϭ 0.0001). The troposphere warms at least as strongly as the surface, with local warming maxima at 300 hPa in the tropics and in the boundary layer of the extratropical Northern Hemisphere (ENH). Tropospheric warming since 1959 is almost hemispherically symmetric, but since 1979 it is significantly stronger in ENH and weaker in the extratropical Southern Hemisphere (ESH). ESH trends are relatively uncertain because of poor sampling. Stratospheric cooling also remains stronger than indicated by MSU and likely excessive.While this effort appears not to have detected all artifacts, trends appear to be systematically improved. Stronger warming is shown in the Northern Hemisphere where sampling is best. Several suggestions are made for future attempts. These results support the hypothesis that trends in wind data are relatively uncorrupted by artifacts compared to temperature, and should be exploited in future homogenization efforts.

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Utility of Radiosonde Wind Data in Representing Climatological Variations of Tropospheric Temperature and Baroclinicity in the Western Tropical Pacific

Cited by 17 publications

References 36 publications

Assessing Bias and Uncertainty in the HadAT-Adjusted Radiosonde Climate Record

Assessing Bias and Uncertainty in the HadAT-Adjusted Radiosonde Climate Record

Toward Elimination of the Warm Bias in Historic Radiosonde Temperature Records—Some New Results from a Comprehensive Intercomparison of Upper-Air Data

Robust Tropospheric Warming Revealed by Iteratively Homogenized Radiosonde Data

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