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Dian J. Seidel and Melissa Free

Abstract

Using a reanalysis of the climate of the past half century as a model of temperature variations over the next half century, tests of various data collection protocols are made to develop recommendations for observing system requirements for monitoring upper-air temperature. The analysis focuses on accurately estimating monthly climatic data (specifically, monthly average temperature and its standard deviation) and multidecadal trends in monthly temperatures at specified locations, from the surface to 30 hPa. It does not address upper-air network size or station location issues.

The effects of reducing the precision of temperature data, incomplete sampling of the diurnal cycle, incomplete sampling of the days of the month, imperfect long-term stability of the observations, and changes in observation schedule are assessed. To ensure accurate monthly climate statistics, observations with at least 0.5-K precision, made at least twice daily, at least once every two or three days are sufficient. Using these same criteria, and maintaining long-term measurement stability to within 0.25 (0.1) K, for periods of 20 to 50 yr, errors in trend estimates can be avoided in at least 90% (95%) of cases. In practical terms, this requires no more than one intervention (e.g., instrument change) over the period of record, and its effect must be to change the measurement bias by no more than 0.25 (0.1) K. The effect of the first intervention dominates the effects of subsequent, uncorrelated interventions. Changes in observation schedule also affect trend estimates. Reducing the number of observations per day, or changing the timing of a single observation per day, has a greater potential to produce errors in trends than reducing the number of days per month on which observations are made.

These findings depend on the validity of using reanalysis data to approximate the statistical nature of future climate variations, and on the statistical tests employed. However, the results are based on conservative assumptions, so that adopting observing system requirements based on this analysis should result in a data archive that will meet climate monitoring needs over the next 50 yr.

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Yehui Zhang, Dian J. Seidel, and Shaodong Zhang

Abstract

Estimates of trends in planetary boundary layer height over Europe are presented, based on daily radiosonde observations at 25 stations during 1973–2010 and using a bulk Richardson number approach to determine heights. Most stations show statistically significant increases in daytime heights in all four seasons, but fewer show statistically significant trends in nighttime heights. Daytime height variations show an expected strong negative correlation with surface relative humidity and strong positive correlation with surface temperature at most stations studied, on both year-to-year and day-to-day time scales. Similar relations hold for long-term trends: increasing daytime boundary layer height is associated with decreasing surface relative humidity and increasing surface temperature at most stations. The extent to which these changes are regionally representative or local reflections of environmental changes near the observing stations is difficult to ascertain.

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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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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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Bomin Sun, Thomas R. Karl, and Dian J. Seidel

Abstract

U.S. weather stations operated by NOAA’s National Weather Service (NWS) have undergone significant changes in reporting and measuring cloud ceilings. Stations operated by the Department of Defense have maintained more consistent reporting practices. By comparing cloud-ceiling data from 223 NWS first-order stations with those from 117 military stations, and by further comparison with changes in physically related parameters, inhomogeneous records, including all NWS records based only on automated observing systems and the military records prior to the early 1960s, were identified and discarded. Data from the two networks were then used to determine changes in daytime ceiling height (the above-ground height of the lowest sky-cover layer that is more than half opaque) and ceiling occurrence frequency (percentage of total observations that have ceilings) over the contiguous United States since the 1950s.

Cloud-ceiling height in the surface–3.6-km layer generally increased during 1951–2003, with more significant changes in the period after the early 1970s and in the surface–2-km layer. These increases were mostly over the western United States and in the coastal regions. No significant change was found in surface–3.6-km ceiling occurrence during 1951–2003, but during the period since the early 1970s, there is a tendency for a decrease in frequency of ceilings with height below 3.6 km. Cloud-ceiling heights above 3.6 km have shown no significant changes in the past 30 yr, but there has been an increase in frequency, consistent with the increase in ceiling height below 3.6 km. For the surface–3.6-km layer, physically consistent changes were identified as related to changes in ceiling height and frequency of occurrence. This included reductions in precipitation frequency related to low ceiling frequency, and surface warming and decreasing relative humidity accompanying increasing ceiling heights during the past 30 yr.

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Rebecca J. Ross, William P. Elliott, Dian J. Seidel, and Participating AMIP-II Modeling Groups

Abstract

Annual and seasonal correlations between temperature and both specific and relative humidity are presented based on radiosonde station data over the tropical Pacific Ocean and North America. Results are presented for the surface and the 850-, 700-, and 500-hPa levels. The correlations between anomalies of temperature and relative humidity are generally negative, and those between temperature and specific humidity are generally positive. Longitudinal differences in the pattern of correlations are found both in low latitudes and over midlatitude North America. In particular, near-zero or negative temperature–specific humidity correlations are found in the western United States at and below 700 hPa (especially in summer) and over the western tropical Pacific at 700 and 500 hPa (especially in winter). The observed correlation patterns are compared with those of 12 atmospheric general circulation model (AGCM) simulations. Simulated high-latitude correlation patterns qualitatively agree with observations, but a sizable fraction of the correlations are higher than observed. The models show varying degrees of success in simulating the longitudinal differences in the temperature–specific humidity relationship in midlatitudes. At low latitudes, the models are generally unsuccessful at simulating the observed longitudinal differences. The simulated mean humidity fields are also compared with observations. The models show 10%–20% higher relative humidity than is observed at mid- and high latitudes and over the Tropics. However, over the Pacific region, the relative humidity bias is of opposite sign (models drier than observed) and is confined to the 850-hPa level.

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Amy H. Butler, Dian J. Seidel, Steven C. Hardiman, Neal Butchart, Thomas Birner, and Aaron Match

Abstract

Sudden stratospheric warmings (SSWs) are large, rapid temperature rises in the winter polar stratosphere, occurring predominantly in the Northern Hemisphere. Major SSWs are also associated with a reversal of the climatological westerly zonal-mean zonal winds. Circulation anomalies associated with SSWs can descend into the troposphere with substantial surface weather impacts, such as wintertime extreme cold air outbreaks. After their discovery in 1952, SSWs were classified by the World Meteorological Organization. An examination of literature suggests that a single, original reference for an exact definition of SSWs is elusive, but in many references a definition involves the reversal of the meridional temperature gradient and, for major warmings, the reversal of the zonal circulation poleward of 60° latitude at 10 hPa.

Though versions of this definition are still commonly used to detect SSWs, the details of the definition and its implementation remain ambiguous. In addition, other SSW definitions have been used in the last few decades, resulting in inconsistent classification of SSW events. We seek to answer the questions: How has the SSW definition changed, and how sensitive is the detection of SSWs to the definition used? For what kind of analysis is a “standard” definition useful? We argue that a standard SSW definition is necessary for maintaining a consistent and robust metric to assess polar stratospheric wintertime variability in climate models and other statistical applications. To provide a basis for, and to encourage participation in, a communitywide discussion currently underway, we explore what criteria are important for a standard definition and propose possible ways to update the definition.

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Yehui Zhang, Dian J. Seidel, Jean-Christophe Golaz, Clara Deser, and Robert A. Tomas

Abstract

Surface-based inversions (SBIs) are frequent features of the Arctic and Antarctic atmospheric boundary layer. They influence vertical mixing of energy, moisture and pollutants, cloud formation, and surface ozone destruction. Their climatic variability is related to that of sea ice and planetary albedo, important factors in climate feedback mechanisms. However, climatological polar SBI properties have not been fully characterized nor have climate model simulations of SBIs been compared comprehensively to observations. Using 20 years of twice-daily observations from 39 Arctic and 6 Antarctic radiosonde stations, this study examines the spatial and temporal variability of three SBI characteristic—frequency of occurrence, depth (from the surface to the inversion top), and intensity (temperature difference over the SBI depth)—and relationships among them. In both polar regions, SBIs are more frequent, deeper, and stronger in winter and autumn than in summer and spring. In the Arctic, these tendencies increase from the Norwegian Sea eastward toward the East Siberian Sea, associated both with (seasonal and diurnal) variations in solar elevation angle at the standard radiosonde observation times and with differences between continental and maritime climates. Two state-of-the-art climate models and one reanalysis dataset show similar seasonal patterns and spatial distributions of SBI properties as the radiosonde observations, but with biases in their magnitudes that differ among the models and that are smaller in winter and autumn than in spring and summer. SBI frequency, depth, and intensity are positively correlated, both spatially and temporally, and all three are anticorrelated with surface temperature.

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Melissa Free, James K. Angell, Imke Durre, John Lanzante, Thomas C. Peterson, and Dian J. Seidel

Abstract

The utility of a “first difference” method for producing temporally homogeneous large-scale mean time series is assessed. Starting with monthly averages, the method involves dropping data around the time of suspected discontinuities and then calculating differences in temperature from one year to the next, resulting in a time series of year-to-year differences for each month at each station. These first difference time series are then combined to form large-scale means, and mean temperature time series are constructed from the first difference series. When applied to radiosonde temperature data, the method introduces random errors that decrease with the number of station time series used to create the large-scale time series and increase with the number of temporal gaps in the station time series. Root-mean-square errors for annual means of datasets produced with this method using over 500 stations are estimated at no more than 0.03 K, with errors in trends less than 0.02 K decade−1 for 1960–97 at 500 mb. For a 50-station dataset, errors in trends in annual global means introduced by the first differencing procedure may be as large as 0.06 K decade−1 (for six breaks per series), which is greater than the standard error of the trend. Although the first difference method offers significant resource and labor advantages over methods that attempt to adjust the data, it introduces an error in large-scale mean time series that may be unacceptable in some cases.

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