Abstract. Detection of long-term, linear trends is affected by a number of factors, including the size of trend to be detected, the time span of available data, and the magnitude of variability and autocorrelation of the noise in the data. The number of years of data necessary to detect a trend is strongly dependent on, and increases with, the magnitude of variance (o-2•) and autocorrelation coefficient (qb) of the noise. For a typical range of values of o-2• and 4> the number of years of data needed to detect a trend of 5%/decade can vary from -10 to >20 years, implying that in choosing sites to detect trends some locations are likely to be more efficient and cost-effective than others. Additionally, some environmental variables allow for an earlier detection of trends than other variables because of their low variability and autocorrelation. The detection of trends can be confounded when sudden changes occur in the data, such as when an instrument is changed or a volcano erupts. Sudden level shifts in data sets, whether due to artificial sources, such as changes in instrumentation or site location, or natural sources, such as volcanic eruptions or local changes to the environment, can strongly impact the number of years necessary to detect a given trend, increasing the number of years by as much as 50% or more. This paper provides formulae for estimating the number of years necessary to detect trends, along with the estimates of the impact of interventions on trend detection. The uncertainty associated with these estimates is also explored. The results presented are relevant for a variety of practical decisions in managing a monitoring station, such as whether to move an instrument, change monitoring protocols in the middle of a long-term monitoring program, or try to reduce uncertainty in the measurements by improved calibration techniques. The results are also useful for establishing reasonable expectations for trend detection and can be helpful in selecting sites and environmental variables for the detection of trends. An important implication of these results is that it will take several decades of high-quality data to detect the trends likely to occur in nature. IntroductionThe impact of human intervention in a changing environment has brought about increased concern for detecting trends in various types of environmental data. A variety of studies

An updated analysis of observed stratospheric temperature variability and trends is presented on the basis of satellite, radiosonde, and lidar observations. Satellite data include measurements from the series of NOAA operational instruments, including the Microwave Sounding Unit covering 1979-2007 and the Stratospheric Sounding Unit (SSU) covering 1979-2005. Radiosonde results are compared for six different data sets, incorporating a variety of homogeneity adjustments to account for changes in instrumentation and observational practices. Temperature changes in the lower stratosphere show cooling of ~0.5 K/decade over much of the globe for 1979-2007, with some differences in detail among the different radiosonde and satellite data sets. Substantially larger cooling trends are observed in the Antarctic lower stratosphere during spring and summer, in association with development of the Antarctic ozone hole. Trends in the lower stratosphere derived from radiosonde data are also analyzed, for a longer record (back to 1958); trends for the presatellite era (1958-1978) have a large range among the different homogenized data sets, implying large trend uncertainties. Trends in the middle and upper stratosphere have been derived from updated SSU data, taking into account changes in the SSU weighting functions due to observed atmospheric CO2 increases. The results show mean cooling of 0.5-1.5 K/decade during 1979-2005, with the greatest cooling in the upper stratosphere near 40-50 km. Temperature anomalies throughout the stratosphere were relatively constant during the decade 1995-2005. Long records of lidar temperature measurements at a few locations show reasonable agreement with SSU trends, although sampling uncertainties are large in the localized lidar measurements. Updated estimates of the solar cycle influence on stratospheric temperatures show a statistically significant signal in the tropics (~30°N-S), with an amplitude (solar maximum minus solar minimum) of ~0.5 K (lower stratosphere) to ~1.0 K (upper stratosphere)

It is widely assumed that variations in Earth's radiative energy budget at large time and space scales are small. We present new evidence from a compilation of over two decades of accurate satellite data that the top-of-atmosphere (TOA) tropical radiative energy budget is much more dynamic and variable than previously thought. Results indicate that the radiation budget changes are caused by changes in tropical mean cloudiness. The results of several current climate model simulations fail to predict this large observed variation in tropical energy budget. The missing variability in the models highlights the critical need to improve cloud modeling in the tropics so that prediction of tropical climate on interannual and decadal time scales can be improved.

This paper is concerned with temporal data requirements for the assessment of trends and for estimating spatial correlations of atmospheric species.We examine statistically three basic issues:(1) the effect of autocorrelations in monthly observations and the effect of the length of data record on the precision of trend estimates, (2) the effect of autocorrelations in the daily data on the sampling frequency requirements with respect to the representativeness of monthly averages for trend estimation, and (3) the effect of temporal sampling schemes on estimating spatial reasons other than a coordinated network designed to measure global ozone change.In these studies,

Abstract. We present the results of two independent analyses of trends in the vertical distribution of ozone. For most of the ozonesonde stations we use data that were recently reevaluated and reprocessed to improve their quality and internal consistency. The two analyses give similar results for trends in ozone. We attribute differences in results primarily to differences in data selection criteria, rather than in statistical trend models. We find significant decreases

[1] Statistical trend analyses have been performed for monthly zonal average total ozone data from both TOMS and SBUV satellite sources and ground-based instruments over the period 1978-2002 for detection of a ''turnaround'' in the previous downward trend behavior and hence evidence for the beginning of an ozone recovery. Since other climatic and geophysical changes can impact ozone behavior and can influence the detection of turnaround and recovery, we also focus on accounting for ozone variations that may be ascribed to various physical and chemical influences. Thus we include in the statistical trend modeling and analysis the effects of various dynamical and circulation variations in the atmosphere, including those associated with the quasibiennial oscillation (QBO), Arctic Oscillation (AO) and Antarctic Oscillation (AAO), and Eliassen-Palm (EP) flux influences, as well as influences of solar cycle. A notable result of the analysis is that for latitude zones of 40°and above in both hemispheres, large positive and significant estimates of a change in trend (since 1996) are obtained (on the order of 1.5 to 3 DU per year). The dynamic index series, AO/AAO and EP flux, are found to have a substantial influence on total ozone for these higher latitudes, and significant influences of lesser magnitude are also found for lower latitudes. The feature of positive significant change in trend in total ozone over recent years, however, is obtained both without and with the dynamical index terms included in the statistical models.

The Clouds and the Earth's Radiant Energy System (CERES) is part of NASA's Earth Observing System (EOS). CERES objectives include the following. 1) For climate change analysis, provide a continuation of the Earth Radiation Budget Experiment (ERBE) record of radiative fluxes at the top-of-the-atmosphere (TOA), analyzed using the same techniques as the existing ERBE data. 2) Double the accuracy of estimates of radiative fluxes at TOA and the earth's surface; 3) Provide the first long-term global estimates of the radiative fluxes within the earth's atmosphere. 4) Provide cloud property estimates collocated in space and time that are consistent with the radiative fluxes from surface to TOA. In order to accomplish these goals, CERES uses data from a combination of spaceborne instruments: CERES scanners, which are an improved version of the ERBE broadband radiome

The 1992 global average total ozone, measured by the Total Ozone Mapping Spectrometer (TOMS) on the Nimbus-7 satellite, was 2 to 3 percent lower than any earlier year observed by TOMS (1979 to 1991). Ozone amounts were low in a wide range of latitudes in both the Northern and Southern hemispheres, and the largest decreases were in the regions from 10 degrees S to 20 degrees S and 100N to 60 degrees N. Global ozone in 1992 is at least 1.5 percent lower than would be predicted by a statistical model that includes a linear trend and accounts for solar cycle variation and the quasi-biennial oscillation. These results are confirmed by comparisons with data from other ozone monitoring instruments: the SBUV/2 instrument on the NOAA-11 satellite, the TOMS instrument on the Russian Meteor-3 satellite, the World Standard Dobson Instrument 83, and a collection of 22 ground-based Dobson instruments.