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NASA NTRS2021

Trend Detection of Atmospheric Time Series: Incorporating Appropriate Uncertainty Estimates and Handling Extreme Events

This paper is aimed at atmospheric scientists without formal training in statistical theory. Its goal is to, 1) provide a critical review of the rationale for trend analysis of the time series typically encountered in the field of atmospheric chemistry; 2) describe a range of trend-detection methods; and 3) demonstrate effective means of conveying the results to a general audience. Trend detections in atmospheric chemical composition data are often challenged by a variety of sources of uncertainty, which often behave differently to other environmental phenomena such as temperature, precipitation rate, or stream flow, and may require specific methods depending on the science questions to be addressed. Some sources of uncertainty can be explicitly included in the model specification, such as autocorrelation and seasonality, but some inherent uncertainties are difficult to quantify, such as data heterogeneity and measurement uncertainty due to the combined effect of short- and long-term natural variability, instrumental stability, and aggregation of data from sparse sampling frequency. Failure to account for these uncertainties might result in an inappropriate inference of the trends and their estimation errors. On the other hand, the variation in extreme events might be interesting for different scientific questions, for example, the frequency of extremely high surface ozone events and their relevance to human health. In this study we aim to, 1) review trend detection methods for addressing different levels of data complexity in different chemical species; 2) demonstrate that the incorporation of scientifically interpretable covariates can outperform pure numerical curve fitting techniques in terms of uncertainty reduction and improved predictability; 3) illustrate the study of trends based on extreme quantiles that can provide insight beyond standard mean or median based trend estimates; and 4) present an advanced method of quantifying regional trends based on the inter-site correlations of multi-site data. All demonstrations are based on time series of observed trace gases relevant to atmospheric chemistry, but the methods can be applied to other environmental data sets.

Trace gas↗

DOE OSTI2013

Temperature trends in the midlatitude summer mesosphere

[1] Here, we have performed trend studies in the mesosphere in the period 1961–2009 with Leibniz-Institute Middle Atmosphere (LIMA) model driven by European Centre for Medium-Range Weather Forecasts reanalysis below approximately 40 km and adapts temporal variations of CO 2 and O 3 according to observations. Temperatures in the mesosphere/lower thermosphere vary nonuniformly with time, mainly due to the influence of O 3 . In this report we analyze the contribution of varying concentrations of CO 2 and O 3 to the temperature trend in the mesosphere. It is important to distinguish between trends on pressure altitudes, z p , and geometrical altitudes, zgeo, where the latter includes the effect of shrinking due to cooling at lower heights. For the period 1961–2009, temperature trends on geometrical and pressure altitudes can differ by as much as -0.9 K/dec in the mesosphere. Temperature trends reach approximately -1.3±0.11 K/dec at z p ~60 km and -1.8±0.18 K/dec at z geo ~70 km, respectively. CO 2 is the main driver of these trends in the mesosphere, whereas O 3 contributes approximately one third, both on geometrical and pressure heights. Depending on the time period chosen, linear temperature trends can vary substantially. Altitudes of pressure levels in the mesosphere decrease by up to several hundred meters. We have performed long-term runs with LIMA applying twentieth century reanalysis dating back to 1871. Again, trends are nonuniform with time. Since the late nineteenth century, temperatures in the mesosphere have dropped by approximately 5–7 K on pressure altitudes and up to 10–12 K on geometrical altitudes.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2013

A Global Assessment of Long-Term Greening and Browning Trends in Pasture Lands Using the GIMMS LAI3g Dataset

Pasture ecosystems may be particularly vulnerable to land degradation due to the high risk of human disturbance (e.g., overgrazing, burning, etc.), especially when compared with natural ecosystems (non-pasture, non-cultivated) where direct human impacts are minimal. Using maximum annual leaf area index (LAImax) as a proxy for standing biomass and peak annual aboveground productivity, we analyze greening and browning trends in pasture areas from 1982-2008. Inter-annual variability in pasture productivity is strongly controlled by precipitation (positive correlation) and, to a lesser extent, temperature (negative correlation). Linear temporal trends are significant in 23% of pasture cells, with the vast majority of these areas showing positive LAImax trends. Spatially extensive productivity declines are only found in a few regions, most notably central Asia, southwest North America, and southeast Australia. Statistically removing the influence of precipitation reduces LAImax trends by only 13%, suggesting that precipitation trends are only a minor contributor to long-term greening and browning of pasture lands. No significant global relationship was found between LAImax and pasture intensity, although the magnitude of trends did vary between cells classified as natural versus pasture. In the tropics and Southern Hemisphere, the median rate of greening in pasture cells is significantly higher than for cells dominated by natural vegetation. In the Northern Hemisphere extra-tropics, conversely, greening of natural areas is 2-4 times the magnitude of greening in pasture areas. This analysis presents one of the first global assessments of greening and browning trends in global pasture lands, including a comparison with vegetation trends in regions dominated by natural ecosystems. Our results suggest that degradation of pasture lands is not a globally widespread phenomenon and, consistent with much of the terrestrial biosphere, there have been widespread increases in pasture productivity over the last 30 years.

ecosystems↗

NASA NTRS2015

Chlorophyll Variability in the Oligotrophic Gyres: Mechanisms, Seasonality and Trends

A 16-year (1998-2013) analysis of trends and seasonal patterns was conducted for the 5 subtropical ocean gyres using chlorophyll-a (Chl-a) retrievals from ocean color satellite data, sea surface temperature (SST) obtained from optimally interpolated Advanced Very High Resolution Radiometer (AVHRR) data, and sea-level anomaly (SLA) from Aviso multi-sensor altimetry data. Trend analysis was also performed on mixed-layer data derived from gridded temperature and salinity profiles (1998-2010) from the Simple Ocean Data Assimilation (SODA) model. The Chl-a monthly composites were constructed from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate-resolution Imaging Spectroradiometer (MODIS) on Aqua using two different algorithms: the standard algorithm (STD) that has been in use since the start of the SeaWiFS mission in 1997, and a more recently developed Ocean Color Index (OCI) algorithm that is purported to provide improved accuracy in low chlorophyll waters such as the oligotrophic regions of the subtropical gyres. Trends were obtained for all gyres using both STD and OCI algorithms, which demonstrated generally consistent results. The North Pacific, Indian Ocean, North Atlantic and South Atlantic gyres showed significant downward trends in Chl-a, while the South Pacific gyre has a much weaker upward trend with no statistical significance. Time series of satellite-derived net primary production (NPP) showed downward trends for all the gyres, while all 5 gyres exhibited positive trends in SST and SLA. The seasonal variability of Chl-a in each gyre is tightly coupled to the variability in mixed layer depth (MLD) with peak values in winter in both hemispheres when vertical mixing is more vigorous, reaching depths approaching the nutricline (ZNO3, here defined as the depth of the 0.2 micron nitrate concentration). On a seasonal basis, Chl-a concentrations increase when the MLD approaches or is deeper than the nutricline depth, in agreement with the concept that vertical mixing is the major driving mechanism for phytoplankton photosynthesis in the interior of the gyres. In addition, MLD and SST seasonal changes are well correlated indicating that SST is a reasonable index of vertical mixing in the gyres. The combination of surface warming trends and biomass reduction over the 16-year period has the potential to reduce atmospheric CO2 uptake by the gyres and therefore influence the global carbon cycle.

Long-term trends↗

NASA NTRS2022

Global Total Ozone Recovery Trends Attributed to Ozone-Depleting Substance (ODS) Changes Derived From Five Merged Ozone Datasets

We report on updated trends using different merged zonal mean total ozone datasets from satellite and ground-based observations for the period from 1979 to 2020. This work is an update of the trends reported in Weber et al. (2018) using the same datasets up to 2016. Merged datasets used in this study include NASA MOD v8.7 and NOAA Cohesive Data (COH) v8.6, both based on data from the series of Solar Backscatter Ultraviolet (SBUV), SBUV-2, and Ozone Mapping and Profiler Suite (OMPS) satellite instruments (1978–present), as well as the Global Ozone Monitoring Experiment (GOME)-type Total Ozone – Essential Climate Variable (GTO-ECV) and GOME-SCIAMACHY-GOME-2 (GSG) merged datasets (both 1995–present), mainly comprising satellite data from GOME, SCIAMACHY, OMI, GOME-2A, GOME-2B, and TROPOMI. The fifth dataset consists of the annual mean zonal mean data from ground-based measurements collected at the World Ozone and Ultraviolet Radiation Data Centre (WOUDC). Trends were determined by applying a multiple linear regression (MLR) to annual mean zonal mean data. The addition of 4 more years consolidated the fact that total ozone is indeed slowly recovering in both hemispheres as a result of phasing out ozone-depleting substances (ODSs) as mandated by the Montreal Protocol. The near-global (60° S–60° N) ODS-related ozone trend of the median of all datasets after 1995 was 0.4 ± 0.2 (2σ) %/decade, which is roughly a third of the decreasing rate of 1.5 ± 0.6 %/decade from 1978 until 1995. The ratio of decline and increase is nearly identical to that of the EESC (equivalent effective stratospheric chlorine or stratospheric halogen) change rates before and after 1995, confirming the success of the Montreal Protocol. The observed total ozone time series are also in very good agreement with the median of 17 chemistry climate models from CCMI-1 (Chemistry-Climate Model Initiative Phase 1) with current ODS and GHG (greenhouse gas) scenarios (REF-C2 scenario). The positive ODS-related trends in the Northern Hemisphere (NH) after 1995 are only obtained with a sufficient number of terms in the MLR accounting properly for dynamical ozone changes (Brewer–Dobson circulation, Arctic Oscillation (AO), and Antarctic Oscillation (AAO)). A standard MLR (limited to solar, Quasi-Biennial Oscillation (QBO), volcanic, and El Niño–Southern Oscillation (ENSO)) leads to zero trends, showing that the small positive ODS-related trends have been balanced by negative trend contributions from atmospheric dynamics, resulting in nearly constant total ozone levels since 2000.

Total Column Ozone Trends↗

NASA NTRS2022

A Synopsis of AIRS Global-Mean Clear-Sky Radiance Trends From 2003 to 2020

Atmospheric Infrared Sounder (AIRS) aboard the National Aeronautics and Space Administration (NASA) Aqua satellite has been operating since September 2002. Its information content, superb instrument performance, and dense sampling pattern make the AIRS radiances an invaluable data set for climate studies. The trends of global-mean, nadir-view, clear-sky AIRS radiances from 2003 to 2020 are studied here, together with the counterparts of synthetic radiances based on two reanalyzes, European Centre for Medium-Range Weather Forecasts Reanalysis V5 (ECMWF ERA5) and NASA Goddard Earth Observing System V5.4.1 (GEOS-5.4.1; a reanalysis product without assimilation of hyperspectral radiances such as AIRS). The AIRS observation shows statistically significant negative trends in most of its CO2 channels, positive but non-significant trends in the channels over the window regions, and statistically significant positive trends in some of its H2O channels. The best agreements between observed and simulated radiance trends are seen over the CO2 tropospheric channels, while the observed and simulated trends over the CO2 stratospheric channels are opposite. ERA5 results largely agree with the AIRS observation over the H2O channels. The comparison in the H2O channels helps reveal a data continuity issue in the GEOS-5.4.1. Contributions from individual variables to the radiance trends are also assessed by performing separate simulations. This study provides the first synopsis of the global-mean trend of AIRS radiances over all its thermal-IR channels.

CO2↗

DOE OSTI2015

Detectability of historical trends in station‐based precipitation characteristics over the continental United States

Abstract The goal of this paper is to detect secular trends in observed, station‐based precipitation variations and extreme event occurrences over the United States. By definition, detectable trends are those that are unlikely to have arisen from internal variability alone. To represent this internal variability, we use station‐specific, seasonally varying, daily time scale stationary stochastic weather models—models in which the simulated interannual‐to‐multidecadal precipitation variance is purely the result of the random evolution of daily precipitation events within a given time period—to first estimate the trends in various means and extremes that can occur even with fixed, climatological daily precipitation characteristics. Detection of secular trends in the observed climate—whether naturally or anthropogenically induced—can then be defined relative to this stochastic variability, i.e., as trends in the means and/or extremes that are likely to have occurred only through a change in the underlying precipitation characteristics. The derived results have two important ramifications. First, they identify “hot spot” regions in which trends in precipitation characteristics are already emerging from within the envelope of stochastic variability, including (but not limited to) positive trends in annual occurrence across most of the U.S. and positive trends in annual intensity and heavy‐event accumulations across the Interior Plains and around the Great Lakes. Further, they identify “sentinel” metrics which show the greatest detectability—e.g., annual precipitation occurrence and intensity—as well as those which show the least detectability and hence are unlikely to produce any statistically meaningful signals—e.g., seasonal total precipitation and extremes.

Anderson, Bruce T.↗

DOE OSTI2017

Long-Term Warming Trends in Korea and Contribution of Urbanization: An Updated Assessment: Urbanization Contribution in Korea

This study conducted an updated analysis of the long-term temperature trends over South Korea and reassessed the contribution of the urbanization effect to the local warming trends. Linear trends were analyzed for three different periods over South Korea in order to consider possible inhomogeneity due to changes in the number of available stations: recent 103 years (1912–2014), 61 years (1954–2014), and42 years (1973–2014). The local temperature has increased by 1.90°C, 1.35°C, and 0.99°C during the three periods, respectively, which are found 1.4–2.6 times larger than the global land mean trends. The countries located in the northern middle and high latitudes exhibit similar warming trends (about 1.5 times stronger than the global mean), suggesting a weak influence of urbanization on the local warming over South Korea.Urbanization contribution is assessed using two methods. First, results from “city minus rural” methods showed that 30–45% of the local warming trends during recent four decades are likely due to the urbanization effect, depending on station classification methods and analysis periods. Results from an“observation minus reanalysis” method using the Twentieth Century Reanalysis (20CR) data sets (v2 and v2c)indicated about 25–30% contribution of the urbanization effect to the local warming trend during the recent six decades. However, the urbanization contribution was estimated as low as 3–11% when considering the century-long period. Our results confirm large uncertainties in the estimation of urbanization contribution when using shorter-term periods and suggest that the urbanization contribution to the century-long warming trends could be much lower.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Trends in extreme temperature over Nigeria from percentile‐based threshold indices

ABSTRACT This study analyses spatial and temporal trends in extreme temperature indices over Nigeria. The percentile indices were calculated from newly homogenized daily minimum and maximum temperature data for the period 1971–2012 for 21 stations in Nigeria. Indices describing the characteristics of hot extremes and cold extremes are calculated with the RClimDex software. The annual and seasonal trends in these indices are obtained using the ordinary least square fit and the statistical significance tested using the R‐based modified Mann–Kendall test. We examine characteristics of these indices for the entire country and separately for the three geographical zones in Nigeria: Guinea, Savanna, and Sahel. The spatial and temporal patterns of trends in the indices indicate that Nigeria has experienced statistically significant increase in the frequency of hot extreme and decrease in cold extreme events. Although majority of the stations have significant trends in warm days and warm nights, the annual trend is greatest in warm nights. In addition, the rate of warming in minimum temperature (‘warm nights’) is stronger in June, July, August ( JJA ) and September, October, November ( SON ) compare with December, January, February ( DJF ) and March, April, May ( MAM ). As for the trends in cold days and cold nights, the trends in cold nights are larger than for cold days at both the annual and seasonal scales. The regional analysis indicates that trends in warm nights and cold nights are most pronounced in Guinea and Sahel regions.

Abatan, Abayomi A.↗

NASA NTRS1994

Trends in surface ozone over Europe, 1978-1990

It has been suggested that surface ozone concentrations in rural areas of Europe have been increasing at a rate of 1 to 3 percent per year over the past two to three decades, presumably due to human influences (Feister and Warmbt, 1987; Bojkov, 1988; Penkett, 1989). Recently, we have analyzed surface ozone data from 20 European stations of differing character (remote, rural, suburban and urban) for a common period of 1978-1988 (Low et al., 1992). It was found that there were pronounced annual and seasonal variations in the linear trends in different areas, and there was no dominant region-wide trend. In spring and, most notably, summer, stations on the maritime fringe of the network generally exhibited negative trends whilst those located further into the continental interior exhibited positive trends. In winter, most of the stations in the network exhibited positive trends. Relatively few of these trends were statistically significant. This paper updates our earlier analysis by extending the data sets of the network up to the year 1990. The spatial variations in surface ozone trends over the extended period 1978-1990 are examined and discussed in comparison to the 1978-1988 patterns. The update confirms the overall conclusions of the earlier analysis, specifically that caution should be exercised in interpreting the results of trend analyses based on station data representative of a limited period of time and/or geographical area.

Low, Pak Sum↗

NASA NTRS1994

Trend analysis of the long-term Swiss ozone measurements

Trend analyses, assuming a linear trend which started at 1970, were performed from total ozone measurements from Arosa (Switzerland, 1926-1991). Decreases in monthly mean values were statistically significant for October through April showing decreases of about 2.0-4 percent per decade. For the period 1947-91, total ozone trends were further investigated using a multiple regression model. Temperature of a mountain peak in Switzerland (Mt. Santis), the F10.7 solar flux series, the QBO series (quasi biennial oscillation), and the southern oscillation index (SOI) were included as explanatory variables. Trends in the monthly mean values were statistically significant for December through April. The same multiple regression model was applied to investigate the ozone trends at various altitudes using the ozone balloon soundings from Payerne (1967-1989) and the Umkehr measurements from Arosa (1947-1989). The results show four different vertical trend regimes: On a relative scale changes were largest in the troposphere (increase of about 10 percent per decade). On an absolute scale the largest trends were obtained in the lower stratosphere (decrease of approximately 6 per decade at an altitude of about 18 to 22 km). No significant trends were observed at approximately 30 km, whereas stratospheric ozone decreased in the upper stratosphere.

Staehelin, Johannes↗

NASA NTRS1994

Seasonal trend analysis of published ground-based and TOMS total ozone data through 1991

A seasonal trend analysis of published Dobson (including stations' newly revised and Brewer-simulated Dobson) total ozone data through 1991 from a network of 56 stations has been performed, using three different data periods. The trend results for the longest data period 1964 - 1991 indicate substantial negative trends in ozone in the higher northern latitudes during the winter and spring seasons, some evidence of negative trend in the higher southern latitudes (30 deg S - 55 deg S) during all seasons, and trends close to zero for all seasons over the 30 deg S - 30 deg N latitude range. For the shortest data period, November 1978 through 1991, there is a clear indication that trends have become more negative in the higher northern latitudes, especially during the winter and spring seasons, and also in the higher southern latitudes in all seasons. A seasonal trend analysis of zonal averages of total ozone mapping spectrometer (TOMS) satellite total ozone data for the comparable period November 1978 through 1991 has also been performed, and moderately good agreement is found between trends in Dobson and TOMS data over this period.

Reinsel, Gregory C.↗

NASA NTRS1995

Ozone trends deduced from combined Nimbus 7 SBUV and NOAA 11 SBUV/2 data

The long-term time series of global ozone from the Nimbus-7 Solar Backscatter Ultraviolet instrument (SBUV) (Nov. 1978-June 1990) are extended through June 1994 by using measurements from the NOAA-11 SBUV/2. The data sets are merged based upon comparisons during the 18-month overlap period in which both instruments were operational. During this period, the average offset between the two time series is less than 2% in total ozone, and less than 6% in Umkehr layers 1-10. A linear-regression trend model is applied to the extended time series to calculate updated trends as a function of latitude and altitude. Trends through June 1994 are 1.5-2% per decade less negative than through June 1990 in the tropical middle stratosphere (35-40 km) and in the upper stratosphere (45-50 km) at mid-latitudes. In the lower stratosphere, the trends are nearly 1.5% per decade more negative in the southern hemisphere tropical regions to 25 deg S, but remain relatively unchanged elsewhere. The seasonal structure of the total ozone trends is similar to past trend study results, but the magnitude of the seasonal trend can vary by 2% per decade depending on the length of the time series. Both Total Ozone Mapping Spectrometer (TOMS) (through April 1993) and SBUV total ozone time series show small negative trends in the equatorial region, though they are not statistically at the 2-sigma level.

Hollandsworth, S. M.↗

NASA NTRS1998

A Monte Carlo Uncertainty Analysis of Ozone Trend Predictions in a Two Dimensional Model

We use Monte Carlo analysis to estimate the uncertainty in predictions of total O3 trends between 1979 and 1995 made by the Goddard Space Flight Center (GSFC) two-dimensional (2D) model of stratospheric photochemistry and dynamics. The uncertainty is caused by gas-phase chemical reaction rates, photolysis coefficients, and heterogeneous reaction parameters which are model inputs. The uncertainty represents a lower bound to the total model uncertainty assuming the input parameter uncertainties are characterized correctly. Each of the Monte Carlo runs was initialized in 1970 and integrated for 26 model years through the end of 1995. This was repeated 419 times using input parameter sets generated by Latin Hypercube Sampling. The standard deviation (a) of the Monte Carlo ensemble of total 03 trend predictions is used to quantify the model uncertainty. The 34% difference between the model trend in globally and annually averaged total O3 using nominal inputs and atmospheric trends calculated from Nimbus 7 and Meteor 3 total ozone mapping spectrometer (TOMS) version 7 data is less than the 46% calculated 1 (sigma), model uncertainty, so there is no significant difference between the modeled and observed trends. In the northern hemisphere midlatitude spring the modeled and observed total 03 trends differ by more than 1(sigma) but less than 2(sigma), which we refer to as marginal significance. We perform a multiple linear regression analysis of the runs which suggests that only a few of the model reactions contribute significantly to the variance in the model predictions. The lack of significance in these comparisons suggests that they are of questionable use as guides for continuing model development. Large model/measurement differences which are many multiples of the input parameter uncertainty are seen in the meridional gradients of the trend and the peak-to-peak variations in the trends over an annual cycle. These discrepancies unambiguously indicate model formulation problems and provide a measure of model performance which can be used in attempts to improve such models.

Considine, D. B.↗

NASA NTRS2004

Petrology of New Stannern-trend Eucrites and Eucrite Genesis

Eucrites are basaltic meteorites of the howardite-eucrite-diogenite (HED) suite that originated on a differentiated asteroid, possibly 4 Vesta. Basaltic eucrites are divided into three subgroups based on composition: main group, Stannern-trend, and Nuevo Laredo-trend. The main group and Nuevo Laredo-trend define a sequence formed by fractional crystallization of pigeonite and plagioclase from primitive parent melts [2, 3]. The Stannern-trend cannot be explained this way, but may rather represent a partial-melt sequence of their parent body. However, this model seems inadequate to explain eucrite siderophile element contents, and it is difficult to develop a single unifying model for petrogenesis of all eucrites. Until recently, there were only four Stannern- trend eucrites. One is an anomalous partial cumulate. There is little geochemical variation among these meteorites, so the Stannern-trend was poorly defined. Geochemical studies have identified four additional eucrites as members of the Stannern-trend; one extends the Stannern-trend closer to the main group [5]. No detailed descriptions of these rocks have been published. In order to better integrate these eucrites into the suite, we have done petrologic study of them. They are: LEW 88010, PCA 82501, PCA 91006 and PCA 91179.

Gardner, K. G.↗

NASA NTRS2008

Seasonal Trends in Stratospheric Water Vapor as Derived from SAGE II Data

Published analysis of HALOE and Boulder balloon measurements of water vapor have shown conflicting trends in stratospheric water vapor for the periods of 1981 through 2005. Analysis of the SAGE II monthly mean water vapor data filtered for large aerosol events for time periods from 1985-1991, 1995-1999, and 2000-2005 have shown a globally decreasing water vapor trend at 17.5km. Seasonal analysis for these three time periods show a decreasing trend in water vapor at 17.5km for the winter and spring seasons. The summer and autumn seasonal analysis show a decreasing trend from 1985-2005, however, there is a increasing trend in water vapor at 17.5km for these seasons during 1995-2005. Latitude vs height seasonal analysis show a decreasing trend in the lower stratosphere between 20S - 20N for the autumn season, while at the latitudes of 30-50S and 30-50N there is an increasing trend in water vapor at heights up to 15km for that season. Comparison with regions of monsoon activity (Asian and North American) show that the Asian monsoon region had some effect on the lower stratospheric moistening in 1995-1999, however, for the time period of 2000-2005, there was no change in the global trend analysis due to either monsoon region. This may be due to the limitations of the SAGE II data from 2000-2005.

Roell, Marilee M.↗

NASA NTRS2006

Identifying Trends in Deep Space Network Monitor Data

A computer program has been developed that analyzes Deep Space Network monitor data, looking for changes of trends in critical parameters. This program represents a significant improvement over the previous practice of manually plotting data and visually inspecting the resulting graphs to identify trends. This program uses proven numerical techniques to identify trends. When a statistically significant trend is detected, then it is characterized by means of a symbol that can be used by pre-existing model-based reasoning software. The program can perform any of the following functions: Given an expectation that data in a given list should exhibit an upward, downward, constant, or unknown trend, it can determine whether the data do or do not follow such a trend. Given a list of data, it can identify which of the aforementioned trends the data follow. Given two lists of data, it can determine whether or not both follow the same trend. This program can be executed on a variety of computers. It can be distributed in either source code or binary code form. It must be run in conjunction with any one of a number of Lisp compilers that are available commercially or as shareware.

James, Mark↗

NASA NTRS2010

21st Century Trends in Antarctic Temperature and Polar Stratospheric Cloud (PSC) Area in the GEOS Chemistry-Climate Model

This study examines trends in Antarctic temperature and APSC, a temperature proxy for the area of polar stratospheric clouds, in an ensemble of Goddard Earth Observing System (GEOS) chemistry-climate model (CCM) simulations of the 21st century. A selection of greenhouse gas, ozone-depleting substance, and sea surface temperature scenarios is used to test the trend sensitivity to these parameters. One scenario is used to compare temperature trends in two versions of the GEOS CCM. An extended austral winter season is examined in detail. In May, June, and July, the expected future increase in CO2-related radiative cooling drives temperature trends in the Antarctic lower stratosphere. At 50 hPa, a 1.3 K cooling is expected between 2000 and 2100. Ozone levels increase, despite this robust cooling signal and the consequent increase in APSC, suggesting the enhancement of stratospheric transport in future. In the lower stratosphere, the choice of climate change scenarios does not affect the magnitude of the early winter cooling. Midwinter temperature trends are generally small. In October, APSC trends have the same sign as the prescribed halogen trends. That is, there are negative APSC trends in "grealistic future" simulations, where halogen loading decreases in accordance with the Montreal Protocol and CO2 continues to increase. In these simulations, the speed of ozone recovery is not influenced by either the choice of sea surface temperature and greenhouse gas scenarios or by the model version.

Hurwitz, M. M.↗