Global Tropospheric Temperature Research Articles

Has global warming already arrived?

The enhancement of the atmospheric greenhouse effect due to the increase in the atmospheric greenhouse gases is often considered as responsible for global warming (known as greenhouse hypothesis of global warming). In this context, the temperature field of global troposphere and lower stratosphere over the period 12/1978–07/2018 is explored using the recent Version 6 of the UAH MSU/AMSU global satellite temperature dataset. Our analysis did not show a consistent warming with gradual increase from low to high latitudes in both hemispheres, as it should be from the global warming theory. In addition, in the lower stratosphere the temperature cooling over both poles is lower than that over tropics and extratropics. To study further the thermal field variability we investigated the long-range correlations throughout the global lower troposphere-lower stratosphere region. The results show that the temperature field displays power-law behaviour that becomes stronger by going from the lower troposphere to the tropopause.This power-law behaviour suggests that the fluctuations in global tropospheric temperature at short intervals are positively correlated with those at longer intervals in a power-law manner. The latter, however, does not apply to global temperature in the lower stratosphere. This suggests that the investigated intrinsic properties of the lower stratospheric temperature are not related to those of the troposphere, as is expected by the global warming theory.

Long-Term Rainfall Variability in the Eastern Gangetic Plain in Relation to Global Temperature Change

ABSTRACTIndia’s annual weather cycle consists mainly of wet and dry periods with monsoonal rains being one of the significant wet periods that shows strong spatiotemporal variability. This study includes the climatological characteristics, fluctuation features, and periodic cycles of annual, seasonal, and monthly rainfall of seven river basins across the eastern Gangetic Plain (EGP) using the longest possible instrumental area-averaged monthly rainfall series (1829–2012). Understanding the relationships between these parameters and global tropospheric temperature changes and El Niño and La Niña climatic signals is also attempted.Climatologically, mean annual rainfall in the EGP varies from 1070.5 mm in the Tons River basin to 1508.6 mm in the Subarnarekha River basin. The highest rainfall in the EGP occurs during monsoon (1188 mm). The annual rainfall in all river basins and monsoon rainfall in four river basins is normally distributed. Annual and monsoonal rainfall in the Brahmani and Son River basins show a significant decreasing long-term trend. Over the last 20 years, annual rainfall in all river basins and monsoonal rainfall in five river basins show a decreasing trend. The power spectra for all rainfall series are characterized by consistent significant wavelength peaks at 3–5 years, 10–20 years, 40 years, and more than 80 years. Short-term fluctuations with a period less than 10 years is the major contributor to total variance in annual and/or monsoon rainfall (77.6%), followed by decadal variations with a period of 10–30 years (13.1%) and a long-term trend with a period greater than 30 years (9.3%).Temperature and thickness gradients from the Tibet–Himalaya–Karakoram–Hindu Kush highlands to eight strong highs show a significant correlation with rainfall during the onset and withdrawal phases of summer monsoon in the EGP.

Effect of Global Temperature Changes on Rainfall Fluctuations over River Basins Across Eastern Indo-GangeticPlains

Annual weather cycle of India comprises mainly wet and dry periods with monsoonal rains as one of the significant wet periods. All India monsoon rainfall shows strong spatio-temporal variations and large departures from its normal values. It is proposed in this study to document climatological characteristics, fluctuation features and periodic cycles in annual, seasonal and monthly rainfall series of seven river basins across eastern Indo-Gangetic plains (EIGP) using longest possible instrumental area-averaged monthly rainfall series (sometimes goes back up to 1829) up to 2007. Understanding its relationships with the global tropospheric temperature changes and El Nino-La-Nina events are also attempted. Climatologically mean annual rainfall vary from 1070.5mm (±216.8mm) over Tons to 1508.6mm (±205.2mm) over Subarnarekha river basin. The highest rainfall over EIGP occurs during monsoon (1188±115.4mm) and that is during month of July (372.6±56.3mm). The annual and monsoonal rainfall of all river basins is normally distributed, except post-monsoon and winter. Over the period of available records, rainfall fluctuations showed 2-to-3 tendencies in the combination of increase, decrease and normal. Annual rainfall of none of the river basins show significant long term trend however, monsoonal rainfall of Brahmani, Sons, Mahanadi and EIGP does show significant decreasing long-term trend. In recent 20 years all river basins show declining tendency in monsoonal rainfall. Power spectra of all rainfall series are characterized by consistent significant peaks at 3-5 years, 10-20 years, 40 years and >80 years of wavelength. Short-term fluctuations of period <10 years is the major contributor of total variance of annual/monsoon rainfall (77.6%), followed by decadal variations of period 10-30 years (13.1%) and long-term trend of period >30 years (9.3%). The short term variations can be attributed to the variability in intensity and duration of rain producing weather systems, decadal variability is seems to be in relation with the different climatic signal and long-term changes are the manifestation of asymmetry in whole tropospheric warming across globe.

The role of remote sensing in monitoring global bulk tropospheric temperatures

The IPCC AR4 (2007) discussed bulk tropospheric temperatures as an indicator of atmospheric energy content. Here, we examine the latest publications about, and versions of, the AR4 data sets. The metric studied is the trend that represents the average rate of atmospheric energy accumulation that relates to increased greenhouse gas forcing. For temperatures from microwave instruments, UAHuntsville's indicates the lowest trend for 1979–2009 and National Oceanic and Atmospheric Administration – Center for Satellite Applications and Research (NOAA-STAR)'s the highest, being slightly higher than Remote Sensing Systems' (RSS). Updated analyses using radiosonde data suggest RSS and STAR experienced spurious warming after the mid-1990s. When satellite and radiosonde data sets are considered, the global trends for 1979–2009 of the lower and mid-troposphere are +0.15 and +0.06°C decade−1 respectively. Error ranges of these estimates, if we do not apply information that indicates some data sets contain noticeable trend problems, are at least ±0.05°C decade−1, which needs reduction to characterize forcing and response in the climate system accurately.

Satellite Global and Hemispheric Lower Tropospheric Temperature Annual Temperature Cycle

Previous analyses of the Earth’s annual cycle and its trends have utilized surface temperature data sets. Here we introduce a new analysis of the global and hemispheric annual cycle using a satellite remote sensing derived data set during the period 1979–2009, as determined from the lower tropospheric (LT) channel of the MSU satellite. While the surface annual cycle is tied directly to the heating and cooling of the land areas, the tropospheric annual cycle involves additionally the gain or loss of heat between the surface and atmosphere. The peak in the global tropospheric temperature in the 30 year period occurs on 10 July and the minimum on 9 February in response to the larger land mass in the Northern Hemisphere. The actual dates of the hemispheric maxima and minima are a complex function of many variables which can change from year to year thereby altering these dates.Here we examine the time of occurrence of the global and hemispheric maxima and minima lower tropospheric temperatures, the values of the annual maxima and minima, and the slopes and significance of the changes in these metrics. The statistically significant trends are all relatively small. The values of the global annual maximum and minimum showed a small, but significant trend. Northern and Southern Hemisphere maxima and minima show a slight trend toward occurring later in the year. Most recent analyses of trends in the global annual cycle using observed surface data have indicated a trend toward earlier maxima and minima.

Comment on “Influence of the Southern Oscillation on tropospheric temperature” by J. D. McLean, C. R. de Freitas, and R. M. Carter

McLean et al. (2009) (henceforth MFC09) claim that the El Niño–Southern Oscillation (ENSO), as represented by the Southern Oscillation Index (SOI), accounts for as much as 72% of the global tropospheric temperature anomaly and an even higher 81% of this anomaly in the tropics. They conclude that the SOI is a “dominant and consistent influence on mean global temperatures,” “and perhaps recent trends in global temperatures.” However, their analysis is inappropriate in a number of ways and overstates the influence of ENSO on the climate system. This comment first briefly reviews what is understood about the influence of ENSO on global temperatures and then shows that the analysis of MFC09 greatly overestimates the correlation between temperature anomalies and the SOI by inflating the power in the 2–6 year time window while filtering out variability on longer and shorter time scales. The suggestion in their conclusions that ENSO may be a major contributor to recent trends in global temperature is not supported by their analysis or any physical theory presented in their paper, especially as the analysis method itself eliminates the influence of trends on the purported correlations.

On the altitude dependence of the temperature scaling behaviour at the global troposphere

Detrended fluctuation analysis is applied to the mean monthly temperature values, over different heights of the global troposphere, during 1980–2004, to search for self-similarity properties. The results show that the tropospheric temperature anomalies obey persistent long-range power-law correlations for time-scales longer than about four months and shorter than about six years. This suggests that the temperature fluctuations over small time periods (i.e. a few months) are related to those over longer time periods (i.e. a few years). In addition, the long-range power-law persistence in the global tropospheric temperature fluctuations becomes stronger as the altitude increases.

Influence of the Southern Oscillation on tropospheric temperature

Time series for the Southern Oscillation Index (SOI) and global tropospheric temperature anomalies (GTTA) are compared for the 1958−2008 period. GTTA are represented by data from satellite microwave sensing units (MSU) for the period 1980–2008 and from radiosondes (RATPAC) for 1958–2008. After the removal from the data set of short periods of temperature perturbation that relate to near‐equator volcanic eruption, we use derivatives to document the presence of a 5‐ to 7‐month delayed close relationship between SOI and GTTA. Change in SOI accounts for 72% of the variance in GTTA for the 29‐year‐long MSU record and 68% of the variance in GTTA for the longer 50‐year RATPAC record. Because El Niño−Southern Oscillation is known to exercise a particularly strong influence in the tropics, we also compared the SOI with tropical temperature anomalies between 20°S and 20°N. The results showed that SOI accounted for 81% of the variance in tropospheric temperature anomalies in the tropics. Overall the results suggest that the Southern Oscillation exercises a consistently dominant influence on mean global temperature, with a maximum effect in the tropics, except for periods when equatorial volcanism causes ad hoc cooling. That mean global tropospheric temperature has for the last 50 years fallen and risen in close accord with the SOI of 5–7 months earlier shows the potential of natural forcing mechanisms to account for most of the temperature variation.

How Low Can We Go?

Climate Science![Figure][1] CREDIT: ISTOCK PHOTO Though it is well established that greenhouse gas emissions are causing the world to warm, policy-makers would benefit from further specific information in order to produce legislation that balances the environmental and economic effects of a given emissions reduction strategy. Washington et al. use a global coupled climate model to evaluate the consequences of a low-emission scenario developed by the United States Climate Change Science Program (CCSP), and thereby illustrate how aggressive mitigation can limit the rise of the global average tropospheric temperature to 1°C above current value by the year 2100. This temperature target is used because it is thought to represent the maximum at which the consequences of climate warming will remain manageable, before becoming dangerous. The authors also discuss ancillary climate consequences of this mitigation route, in an attempt to provide information relevant for the assessment of a wide range of policy options. Geophys. Res. Lett. 36 , L08703 (2009). [1]: pending:yes

Estimation of Tropospheric Temperature Trends from MSU Channels 2 and 4

Abstract The problems inherent in the estimation of global tropospheric temperature trends from a combination of near-nadir Microwave Sounding Unit (MSU) channel-2 and -4 data are described. The authors show that insufficient overlap between those two channels’ weighting functions prevents a physical removal of the stratospheric influence on tropospheric channel 2 from the stratospheric channel 4. Instead, correlations between stratospheric and tropospheric temperature fluctuations based upon ancillary (e.g., radiosonde) information can be used to statistically estimate a correction for the stratospheric influence on MSU 2 from MSU 4. Fu et al. developed such a regression relationship from radiosonde data using the 850–300-hPa layer as the target predictand. There are large errors in the resulting fit of the two MSU channels to the tropospheric target layer, so the correlations from the ancillary data must be relied upon to provide a statistical minimization of the resulting errors. Such relationships depend upon the accuracy of the particular training dataset as well as the dataset time period and its global representativeness (i.e., temporal and spatial stationarity of the statistics). It is concluded that near-nadir MSU channels 2 and 4 cannot be combined to provide a tropospheric temperature measure without substantial uncertainty resulting from a necessary dependence on ancillary information regarding the vertical profile of temperature variations, which are, in general, not well known on a global basis.

Calibration of multisatellite observations for climatic studies: Microwave Sounding Unit (MSU)

The Microwave Sounding Units (MSU) aboard the NOAA series of polar orbiting satellites has been used by three groups to monitor the very small trend in the global tropospheric temperature over the 25‐year satellite record. To obtain a homogeneous data set, each group made different calibration corrections of the MSUs in the form of fixed biases, and in some cases temperature‐dependent adjustments, to each of the nine satellite instruments using data during the overlap periods. Up until now, however, the adjustments are empirically based. To improve the accuracy as well as our understanding of the error sources, this paper develops an alternate, physical approach for intercalibrating the MSU instruments. The paper develops a calibration model for the MSU instrument that includes the errors in the cold space and warm target measurements, as well as the nonlinear factor. Corrections for these calibration errors are estimated using a least squares minimization where the predictors are the differences between all 12 overlapping satellite measurements at low and high latitudes. After applying the calibration corrections, the zonally averaged differences between satellite instruments are no larger than 0.03 K, independent of latitude. It is also found that the tropospheric temperature trend derived from MSU measurements is nearly the same as the surface trend. Furthermore, it now appears that much of the earlier inconsistency between the satellite and surface measurements arises from errors in the MSU calibration correction procedure, which can artificially suppress the temperature trend.

What may we conclude about global tropospheric temperature trends?

Three realizations of the atmospheric temperature representing the layer from the surface to about 18 km generated from microwave emissions were published in 2003. Their 1979–2002 linear trends were stated as +0.24 ± 0.02, +0.12 ± 0.02 and +0.03 ± 0.05°C decade−1. Because the upper portion of this layer includes the stratosphere, the opportunity to utilize radiosonde measurements as an independent assessor of these trend values is diminished. However, the University of Alabama in Huntsville (UAH) also produces a lower tropospheric temperature (LT) product (0–8 km, trend of +0.08°C decade−1) for which radiosondes are much more suitable. Comparisons of this UAH product with radiosonde‐simulated layer temperatures show no significant difference in LT trends, lending support for the least positive trend of the three deeper layer values (+0.03 ± 0.05°C decade−1) as it was constructed in the same manner as LT.

Global warming trend of mean tropospheric temperature observed by satellites.

We have analyzed the global tropospheric temperature for 1978 to 2002 with the use of passive microwave sounding data from the NOAA series of polar orbiters and the Earth Observing System Aqua satellite. To accurately retrieve the climatic trend, we combined the satellite data with an analytic model of temperature that contains three different time scales: a linear trend and functions that define the seasonal and diurnal cycles. Our analysis shows a trend of +0.22 degrees to 0.26 degrees C per 10 years, consistent with the global warming trend derived from surface meteorological stations.

Variations of solar coronal hole area and terrestrial lower tropospheric air temperature from 1979 to mid-1998: astronomical forcings of change in earth's climate?

The temperature anomaly of the terrestrial lower troposphere, inferred from the Microwave Sounding Unit (MSU) radiometers, is found to be inversely correlated with the area of the Sun covered by coronal holes. The correlation between the monthly time series of global tropospheric temperature anomaly and total coronal hole area from January 1979 to April 1998 has a Pearson coefficient of −0.46, which is different from zero at a 95% confidence level. Physical reasonings for the explained and unexplained parts of the correlation are discussed. The coronal hole area is a physical proxy for both the global-scale, 22-yr geometrical and shorter-term, dynamical components of the cosmic ray modulation, as well as the corpuscular emission of the Sun. Other solar parameters that may indicate a solar radiative effect on climate are also evaluated. It is concluded that variable fluxes either of solar charged particles or cosmic rays modulated by the solar wind, or both, may influence the terrestrial tropospheric temperature on timescale of months to years.

1973–1996 Trends in depth‐averaged tropospheric temperature

The analysis of thickness derived from the National Center for Environmental Prediction (NCEP) reanalysis indicates that there has been no statistically significant warming trend in layer‐averaged global tropospheric temperatures during the period 1979–1996. While this result is at variance with data based on surface information, NCEP trends and interannual variations are closely related to tropospheric mean‐layer temperatures obtained from the satellite‐based microwave sounding unit (MSU) lower‐tropospheric data set. When a longer period, 1973–1996, is used for the NCEP analysis, a warming trend within a 95% confidence interval is derived. However, it is nearly half the magnitude of the surface‐derived trends. Strong correlations of the yearly global surface temperature anomalies and those calculated for several layers in the NCEP data indicate coincident interannual temperature variations throughout the depth of the troposphere. The disagreement of both our analysis and satellite‐derived estimates with surface data could be due to a land surface measurement bias, a result of land use changes such as deforestation and agricultural expansion whose effects are not yet accounted for in the global temperature records, and/or a decoupling between surface and lower‐tropospheric temperature over the last several years.

Toward monitoring the tropospheric temperature by means of a general circulation model

The recent global tropospheric temperature trend can be reproduced by climate models that are forced only by observed sea surface temperature (SST) anomalies. In this study, simulations with the Hamburg climate model (ECHAM) are compared to temperatures from microwave sounding units (MSU) and to reanalyses from the European Centre for Medium‐Range Weather Forecasts. There is overall agreement of observed and simulated tropospheric temperature anomalies in many regions, in particular in the tropics and over the oceans, which lack conventional observing systems. This provides the opportunity to link physically different quantities, such as surface observations or analyses (SST) and satellite soundings (MSU) by means of a general circulation model. The proposed method can indicate inconsistencies between MSU temperatures and SSTs and has apparently done so. Differences between observed and simulated tropospheric temperature anomalies can partly be attributed to stratospheric aerosol variations due to major volcanic eruptions.

Impact of lunar phase on the timing of global and latitudinal tropospheric temperature maxima

Daily global and latitudinal‐band lower‐tropospheric temperatures are examined with respect to lunar phase. Over the past 16 years, global temperature data show that the warmest time of the synodic cycle generally occurs five to eight days before the full moon. This global pattern appears strongly in the polar and subtropical regions, however, the mid‐latitudes of both hemispheres are inversely related to the global pattern. These empirical findings discount the possibility that variations in radiant energy directly control lower‐tropospheric temperatures through the synodic month, and suggest a more indirect lunar modulation related to atmospheric circulation, specifically mid‐latitude Rossby wave variations.

Variation in global tropospheric temperature after adjustment for the El Nino influence, 1958–89

Data from a 63‐station radiosonde network are used to estimate the variation in global tropospheric (850–300 mb) temperature between 1958 and 1989. The annual temperature was a maximum in 1988, 0.42°C above the 1958–88 mean. However, the 1989 value is indicated to be only 0.12°C above this mean. During 1958–88, there has been a correlation of 0.76 (significant at the 0.1% level) between annual values of global tropospheric‐temperature deviation and annual values of sea‐surface temperature (SST) deviation in eastern equatorial Pacific two seasons earlier. The associated linear‐regression line indicates that an annual SST deviation of 1°C in the region 12°S‐2°N, 180°‐90°W has been related on average to an annual global tropospheric‐temperature deviation of 0.36°C. The annual values of global tropospheric temperature have been adjusted based on this regression. With this adjustment, the year‐to‐year variability in global tropospheric temperature is halved, the increase in decadal mean temperature between the 1960's and 1980's is reduced from 0.33°C to 0.24°C, the annual temperature is a maximum in 1989 (0.39°C above the 31‐year mean) rather than in 1988, and there is much more convincing evidence that the eruptions of Agung in 1963 and El Chichon in 1982 decreased global tropospheric temperatures by 0.2–0.3°C for about 3 years.