Precipitation and Temperature Variations on the Interannual Time Scale: Assessing the Impact of ENSO and Volcanic Eruptions

2011 ◽  
Vol 24 (9) ◽  
pp. 2258-2270 ◽  
Author(s):  
Guojun Gu ◽  
Robert F. Adler
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Surface Temperature ◽  
Volcanic Eruptions ◽  
Time Lags ◽  
Tropospheric Temperature ◽  
Precipitation Temperature ◽  
The Impact ◽  
Global Mean ◽  
Temperature Surface

Abstract The effects of ENSO and two large tropical volcanic eruptions (El Chichón, March 1982; Mt. Pinatubo, June 1991) are examined for the period of 1979–2008 using various satellite- and station-based observations of precipitation, temperature (surface and atmospheric), and tropospheric water vapor content. By focusing on the responses in the time series of tropical and global means over land, ocean, and land and ocean combined, the authors intend to provide an observational comparison of how these two phenomena, represented by Niño-3.4 and the tropical mean stratospheric aerosol optical thickness (τ), respectively, influence precipitation, temperature, and water vapor variations. As discovered in past studies, strong same-sign ENSO signals appear in tropical and global mean temperature (surface and tropospheric) over both land and ocean. However, ENSO only has very weak impact on tropical and global mean (land + ocean) precipitation, though intense anomalies are readily seen in the time series of precipitation averaged over either land or ocean. In contrast, the two volcanoes decreased not only tropical and global mean surface and tropospheric temperature but also tropical and global mean (land + ocean) precipitation. The differences between the responses to ENSO and volcanic eruptions are thus further examined by means of lag-correlation analyses. The ENSO-related peak responses in oceanic precipitation and sea surface temperature (SST) have the same time lags with Niño-3.4, 2 (4) months for the tropical (global) means. Tropical and global mean tropospheric water vapor over ocean (and land) generally follows surface temperature. However, land precipitation responds to ENSO much faster than temperature, suggesting a certain time needed for surface energy adjustment there following ENSO-related circulation and precipitation anomalies. Weak ENSO signals in the tropical and global mean mid- to lower-tropospheric atmospheric (dry) static instability are further discovered, which tend to be consistent with weak ENSO responses in the tropical and global mean (land + ocean) precipitation. For volcanic eruptions, tropical and global mean precipitation over either ocean or land responds faster than temperature (surface and atmospheric) and tropospheric water vapor averaged over the same areas, suggesting that precipitation tends to be more sensitive to volcanic-related solar forcing. The volcanic-related precipitation variations are further shown to be related to the changes in the mid- to lower-tropospheric atmospheric (dry) instability.

scholarly journals Identifying Signatures of Natural Climate Variability in Time Series of Global-Mean Surface Temperature: Methodology and Insights

2009 ◽  
Vol 22 (22) ◽  
pp. 6120-6141 ◽  
Author(s):  
David W. J. Thompson ◽  
John M. Wallace ◽  
Phil D. Jones ◽  
John J. Kennedy
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Surface Temperature ◽  
High Latitude ◽  
Volcanic Eruptions ◽  
Natural Variability ◽  
Natural Climate Variability ◽  
Global Mean Surface Temperature ◽  
Natural Climate ◽  
Global Mean

Abstract Global-mean surface temperature is affected by both natural variability and anthropogenic forcing. This study is concerned with identifying and removing from global-mean temperatures the signatures of natural climate variability over the period January 1900–March 2009. A series of simple, physically based methodologies are developed and applied to isolate the climate impacts of three known sources of natural variability: the El Niño–Southern Oscillation (ENSO), variations in the advection of marine air masses over the high-latitude continents during winter, and aerosols injected into the stratosphere by explosive volcanic eruptions. After the effects of ENSO and high-latitude temperature advection are removed from the global-mean temperature record, the signatures of volcanic eruptions and changes in instrumentation become more clearly apparent. After the volcanic eruptions are subsequently filtered from the record, the residual time series reveals a nearly monotonic global warming pattern since ∼1950. The results also reveal coupling between the land and ocean areas on the interannual time scale that transcends the effects of ENSO and volcanic eruptions. Globally averaged land and ocean temperatures are most strongly correlated when ocean leads land by ∼2–3 months. These coupled fluctuations exhibit a complicated spatial signature with largest-amplitude sea surface temperature perturbations over the Atlantic Ocean.

scholarly journals Global Influence of Tropical Pacific Variability with Implications for Global Warming Slowdown

2017 ◽  
Vol 30 (7) ◽  
pp. 2679-2695 ◽  
Author(s):  
Chuan-Yang Wang ◽  
Shang-Ping Xie ◽  
Yu Kosaka ◽  
Qinyu Liu ◽  
Xiao-Tong Zheng
Keyword(s):  
Global Warming ◽  
Surface Temperature ◽  
Time Scale ◽  
Decadal Variability ◽  
Temperature Response ◽  
Tropical Pacific ◽  
Tropospheric Temperature ◽  
Decadal Time Scale ◽  
The Impact ◽  
Global Mean

The impact of internal tropical Pacific variability on global mean surface temperature (GMST) is quantified using a multimodel ensemble. A tropical Pacific index (TPI) is defined to track tropical Pacific sea surface temperature (SST) variability. The simulated GMST is highly correlated with TPI on the interannual time scale but this correlation weakens on the decadal time scale. The time-scale dependency is such that the GMST regression equation derived from the observations, which are dominated by interannual variability, would underestimate the magnitude of decadal GMST response to tropical Pacific variability. The surface air temperature response to tropical Pacific variability is strong in the tropics but weakens in the extratropics. The regression coefficient of GMST against TPI shows considerable intermodel variations, primarily because of differences in high latitudes. The results have important implications for the planned intercomparison of pacemaker experiments that force Pacific variability to follow the observed evolution. The model dependency of the GMST regression suggests that in pacemaker experiments—model performance in simulating the recent “slowdown” in global warming—will vary substantially among models. It also highlights the need to develop observational constraints and to quantify the TPI effect on the decadal variability of GMST. Compared to GMST, the correlation between global mean tropospheric temperature and TPI is high on both interannual and decadal time scales because of a common structure in the tropical tropospheric temperature response that is upward amplified and meridionally broad.

scholarly journals Quantifying the impact of early 21st century volcanic eruptions on global-mean surface temperature

2017 ◽  
Vol 12 (5) ◽  
pp. 054010 ◽  
Author(s):  
Paul-Arthur Monerie ◽  
Marie-Pierre Moine ◽  
Laurent Terray ◽  
Sophie Valcke
Keyword(s):  
Surface Temperature ◽  
21St Century ◽  
Volcanic Eruptions ◽  
Early 21St Century ◽  
Global Mean Surface Temperature ◽  
The Impact ◽  
Global Mean

scholarly journals Towards Reliable Probabilistic Time-Series Projections of Global Mean Surface Temperature

2021 ◽  
Author(s):  
Philip G. Sansom ◽  
Donald Cummins ◽  
Stefan Siegert ◽  
David B Stephenson
Keyword(s):  
Time Series ◽  
Global Warming ◽  
Surface Temperature ◽  
Climate Model ◽  
Future Projections ◽  
Perfect Model ◽  
Global Mean Surface Temperature ◽  
Time Series Approach ◽  
Energy Balance Models ◽  
Global Mean

Abstract Quantifying the risk of global warming exceeding critical targets such as 2.0 ◦ C requires reliable projections of uncertainty as well as best estimates of Global Mean Surface Temperature (GMST). However, uncertainty bands on GMST projections are often calculated heuristically and have several potential shortcomings. In particular, the uncertainty bands shown in IPCC plume projections of GMST are based on the distribution of GMST anomalies from climate model runs and so are strongly determined by model characteristics with little influence from observations of the real-world. Physically motivated time-series approaches are proposed based on fitting energy balance models (EBMs) to climate model outputs and observations in order to constrain future projections. It is shown that EBMs fitted to one forcing scenario will not produce reliable projections when different forcing scenarios are applied. The errors in the EBM projections can be interpreted as arising due to a discrepancy in the effective forcing felt by the model. A simple time-series approach to correcting the projections is proposed based on learning the evolution of the forcing discrepancy so that it can be projected into the future. This approach gives reliable projections of GMST when tested in a perfect model setting. When applied to observations this leads to projected warming of 2.2 ◦ C (1.7 ◦ C to 2.9 ◦ C) in 2100 compared to pre-industrial conditions, 0.4 ◦ C lower than a comparable IPCC anomaly estimate. The probability of staying below the critical 2.0 ◦ C warming target in 2100 more than doubles to 0.28 compared to only 0.11 from a comparably IPCC estimate.

scholarly journals Surface temperature response to the major volcanic eruptions in multiple reanalysis data sets

2019 ◽  
Author(s):  
Masatomo Fujiwara ◽  
Patrick Martineau ◽  
Jonathon S. Wright
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Volcanic Eruptions ◽  
Reanalysis Data ◽  
Data Sets ◽  
Hemispheric Differences ◽  
Quasi Biennial Oscillation ◽  
Cooling Period ◽  
El Chichón ◽  
El Chichon

Abstract. The global response of air temperature at 2 metre above the surface to the eruptions of Mount Agung in March 1963, El Chichón in April 1982, and Mount Pinatubo in June 1991 is investigated using 11 global atmospheric reanalysis data sets (JRA-55, JRA-25, MERRA-2, MERRA, ERA-Interim, ERA-40, CFSR, NCEP-NCAR R-1, 20CR version 2c, ERA-20C, and CERA-20C). Multiple linear regression (MLR) is applied to the monthly mean time series of temperature for two periods, 1980–2010 (for 10 reanalyses) and 1958–2001 (for six reanalyses), by considering explanatory factors of seasonal harmonics, linear trends, Quasi-Biennial Oscillation (QBO), solar cycle, tropical sea surface temperature (SST) variations in the Pacific, Indian, and Atlantic Oceans, and Arctic SST variations. Empirical orthogonal function (EOF) analysis is applied to these climatic indices to obtain a set of orthogonal indices to be used for the MLR. The residuals of the MLR are used to define the volcanic signals for the three eruptions separately. First, latitudinally averaged time series of the residuals are investigated and compared with the results from previous studies. Then, the geographical distribution of the response during the peak cooling period after each eruption is investigated. In general, different reanalyses show similar geographical patterns of the response, but with the largest differences in the polar regions. The Pinatubo response shows largest average cooling in the 60° N–60° S region among the three eruptions, with a peak cooling of 0.10–0.15 K. The El Chichón response shows slightly larger cooling in the NH than in the Southern Hemisphere (SH), while the Agung response shows larger cooling in the SH. These hemispheric differences are consistent with the distribution of stratospheric aerosol optical depth after these eruptions; however, the peak cooling after these two eruptions is comparable in magnitude to unexplained cooling events in other periods without volcanic influence. Other methods in which the MLR model is used with different sets of indices are also tested, and it is found that careful treatment of tropical SST variability is necessary to evaluate the surface response to volcanic eruptions in observations and reanalyses.

scholarly journals Surface temperature response to the major volcanic eruptions in multiple reanalysis data sets

2020 ◽  
Vol 20 (1) ◽  
pp. 345-374
Author(s):  
Masatomo Fujiwara ◽  
Patrick Martineau ◽  
Jonathon S. Wright
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Volcanic Eruptions ◽  
Reanalysis Data ◽  
Data Sets ◽  
Hemispheric Differences ◽  
Quasi Biennial Oscillation ◽  
Cooling Period ◽  
El Chichón ◽  
El Chichon

Abstract. The global response of air temperature at 2 m above the surface to the eruptions of Mount Agung in March 1963, El Chichón in April 1982, and Mount Pinatubo in June 1991 is investigated using 11 global atmospheric reanalysis data sets (JRA-55, JRA-25, MERRA-2, MERRA, ERA-Interim, ERA-40, CFSR, NCEP-NCAR R-1, 20CR version 2c, ERA-20C, and CERA-20C). Multiple linear regression (MLR) is applied to the monthly mean time series of temperature for two periods – 1980–2010 (for 10 reanalyses) and 1958–2001 (for 6 reanalyses) – by considering explanatory factors of seasonal harmonics, linear trends, quasi-biennial oscillation (QBO), solar cycle, tropical sea surface temperature (SST) variations in the Pacific, Indian, and Atlantic Oceans, and Arctic SST variations. Empirical orthogonal function (EOF) analysis is applied to these climatic indices to obtain a set of orthogonal indices to be used for the MLR. The residuals of the MLR are used to define the volcanic signals for the three eruptions separately. First, area-averaged time series of the residuals are investigated and compared with the results from previous studies. Then, the geographical distribution of the response during the peak cooling period after each eruption is investigated. In general, different reanalyses show similar geographical patterns of the response, but with the largest differences in the polar regions. The Pinatubo response shows the largest average cooling in the 60∘ N–60∘ S region among the three eruptions, with a peak cooling of 0.10–0.15 K. The El Chichón response shows slightly larger cooling in the NH than in the Southern Hemisphere (SH), while the Agung response shows larger cooling in the SH. These hemispheric differences are consistent with the distribution of stratospheric aerosol optical depth after these eruptions; however, the peak cooling after these two eruptions is comparable in magnitude to unexplained cooling events in other periods without volcanic influence. Other methods in which the MLR model is used with different sets of indices are also tested, and it is found that careful treatment of tropical SST variability is necessary to evaluate the surface response to volcanic eruptions in observations and reanalyses.

scholarly journals Global Hydrological Cycle Response to Rapid and Slow Global Warming

2013 ◽  
Vol 26 (22) ◽  
pp. 8781-8786 ◽  
Author(s):  
Larissa Back ◽  
Karen Russ ◽  
Zhengyu Liu ◽  
Kuniaki Inoue ◽  
Jiaxu Zhang ◽  
...  
Keyword(s):  
Global Warming ◽  
Water Vapor ◽  
Surface Temperature ◽  
Global Surface Temperature ◽  
Rate Of Increase ◽  
The Tropics ◽  
Precipitation Changes ◽  
Global Surface ◽  
Global Mean ◽  
Global Water

Abstract This study analyzes the response of global water vapor to global warming in a series of fully coupled climate model simulations. The authors find that a roughly 7% K−1 rate of increase of water vapor with global surface temperature is robust only for rapid anthropogenic-like climate change. For slower warming that occurred naturally in the past, the Southern Ocean has time to equilibrate, producing a different pattern of surface warming, so that water vapor increases at only 4.2% K−1. This lower rate of increase of water vapor with warming is not due to relative humidity changes or differences in mean lower-tropospheric temperature. A temperature of over 80°C would be required in the Clausius–Clapeyron relationship to match the 4.2% K−1 rate of increase. Instead, the low rate of increase is due to spatially heterogeneous warming. During slower global warming, there is enhanced warming at southern high latitudes, and hence less warming in the tropics per kelvin of global surface temperature increase. This leads to a smaller global water vapor increase, because most of the atmospheric water vapor is in the tropics. A formula is proposed that applies to general warming scenarios. This study also examines the response of global-mean precipitation and the meridional profile of precipitation minus evaporation and compares the latter to thermodynamic scalings. It is found that global-mean precipitation changes are remarkably robust between rapid and slow warming. Thermodynamic scalings for the rapid- and slow-warming zonal-mean precipitation are similar, but the precipitation changes are significantly different, suggesting that circulation changes are important in driving these differences.

scholarly journals Analysis of Climate Change Effects on Surface Temperature in Central-Italy Lakes Using Satellite Data Time-Series

2021 ◽  
Vol 14 (1) ◽  
pp. 117
Author(s):  
Davide De Santis ◽  
Fabio Del Frate ◽  
Giovanni Schiavon
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Surface Temperature ◽  
Satellite Data ◽  
Water Surface ◽  
Central Italy ◽  
Large Lakes ◽  
Climate Change Effects ◽  
Surface Temperatures ◽  
The Impact

Evaluation of the impact of climate change on water bodies has been one of the most discussed open issues of recent years. The exploitation of satellite data for the monitoring of water surface temperatures, combined with ground measurements where available, has already been shown in several previous studies, but these studies mainly focused on large lakes around the world. In this work the water surface temperature characterization during the last few decades of two small–medium Italian lakes, Lake Bracciano and Lake Martignano, using satellite data is addressed. The study also takes advantage of the last space-borne platforms, such as Sentinel-3. Long time series of clear sky conditions and atmospherically calibrated (using a simplified Planck’s Law-based algorithm) images were processed in order to derive the lakes surface temperature trends from 1984 to 2019. The results show an overall increase in water surface temperatures which is more evident on the smallest and shallowest of the two test sites. In particular, it was observed that, since the year 2000, the surface temperature of both lakes has risen by about 0.106 °C/year on average, which doubles the rate that can be retrieved by considering the whole period 1984–2019 (0.053 °C/year on average).

scholarly journals The impact of volcanic eruptions of different magnitude on stratospheric water vapor in the tropics

2021 ◽  
Vol 21 (8) ◽  
pp. 6565-6591
Author(s):  
Clarissa Alicia Kroll ◽  
Sally Dacie ◽  
Alon Azoulay ◽  
Hauke Schmidt ◽  
Claudia Timmreck
Keyword(s):  
Water Vapor ◽  
Radiative Forcing ◽  
Volcanic Eruptions ◽  
Aerosol Layer ◽  
Power Functions ◽  
Max Planck ◽  
Point Temperature ◽  
Stratospheric Water Vapor ◽  
Cold Point ◽  
The Impact

Abstract. Increasing the temperature of the tropical cold-point region through heating by volcanic aerosols results in increases in the entry value of stratospheric water vapor (SWV) and subsequent changes in the atmospheric energy budget. We analyze tropical volcanic eruptions of different strengths with sulfur (S) injections ranging from 2.5 Tg S up to 40 Tg S using EVAens, the 100-member ensemble of the Max Planck Institute – Earth System Model in its low-resolution configuration (MPI-ESM-LR) with artificial volcanic forcing generated by the Easy Volcanic Aerosol (EVA) tool. Significant increases in SWV are found for the mean over all ensemble members from 2.5 Tg S onward ranging between [5, 160] %. However, for single ensemble members, the standard deviation between the control run members (0 Tg S) is larger than SWV increase of single ensemble members for eruption strengths up to 20 Tg S. A historical simulation using observation-based forcing files of the Mt. Pinatubo eruption, which was estimated to have emitted (7.5±2.5) Tg S, returns SWV increases slightly higher than the 10 Tg S EVAens simulations due to differences in the aerosol profile shape. An additional amplification of the tape recorder signal is also apparent, which is not present in the 10 Tg S run. These differences underline that it is not only the eruption volume but also the aerosol layer shape and location with respect to the cold point that have to be considered for post-eruption SWV increases. The additional tropical clear-sky SWV forcing for the different eruption strengths amounts to [0.02, 0.65] W m−2, ranging between [2.5, 4] % of the aerosol radiative forcing in the 10 Tg S scenario. The monthly cold-point temperature increases leading to the SWV increase are not linear with respect to aerosol optical depth (AOD) nor is the corresponding SWV forcing, among others, due to hysteresis effects, seasonal dependencies, aerosol profile heights and feedbacks. However, knowledge of the cold-point temperature increase allows for an estimation of SWV increases of 12 % per Kelvin increase in mean cold-point temperature. For yearly averages, power functions are fitted to the cold-point warming and SWV forcing with increasing AOD.

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