scholarly journals Spatial and temporal variability of the hydroxyl radical: Understanding the role of large-scale climate features and their influence on OH through its dynamical and photochemical drivers

2020 ◽  
Author(s):  
Daniel C. Anderson ◽  
Bryan N. Duncan ◽  
Arlene M. Fiore ◽  
Colleen B. Baublitz ◽  
Melanie B. Follette-Cook ◽  
...  
Keyword(s):  
Water Vapor ◽  
Climate Variability ◽  
Hydroxyl Radical ◽  
Southern Oscillation ◽  
Satellite Observations ◽  
Spatial And Temporal Variability ◽  
Upper Troposphere ◽  
Modes Of Variability ◽  
The Relationship ◽  
Modes Of Climate Variability

Abstract. The hydroxyl radical (OH) is the primary atmospheric oxidant, responsible for removing many important trace gases, including methane, from the atmosphere. Although robust relationships between OH drivers and modes of climate variability have been shown, the underlying mechanisms between OH and these climate modes, such as the El Niño Southern Oscillation (ENSO), have not been thoroughly investigated. Here, we use a chemical transport model to perform a 38-year simulation of atmospheric chemistry, in conjunction with satellite observations, to understand the relationship between tropospheric OH and ENSO, Northern Hemispheric modes of variability, the Indian Ocean Dipole, and monsoons. Empirical orthogonal function (EOF) and regression analyses show that ENSO is the dominant mode of global OH variability in the tropospheric column and upper troposphere, responsible for approximately 30 % of the total variance in boreal winter. Reductions in OH due to ENSO are centered over the tropical Pacific and Australia and can be as high as 10–15 % in the tropospheric column. The relationship between ENSO and OH is driven by changes in nitrogen oxides in the upper troposphere and changes in water vapor and O1D in the lower troposphere. While the spatial scale of the relationship between monsoons, other modes of variability, and OH are much smaller than ENSO, local changes in OH can be significantly larger than those caused by ENSO. These relationships also occur in multiple models that participated in the Chemistry Climate Model Initiative (CCMI), suggesting that the dependence of OH interannual variability on these well-known modes of climate variability is robust. Finally, modeled relationships between ENSO and OH drivers – such as carbon monoxide, water vapor, and lightning – closely agree with satellite observations. The ability of satellite products to capture the relationship between OH drivers and ENSO provides an avenue to an indirect OH observation strategy and new constraints on OH variability.

scholarly journals Spatial and temporal variability in the hydroxyl (OH) radical: understanding the role of large-scale climate features and their influence on OH through its dynamical and photochemical drivers

2021 ◽  
Vol 21 (8) ◽  
pp. 6481-6508
Author(s):  
Daniel C. Anderson ◽  
Bryan N. Duncan ◽  
Arlene M. Fiore ◽  
Colleen B. Baublitz ◽  
Melanie B. Follette-Cook ◽  
...  
Keyword(s):  
Water Vapor ◽  
Climate Variability ◽  
El Niño ◽  
El Nino ◽  
Satellite Observations ◽  
Spatial And Temporal Variability ◽  
Upper Troposphere ◽  
Modes Of Variability ◽  
The Relationship ◽  
Modes Of Climate Variability

Abstract. The hydroxyl radical (OH) is the primary atmospheric oxidant responsible for removing many important trace gases, including methane, from the atmosphere. Although robust relationships between OH drivers and modes of climate variability have been shown, the underlying mechanisms between OH and these climate modes, such as the El Niño–Southern Oscillation (ENSO), have not been thoroughly investigated. Here, we use a chemical transport model to perform a 38 year simulation of atmospheric chemistry, in conjunction with satellite observations, to understand the relationship between tropospheric OH and ENSO, Northern Hemispheric modes of variability, the Indian Ocean Dipole, and monsoons. Empirical orthogonal function (EOF) and regression analyses show that ENSO is the dominant mode of global OH variability in the tropospheric column and upper troposphere, responsible for approximately 30 % of the total variance in boreal winter. Reductions in OH due to El Niño are centered over the tropical Pacific and Australia and can be as high as 10 %–15 % in the tropospheric column. The relationship between ENSO and OH is driven by changes in nitrogen oxides in the upper troposphere and changes in water vapor and O1D in the lower troposphere. While the correlations between monsoons or other modes of variability and OH span smaller spatial scales than for ENSO, regional changes in OH can be significantly larger than those caused by ENSO. Similar relationships occur in multiple models that participated in the Chemistry–Climate Model Initiative (CCMI), suggesting that the dependence of OH interannual variability on these well-known modes of climate variability is robust. Finally, the spatial pattern and r2 values of correlation between ENSO and modeled OH drivers – such as carbon monoxide, water vapor, lightning, and, to a lesser extent, NO2 – closely agree with satellite observations. The ability of satellite products to capture the relationship between OH drivers and ENSO provides an avenue to an indirect OH observation strategy and new constraints on OH variability.

scholarly journals Influence of Modes of Climate Variability on Global Temperature Extremes

2008 ◽  
Vol 21 (15) ◽  
pp. 3872-3889 ◽  
Author(s):  
Jesse Kenyon ◽  
Gabriele C. Hegerl
Keyword(s):  
North America ◽  
Climate Variability ◽  
Large Scale ◽  
Southern Oscillation ◽  
Temperature Extremes ◽  
Modes Of Variability ◽  
The North ◽  
The Pacific ◽  
The North Atlantic Oscillation ◽  
Modes Of Climate Variability

Abstract The influence of large-scale modes of climate variability on worldwide summer and winter temperature extremes has been analyzed, namely, that of the El Niño–Southern Oscillation, the North Atlantic Oscillation, and Pacific interdecadal climate variability. Monthly indexes for temperature extremes from worldwide land areas are used describe moderate extremes, such as the number of exceedences of the 90th and 10th climatological percentiles, and more extreme events such as the annual, most extreme temperature. This study examines which extremes show a statistically significant (5%) difference between the positive and negative phases of a circulation regime. Results show that temperature extremes are substantially affected by large-scale circulation patterns, and they show distinct regional patterns of response to modes of climate variability. The effects of the El Niño–Southern Oscillation are seen throughout the world but most clearly around the Pacific Rim and throughout all of North America. Likewise, the influence of Pacific interdecadal variability is strongest in the Northern Hemisphere, especially around the Pacific region and North America, but it extends to the Southern Hemisphere. The North Atlantic Oscillation has a strong continent-wide effect for Eurasia, with a clear but weaker effect over North America. Modes of variability influence the shape of the daily temperature distribution beyond a simple shift, often affecting cold and warm extremes and sometimes daytime and nighttime temperatures differently. Therefore, for reliable attribution of changes in extremes as well as prediction of future changes, changes in modes of variability need to be accounted for.

scholarly journals Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

2021 ◽  
Author(s):  
Mark D. Risser ◽  
Michael F. Wehner ◽  
John P. O’Brien ◽  
Christina M. Patricola ◽  
Travis A. O’Brien ◽  
...  
Keyword(s):  
Climate Variability ◽  
Extreme Precipitation ◽  
Southern Oscillation ◽  
Statistical Significance ◽  
In Situ Measurements ◽  
Climate Indices ◽  
Natural Climate Variability ◽  
Modes Of Variability ◽  
Natural Climate

AbstractWhile various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

scholarly journals Effect of tropical cyclones on the Stratosphere-Troposphere Exchange observed using satellite observations over north Indian Ocean

2016 ◽  
Author(s):  
M. Venkat Ratnam ◽  
S. Ravindra Babu ◽  
S. S. Das ◽  
Ghouse Basha ◽  
B. V. Krishnamurthy ◽  
...  
Keyword(s):  
Water Vapor ◽  
Indian Ocean ◽  
Tropical Cyclones ◽  
Lower Stratosphere ◽  
North Indian Ocean ◽  
Satellite Observations ◽  
Upper Troposphere ◽  
North West ◽  
The North ◽  
The Impact

Abstract. Tropical cyclones play an important role in modifying the tropopause structure and dynamics as well as stratosphere-troposphere exchange (STE) process in the Upper Troposphere and Lower Stratosphere (UTLS) region. In the present study, the impact of cyclones that occurred over the North Indian Ocean during 2007–2013 on the STE process is quantified using satellite observations. Tropopause characteristics during cyclones are obtained from the Global Positioning System (GPS) Radio Occultation (RO) measurements and ozone and water vapor concentrations in UTLS region are obtained from Aura-Microwave Limb Sounder (MLS) satellite observations. The effect of cyclones on the tropopause parameters is observed to be more prominent within 500 km from the centre of cyclone. In our earlier study we have observed decrease (increase) in the tropopause altitude (temperature) up to 0.6 km (3 K) and the convective outflow level increased up to 2 km. This change leads to a total increase in the tropical tropopause layer (TTL) thickness of 3 km within the 500 km from the centre of cyclone. Interestingly, an enhancement in the ozone mixing ratio in the upper troposphere is clearly noticed within 500 km from cyclone centre whereas the enhancement in the water vapor in the lower stratosphere is more significant on south-east side extending from 500–1000 km away from the cyclone centre. We estimated the cross-tropopause mass flux for different intensities of cyclones and found that the mean flux from stratosphere to troposphere for cyclonic stroms is 0.05 ± 0.29 × 10−3 kg m−2 and for very severe cyclonic stroms it is 0.5 ± 1.07 × 10−3 kg m−2. More downward flux is noticed in the north-west and south-west side of the cyclone centre. These results indicate that the cyclones have significant impact in effecting the tropopause structure, ozone and water vapour budget and consequentially the STE in the UTLS region.

scholarly journals Interannual variations of water vapor in the tropical upper troposphere and the lower and middle stratosphere and their connections to ENSO and QBO

2019 ◽  
Vol 19 (15) ◽  
pp. 9913-9926 ◽  
Author(s):  
Edward W. Tian ◽  
Hui Su ◽  
Baijun Tian ◽  
Jonathan H. Jiang
Keyword(s):  
Water Vapor ◽  
Southern Oscillation ◽  
Phase Lag ◽  
Interannual Variations ◽  
Quasi Biennial Oscillation ◽  
Upper Troposphere ◽  
Tropical Water ◽  
Enso Phases ◽  
Middle Stratosphere ◽  
Tropical Upper Troposphere

Abstract. In this study, we analyze the Aura Microwave Limb Sounder water vapor data in the tropical upper troposphere and the lower and middle stratosphere (UTLMS) (from 215 to 6 hPa) for the period from August 2004 to September 2017 using time-lag regression analysis and composite analysis to explore the interannual variations of tropical UTLMS water vapor and their connections to El Niño–Southern Oscillation (ENSO) and quasi-biennial oscillation (QBO). Our analysis shows that the interannual tropical UTLMS water vapor anomalies are strongly related to ENSO and QBO which together can explain more than half (∼ 50 %–60 %) but not all variance of the interannual tropical water vapor anomalies. We find that ENSO's impact is strong in the upper troposphere (∼ 215–∼ 120 hPa) and near the tropopause (∼ 110–∼ 90 hPa), with a ∼ 3-month lag but weak in the lower and middle stratosphere (∼ 80 to ∼ 6 hPa). In contrast, QBO's role is large in the lower and middle stratosphere, with an upward-propagating signal starting at the tropopause (100 hPa) with a ∼ 2-month lag, peaking in the middle stratosphere near 15 hPa with a ∼ 21-month lag. The phase lag is based on the 50 hPa QBO index used by many previous studies. This observational evidence supports that the QBO's impact on the tropical stratospheric water vapor is from its modulation on the tropical tropopause temperature and then transported upward with the tape recorder as suggested by many previous studies. In the upper troposphere, ENSO is more important than QBO for the interannual tropical water vapor anomalies that are positive during the warm ENSO phases but negative during the cold ENSO phases. Near the tropopause, both ENSO and QBO are important for the interannual tropical water vapor anomalies. Warm ENSO phase and westerly QBO phase tend to cause positive water vapor anomalies, while cold ENSO phase and easterly QBO phase tend to cause negative water vapor anomalies. As a result, the interannual tropical water vapor anomalies near the tropopause are different depending on different ENSO and QBO phase combinations. In the lower and middle stratosphere, QBO is more important than ENSO for the interannual tropical water vapor anomalies. For the westerly QBO phases, interannual tropical water vapor anomalies are positive near the tropopause and in the lower stratosphere but negative in the middle stratosphere and positive again above. Vice versa for the easterly QBO phases.

scholarly journals Evaluation of Leading Modes of Climate Variability in the CMIP Archives

2020 ◽  
Vol 33 (13) ◽  
pp. 5527-5545 ◽  
Author(s):  
John T. Fasullo ◽  
A. S. Phillips ◽  
C. Deser
Keyword(s):  
Climate Variability ◽  
Southern Oscillation ◽  
Internal Variability ◽  
Intrinsic Variability ◽  
Annular Modes ◽  
Internal Climate Variability ◽  
The North ◽  
The Pacific ◽  
The North Atlantic Oscillation ◽  
Modes Of Climate Variability

AbstractThe adequate simulation of internal climate variability is key for our understanding of climate as it underpins efforts to attribute historical events, predict on seasonal and decadal time scales, and isolate the effects of climate change. Here the skill of models in reproducing observed modes of climate variability is assessed, both across and within the CMIP3, CMIP5, and CMIP6 archives, in order to document model capabilities, progress across ensembles, and persisting biases. A focus is given to the well-observed tropical and extratropical modes that exhibit small intrinsic variability relative to model structural uncertainty. These include El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), the North Atlantic Oscillation (NAO), and the northern and southern annular modes (NAM and SAM). Significant improvements are identified in models’ representation of many modes. Canonical biases, which involve both amplitudes and patterns, are generally reduced across model generations. For example, biases in ENSO-related equatorial Pacific sea surface temperature, which extend too far westward, and associated atmospheric teleconnections, which are too weak, are reduced. Stronger tropical expression of the PDO in successive CMIP generations has characterized their improvement, with some CMIP6 models generating patterns that lie within the range of observed estimates. For the NAO, NAM, and SAM, pattern correlations with observations are generally higher than for other modes and slight improvements are identified across successive model generations. For ENSO and PDO spectra and extratropical modes, changes are small compared to internal variability, precluding definitive statements regarding improvement.

scholarly journals Validation of COSMIC water vapor data in the upper troposphere and lower stratosphere using MLS, MERRA and ERA-Interim

2016 ◽  
Author(s):  
Ming Shangguan ◽  
Katja Matthes ◽  
Wuke Wang ◽  
Tae-Kwon Wee
Keyword(s):  
Water Vapor ◽  
Seasonal Cycle ◽  
Lower Stratosphere ◽  
Southern Oscillation ◽  
Weather Forecast ◽  
Cosmic Radio ◽  
Quasi Biennial Oscillation ◽  
Medium Range Weather Forecast ◽  
Upper Troposphere ◽  
The Antarctic

Abstract. Water vapor is the most important greenhouse gas in the atmosphere with important implications not only for the Earth’s radiation and energy budget but also for various chemical, physical and dynamical processes in the stratosphere. The Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) Radio Occultation (RO) dataset from 2007 through 2013 is used for the first time to study the distribution and variability water vapor in the upper troposphere and lower stratosphere (UTLS). The COSMIC data are compared to the Microwave Limb Sounder (MLS) data, and to two global reanalyses: The Modern-Era Retrospective analysis for Research and Application (MERRA) of the National Aeronautics and Space Administration (NASA); and, the latest reanalysis of the European Center for Medium-range Weather Forecast (ECMWF), the ERA-Interim. The MLS data have been assimilated into the MERRA, whereas the COSMIC data are used for the ERA-Interim. As a result, the MERRA agrees well with the MLS data and so does the ERA-Interim with the COSMIC data. While the monthly zonal mean distributions of water vapor from the four datasets show good agreements in northern mid-latitudes, large discrepancies exist in high southern latitudes and tropics. The MERRA shows overall a consistent seasonal cycle with MLS, but has too strong winter dehydration over the Antarctic, and is very weak in the interannual variations. The ERA-Interim fails to properly represent the winter dehydration over the Antarctic, and shows an unrealistic seasonal cycle in the tropical upper troposphere. The COSMIC data shows a good agreement with the MLS data except for the tropical "taper recorder" signal, where the COSMIC data suggest a faster upward motion than the MLS data. The COSMIC data are able to represent the moisture variabilities associated with the Quasi-Biennial Oscillation and the El Niño-Southern Oscillation.

scholarly journals Multichannel Empirical Orthogonal Teleconnection Analysis: A Method for Space–Time Decomposition of Climate Variability

2017 ◽  
Vol 56 (7) ◽  
pp. 1897-1919
Author(s):  
Benoit Parmentier ◽  
Neeti Neeti ◽  
Elsa Nickl ◽  
Marco Millones
Keyword(s):  
Climate Variability ◽  
Southern Oscillation ◽  
Global Climate ◽  
Singular Spectrum Analysis ◽  
Space Time ◽  
Climate Impacts ◽  
Simple Extension ◽  
Quasi Biennial Oscillation ◽  
Modes Of Variability ◽  
Climate Event

AbstractWith the increasing availability of Earth observation datasets, developing methods for the identification of modes of variability is becoming crucial in Earth system science. These modes, also referred as teleconnections, are useful to understand the global climate system and to predict short-term climate and climate variability. For example, the El Niño–Southern Oscillation (ENSO) phenomenon, a teleconnection with global climate impacts, has been associated with major social, economic, and ecological consequences. In this study, a novel procedure called multichannel empirical orthogonal teleconnection (MEOT) analysis is introduced as a simple extension of the logic of empirical orthogonal teleconnections to uncover the temporal evolution of recurrent space–time patterns. A global monthly sea surface temperature dataset (1982–2007 time series) is used to explore the MEOT method and its differences and similarities with the multichannel singular spectrum analysis (MSSA). Both methods are applied with a 13-month embedding dimension to extract spatiotemporal patterns that exhibit clear basis vectors in quadrature. MSSA extracted four quadratures, and MEOT extracted three. Findings show that MEOT quadratures are more easily related to climate events corresponding to ENSO, South Atlantic Ocean dipole, and Atlantic meridional mode. MSSA identified one quadrature related to ENSO and one related to the quasi-biennial oscillation. The two remaining MSSA quadratures are mixtures of different indices rather than one climate event. Thus, results indicate that, since it does not suffer from a biorthogonality constraint, MEOT is effective at extracting modes of variability in climate datasets, suggesting its potential use in climate research.

Introductory Overview

2003 ◽  
Author(s):  
Douglas G. Goodin
Keyword(s):  
Time Series ◽  
Power Spectrum ◽  
Climate Variability ◽  
Spectrum Analysis ◽  
North American ◽  
Southern Oscillation ◽  
Power Spectrum Analysis ◽  
Teleconnection Patterns ◽  
Modes Of Variability ◽  
Scale Fluctuation

Timescale is the organizing framework of this volume. In various sections, we consider the effects of climate variability on ecosystems at timescales ranging from weeks or months to centuries. In part III, we turn our attention to interdecadal-scale events. The timescales we consider are not absolutely defined, but for our purposes we define the interdecadal scale to encompass effects occurring with recurring cycles generally ranging from 10 to 50 years. A recurring theme in many of the chapters in this section is the effect on ecosystem response of teleconnection patterns associated with recognized quasi-periodic atmospheric circulation modes. These circulation modes include the well-known El Niño– Southern Oscillation (ENSO) phenomenon, which is generally thought to recur at shorter, interdecadal timescales but also includes some longer-term periodicities. Several other climate variability modes, including the Pacific North American index (PNA), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), and North Pacific index (NP) also show strong interdecadal scale signatures and figure prominently in the chapters of part III. McHugh and Goodin begin the section by examining the climate record at several North American LTER sites for evidence of interdecadal-scale fluctuation. They note that interdecadal-scale contributions to climate variability can best be described in terms of two types of variation: (1) discontinuities in mean value, and (2) the presence of trends in the data. Evaluation of interdecadal periodicities in LTER data is complicated by the relatively short time series of observations available. McHugh and Goodin approach the problem mainly through the use of power spectrum analysis, a widely used tool for evaluating the periodicity in a time series of data. Principal components analysis is used to decompose the time series of growing-season climate data for each of the LTER sites into their principal modes of variability. These modes are then subjected to power spectrum analysis to evaluate the proportions of the variance in the data occurring at various timescales. McHugh and Goodin’s results suggest that significant effects on precipitation and temperature at interdecadal timescales are uncommon in these data, although significant periodicities at both shorter and longer frequencies do emerge from the data (a finding of relevance to other sections of this volume).

scholarly journals Synchronous crop failures and climate-forced production variability

2019 ◽  
Vol 5 (7) ◽  
pp. eaaw1976 ◽  
Author(s):  
W. B. Anderson ◽  
R. Seager ◽  
W. Baethgen ◽  
M. Cane ◽  
L. You
Keyword(s):  
Climate Variability ◽  
Crop Production ◽  
Large Scale ◽  
Southern Oscillation ◽  
Global Scale ◽  
Historical Record ◽  
Crop Failure ◽  
Wheat Production ◽  
Production Variability ◽  
Modes Of Climate Variability

Large-scale modes of climate variability can force widespread crop yield anomalies and are therefore often presented as a risk to food security. We quantify how modes of climate variability contribute to crop production variance. We find that the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), tropical Atlantic variability (TAV), and the North Atlantic Oscillation (NAO) together account for 18, 7, and 6% of globally aggregated maize, soybean, and wheat production variability, respectively. The lower fractions of global-scale soybean and wheat production variability result from substantial but offsetting climate-forced production anomalies. All climate modes are important in at least one region studied. In 1983, ENSO, the only mode capable of forcing globally synchronous crop failures, was responsible for the largest synchronous crop failure in the modern historical record. Our results provide the basis for monitoring, and potentially predicting, simultaneous crop failures.

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