Author
Kaustubh Thirumalai
Other affiliations: Brown University, University of Texas at Austin
Bio: Kaustubh Thirumalai is an academic researcher from University of Arizona. The author has contributed to research in topics: Monsoon & Holocene. The author has an hindex of 17, co-authored 57 publications receiving 1148 citations. Previous affiliations of Kaustubh Thirumalai include Brown University & University of Texas at Austin.
Topics: Monsoon, Holocene, Geology, Glacial period, Climate change
Papers
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University of Southern California1, Northern Arizona University2, MathWorks3, University of Arizona4, Australian National University5, United States Geological Survey6, University of Tasmania7, Australian Antarctic Division8, University of Maryland, College Park9, University of Melbourne10, University of Cambridge11, Spanish National Research Council12, University of Wollongong13, University of Bern14, Ca' Foscari University of Venice15, University of Texas at Austin16, University of Bergen17, Chinese Academy of Sciences18, Norwegian Polar Institute19, National University of Cuyo20, University of Washington21, University of Adelaide22, Victoria University of Wellington23, Swiss Federal Institute for Forest, Snow and Landscape Research24, University of Montpellier25, National Taiwan Ocean University26, Columbia University27, Louisiana State University28, University of Maine29, Saint Petersburg State University30, Arctic and Antarctic Research Institute31, Northumbria University32, Lund University33, Institut national de la recherche scientifique34, Nepal Academy of Science and Technology35, Tribhuvan University36, University of Ottawa37, Université catholique de Louvain38, Hirosaki University39, University of Gothenburg40, Xiamen University41, Japan Agency for Marine-Earth Science and Technology42, National Institute of Polar Research43, Aix-Marseille University44, National Institute of Water and Atmospheric Research45, Russian Academy of Sciences46, Autonomous University of Barcelona47, British Antarctic Survey48, University of Tübingen49, University of the Witwatersrand50, University of Brighton51, Alfred Wegener Institute for Polar and Marine Research52, Université Paris-Saclay53, Sukachev Institute of Forest54, University of Toronto55, University at Buffalo56, Australian Nuclear Science and Technology Organisation57, Aarhus University58, University of Florence59, Pierre-and-Marie-Curie University60, Paul Scherrer Institute61, University of Minnesota62, Concordia University63, University of Regina64, National Centre for Antarctic and Ocean Research65, University of New South Wales66, University of the Ryukyus67, National Oceanic and Atmospheric Administration68, University of Colorado Boulder69, Lehigh University70, Australian Institute of Marine Science71, Free University of Berlin72
TL;DR: A community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative, suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.
Abstract: Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850–2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.
260 citations
University of Arizona1, University of Michigan2, University of California, Davis3, Syracuse University4, University of Connecticut5, Queen Mary University of London6, Lamont–Doherty Earth Observatory7, Columbia University8, Stockholm University9, George Mason University10, Centre national de la recherche scientifique11, National Museum of Natural History12, University of California, Riverside13, University of Bristol14, Trinity College, Dublin15, University of Leeds16, National Center for Atmospheric Research17, Texas A&M University18
TL;DR: The recent advances in data collection, statistics, and modeling that might help to better understand how rising levels of atmospheric carbon dioxide will affect future climate are reviewed.
Abstract: As the world warms, there is a profound need to improve projections of climate change. Although the latest Earth system models offer an unprecedented number of features, fundamental uncertainties continue to cloud our view of the future. Past climates provide the only opportunity to observe how the Earth system responds to high carbon dioxide, underlining a fundamental role for paleoclimatology in constraining future climate change. Here, we review the relevancy of paleoclimate information for climate prediction and discuss the prospects for emerging methodologies to further insights gained from past climates. Advances in proxy methods and interpretations pave the way for the use of past climates for model evaluation—a practice that we argue should be widely adopted.
203 citations
University of Wollongong1, University of Maryland, College Park2, Université catholique de Louvain3, Aix-Marseille University4, Spanish National Research Council5, University of Cambridge6, United States Geological Survey7, Autonomous University of Barcelona8, Woods Hole Oceanographic Institution9, Aarhus University10, University of Paris11, University of New South Wales12, Xiamen University13, University of Texas at Austin14, Lund University15, Northumbria University16
TL;DR: In this article, a global ocean sea surface temperature (SST) synthesis (Ocean2k SST synthesis) spanning the Common Era is presented, which shows a cooling trend that is similar, within uncertainty, to that simulated by realistically forced climate models for the past millennium.
Abstract: Knowledge of natural climate variability is essential to better constrain the uncertainties in projections of twenty-first-century climate change 1–5. The past 2,000 years (2 kyr) have emerged as a critical interval in this endeavour, with sufficient length to characterize natural decadal-to-centennial scale change, known external climate forcings 6 and with distinctive patterns of spatiotemporal temperature variations 7. However, reconstructions for the full 2 kyr interval are not available for the global ocean, a primary heat reservoir 8 and an important regulator of global climate on longer timescales 9–11. Here we present a global ocean sea surface temperature (SST) synthesis (Ocean2k SST synthesis) spanning the Common Era, which shows a cooling trend that is similar, within uncertainty, to that simulated by realistically forced climate models for the past millennium. We use the simulations to identify the climate forcing(s) consistent with reconstructed SST variations during the past millennium. The oceans mediate the response of global climate to natural and anthropogenic forcings. Yet for the past 2,000 years — a key interval for understanding the present and future climate response to these forcings — global sea surface temperature changes and the underlying driving mechanisms are poorly constrained. Here we present a global synthesis of sea surface temperatures for the Common Era (ce) derived from 57 individual marine reconstructions that meet strict quality control criteria. We observe a cooling trend from 1 to 1800 ce that is robust against explicit tests for potential biases in the reconstructions. Between 801 and 1800 ce, the surface cooling trend is qualitatively consistent with an independent synthesis of terrestrial temperature reconstructions, and with a sea surface temperature composite derived from an ensemble of climate model simulations using best estimates of past external radiative forcings. Climate simulations using single and cumulative forcings suggest that the ocean surface cooling trend from 801 to 1800 ce is not primarily a response to orbital forcing but arises from a high frequency of explosive volcanism. Our results show that repeated clusters of volcanic eruptions can induce a net negative radiative forcing that results in a centennial and global scale cooling trend via a decline in mixed-layer oceanic heat content.
181 citations
TL;DR: A robust relationship between ENSO and southeast Asian SATs wherein virtually all April extremes occur during El Niño years is found, and global warming increases the likelihood of record-breaking April extremes.
Abstract: In April 2016, southeast Asia experienced surface air temperatures (SATs) that surpassed national records, exacerbated energy consumption, disrupted agriculture and caused severe human discomfort. Here we show using observations and an ensemble of global warming simulations the combined impact of the El Nino/Southern Oscillation (ENSO) phenomenon and long-term warming on regional SAT extremes. We find a robust relationship between ENSO and southeast Asian SATs wherein virtually all April extremes occur during El Nino years. We then quantify the relative contributions of long-term warming and the 2015-16 El Nino to the extreme April 2016 SATs. The results indicate that global warming increases the likelihood of record-breaking April extremes where we estimate that 29% of the 2016 anomaly was caused by warming and 49% by El Nino. These post-Nino Aprils can potentially be anticipated a few months in advance, and thus, help societies prepare for the projected continued increases in extremes.
152 citations
TL;DR: The Climate Data Toolbox for MATLAB aims to reduce time spent writing low‐level code, let researchers focus on physics rather than coding and encourage more efficacious code sharing.
Abstract: Climate science is highly interdisciplinary by nature, so understanding interactions between Earth processes inherently warrants the use of analytical software that can operate across the disciplines of Earth science. Toward this end, we present the Climate Data Toolbox for MATLAB, which contains more than 100 functions that span the major climate-related disciplines of Earth science. The toolbox enables streamlined, entirely scriptable workflows that are intuitive to write and easy to share. Included are functions to evaluate uncertainty, perform matrix operations, calculate climate indices, and generate common data displays. Documentation is presented pedagogically, with thorough explanations of how each function works and tutorials showing how the toolbox can be used to replicate results of published studies. As a well-tested, well-documented platform for interdisciplinary collaborations, the Climate Data Toolbox for MATLAB aims to reduce time spent writing low-level code, let researchers focus on physics rather than coding and encourage more efficacious code sharing.
113 citations
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01 Jan 1980
TL;DR: In this article, the influence of diet on the distribution of nitrogen isotopes in animals was investigated by analyzing animals grown in the laboratory on diets of constant nitrogen isotopic composition and found that the variability of the relationship between the δ^(15)N values of animals and their diets is greater for different individuals raised on the same diet than for the same species raised on different diets.
Abstract: The influence of diet on the distribution of nitrogen isotopes in animals was investigated by analyzing animals grown in the laboratory on diets of constant nitrogen isotopic composition.
The isotopic composition of the nitrogen in an animal reflects the nitrogen isotopic composition of its diet. The δ^(15)N values of the whole bodies of animals are usually more positive than those of their diets. Different individuals of a species raised on the same diet can have significantly different δ^(15)N values. The variability of the relationship between the δ^(15)N values of animals and their diets is greater for different species raised on the same diet than for the same species raised on different diets. Different tissues of mice are also enriched in ^(15)N relative to the diet, with the difference between the δ^(15)N values of a tissue and the diet depending on both the kind of tissue and the diet involved. The δ^(15)N values of collagen and chitin, biochemical components that are often preserved in fossil animal remains, are also related to the δ^(15)N value of the diet.
The dependence of the δ^(15)N values of whole animals and their tissues and biochemical components on the δ^(15)N value of diet indicates that the isotopic composition of animal nitrogen can be used to obtain information about an animal's diet if its potential food sources had different δ^(15)N values. The nitrogen isotopic method of dietary analysis probably can be used to estimate the relative use of legumes vs non-legumes or of aquatic vs terrestrial organisms as food sources for extant and fossil animals. However, the method probably will not be applicable in those modern ecosystems in which the use of chemical fertilizers has influenced the distribution of nitrogen isotopes in food sources.
The isotopic method of dietary analysis was used to reconstruct changes in the diet of the human population that occupied the Tehuacan Valley of Mexico over a 7000 yr span. Variations in the δ^(15)C and δ^(15)N values of bone collagen suggest that C_4 and/or CAM plants (presumably mostly corn) and legumes (presumably mostly beans) were introduced into the diet much earlier than suggested by conventional archaeological analysis.
5,548 citations
01 Apr 2013
TL;DR: In this article, the ability of CMIP3 and CMIP5 coupled ocean-atmosphere general circulation models (CGCMs) to simulate the tropical Pacific mean state and El Nino-Southern Oscillation (ENSO) was analyzed.
Abstract: We analyse the ability of CMIP3 and CMIP5 coupled ocean–atmosphere general circulation models (CGCMs) to simulate the tropical Pacific mean state and El Nino-Southern Oscillation (ENSO). The CMIP5 multi-model ensemble displays an encouraging 30 % reduction of the pervasive cold bias in the western Pacific, but no quantum leap in ENSO performance compared to CMIP3. CMIP3 and CMIP5 can thus be considered as one large ensemble (CMIP3 + CMIP5) for multi-model ENSO analysis. The too large diversity in CMIP3 ENSO amplitude is however reduced by a factor of two in CMIP5 and the ENSO life cycle (location of surface temperature anomalies, seasonal phase locking) is modestly improved. Other fundamental ENSO characteristics such as central Pacific precipitation anomalies however remain poorly represented. The sea surface temperature (SST)-latent heat flux feedback is slightly improved in the CMIP5 ensemble but the wind-SST feedback is still underestimated by 20–50 % and the shortwave-SST feedbacks remain underestimated by a factor of two. The improvement in ENSO amplitudes might therefore result from error compensations. The ability of CMIP models to simulate the SST-shortwave feedback, a major source of erroneous ENSO in CGCMs, is further detailed. In observations, this feedback is strongly nonlinear because the real atmosphere switches from subsident (positive feedback) to convective (negative feedback) regimes under the effect of seasonal and interannual variations. Only one-third of CMIP3 + CMIP5 models reproduce this regime shift, with the other models remaining locked in one of the two regimes. The modelled shortwave feedback nonlinearity increases with ENSO amplitude and the amplitude of this feedback in the spring strongly relates with the models ability to simulate ENSO phase locking. In a final stage, a subset of metrics is proposed in order to synthesize the ability of each CMIP3 and CMIP5 models to simulate ENSO main characteristics and key atmospheric feedbacks.
571 citations
Oeschger Centre for Climate Change Research1, Siberian Federal University2, Stockholm University3, Harvard University4, Princeton University5, Paul Scherrer Institute6, Max Planck Society7, University of Mainz8, University of Lausanne9, University UCINF10, University of Giessen11, ETH Zurich12, Sukachev Institute of Forest13
TL;DR: In this paper, the authors used tree-ring chronologies from the Russian Altai and European Alps to reconstruct summer temperatures over the past two millennia and found an unprecedented, longlasting and spatially synchronized cooling following a cluster of large volcanic eruptions in 536, 540 and 547 AD.
Abstract: Societal upheaval occurred across Eurasia in the sixth and seventh centuries. Tree-ring reconstructions suggest a period of pronounced cooling during this time associated with several volcanic eruptions. Climatic changes during the first half of the Common Era have been suggested to play a role in societal reorganizations in Europe1,2 and Asia3,4. In particular, the sixth century coincides with rising and falling civilizations1,2,3,4,5,6, pandemics7,8, human migration and political turmoil8,9,10,11,12,13. Our understanding of the magnitude and spatial extent as well as the possible causes and concurrences of climate change during this period is, however, still limited. Here we use tree-ring chronologies from the Russian Altai and European Alps to reconstruct summer temperatures over the past two millennia. We find an unprecedented, long-lasting and spatially synchronized cooling following a cluster of large volcanic eruptions in 536, 540 and 547 AD (ref. 14), which was probably sustained by ocean and sea-ice feedbacks15,16, as well as a solar minimum17. We thus identify the interval from 536 to about 660 AD as the Late Antique Little Ice Age. Spanning most of the Northern Hemisphere, we suggest that this cold phase be considered as an additional environmental factor contributing to the establishment of the Justinian plague7,8, transformation of the eastern Roman Empire and collapse of the Sasanian Empire1,2,5, movements out of the Asian steppe and Arabian Peninsula8,11,12, spread of Slavic-speaking peoples9,10 and political upheavals in China13.
527 citations
Ocean University of China1, Hobart Corporation2, University of Paris3, National Institute of Oceanography, India4, Monash University, Clayton campus5, Pohang University of Science and Technology6, University of California, Irvine7, Pusan National University8, University of New South Wales9, Chinese Academy of Sciences10, Chonnam National University11, Utah State University12, Pacific Marine Environmental Laboratory13, Monash University14, University of Exeter15, Geophysical Institute, University of Bergen16, Bjerknes Centre for Climate Research17, Nanjing University of Information Science and Technology18, Complutense University of Madrid19, Centre national de la recherche scientifique20, Barcelona Supercomputing Center21, University of California, San Diego22, Beijing Normal University23, Ulsan National Institute of Science and Technology24, Texas A&M University25
TL;DR: Advances in the understanding of pantropical interbasin climate interactions are reviewed and their implications for both climate prediction and future climate projections are reviewed.
Abstract: The El Nino-Southern Oscillation (ENSO), which originates in the Pacific, is the strongest and most well-known mode of tropical climate variability. Its reach is global, and it can force climate variations of the tropical Atlantic and Indian Oceans by perturbing the global atmospheric circulation. Less appreciated is how the tropical Atlantic and Indian Oceans affect the Pacific. Especially noteworthy is the multidecadal Atlantic warming that began in the late 1990s, because recent research suggests that it has influenced Indo-Pacific climate, the character of the ENSO cycle, and the hiatus in global surface warming. Discovery of these pantropical interactions provides a pathway forward for improving predictions of climate variability in the current climate and for refining projections of future climate under different anthropogenic forcing scenarios.
420 citations
01 Jan 2016
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346 citations