Significant Climate Research Articles

Centennial-scale East Asian winter monsoon variability within the Younger Dryas

The Younger Dryas (YD) is recognized as a millennial-scale cold climate event that occurred during the last deglaciation in the Northern Hemisphere. Modeling and geological evidences reveal that the YD period was punctuated by multiple rapid changes at interdecadal to centennial timescales. However, characteristics and mechanism of abrupt climate variability within the YD in its most pronounced winter interval remain poorly constrained. Here, we present two high-resolution loess grain-size time series from the western Chinese Loess Plateau (CLP) to address centennial-scale East Asian winter monsoon (EAWM) variability during this phenomenal cooling event. The mean grain size results reveal two cold intervals of the Heinrich event 1 and YD during the last deglaciation, corresponding well to climate changes from regional and global context. More importantly, the mean grain size results demonstrate a persistent centennial-scale EAWM variability within the YD. We propose that this was caused by the North Atlantic sea ice variation via fast atmospheric processes between the subpolar and mid-latitude regions. We also observed a marked decrease in magnitudes of centennial-scale EAWM variability around the mid-YD. Such a mid-YD shift is closely related to a northward shift of the atmospheric polar front and sea ice retreat induced by the resumption of the Atlantic meridional overturning circulation (AMOC). Our results suggest that the AMOC-induced sea ice change in the North Atlantic plays a more dominant role than the AMOC itself in transmitting abrupt climate signals over the Northern Hemisphere.

Impact of climate change on river water temperature and dissolved oxygen: Indian riverine thermal regimes

The impact of climate change on the oxygen saturation content of the world’s surface waters is a significant topic for future water quality in a warming environment. While increasing river water temperatures (RWTs) with climate change signals have been the subject of several recent research, how climate change affects Dissolved Oxygen (DO) saturation levels have not been intensively studied. This study examined the direct effect of rising RWTs on saturated DO concentrations. For this, a hybrid deep learning model using Long Short-Term Memory integrated with k-nearest neighbor bootstrap resampling algorithm is developed for RWT prediction addressing sparse spatiotemporal RWT data for seven major polluted river catchments of India at a monthly scale. The summer RWT increase for Tunga-Bhadra, Sabarmati, Musi, Ganga, and Narmada basins are predicted as 3.1, 3.8, 5.8, 7.3, 7.8 °C, respectively, for 2071–2100 with ensemble of NASA Earth Exchange Global Daily Downscaled Projections of air temperature with Representative Concentration Pathway 8.5 scenario. The RWT increases up to7 °C for summer, reaching close to 35 °C, and decreases DO saturation capacity by 2–12% for 2071–2100. Overall, for every 1 °C RWT increase, there will be about 2.3% decrease in DO saturation level concentrations over Indian catchments under climate signals.

Optimizing the Management of Multireservoir Systems Under Shifting Flow Regimes

AbstractOver the past few decades, significant research efforts have been devoted to the development of tools and techniques to improve the operational effectiveness of multireservoir systems. One of those efforts focuses on the incorporation of relevant hydrologic information into reservoir operation models. This effort is particularly relevant in regions characterized by low‐frequency climate signals, where time series of river discharges exhibit regime‐like behavior. Failure to properly capture such regime‐like behavior yields suboptimal operating policies, especially in systems characterized by large storage capacity such as large multireservoir systems. Hidden Markov Modeling is a class of hydrological models that can accommodate both overdispersion and serial dependence in time series, two essential hydrological properties that must be captured when modeling a system where the climate is switching between different states (e.g., dry, normal, and wet). In terms of reservoir operation, Stochastic Dual Dynamic Programming (SDDP) is one of the few optimization techniques that can accommodate both system and hydrologic complexity, that is, a large number of reservoirs and diverse hydrologic information. However, current SDDP formulations are unable to capture the long‐term persistence of the streamflow process found in some regions. In this paper, we present an extension of the SDDP algorithm that can handle the long‐term persistence and provide reservoir operating policies that explicitly capture regime shifts. Using the Senegal River Basin as a case study, we illustrate the potential gain associated with reservoir operating policies tailored to climate states.

Climate Leads to Reversed Latitudinal Changes in Chinese Flood Peak Timing

AbstractChanges in river floods under a changing climate are of worldwide concerns, but relevant knowledge is limited especially over the East Asia monsoon region. Here we examine changes in flood peak timing based on the most comprehensive flood data set to date across China during 1961–2017. The temporal shifts of Chinese flood peak timing range from −19.0 days earlier to +14.0 days later per decade. Earlier flood occurrences are mainly observed in northern China, with delayed flood occurrences in the south. The spatial pattern of reversed latitudinal changes in flood timing leads to growing spatial extents of concurrent river floods over China. Soil moisture plays an important role in modulating such changes, despite precipitation determines the climatological mean dates of flood occurrences. Our results highlight a strong climate signal on the changes in flood timing over China, and call for coordinated efforts in alleviating expanding flood hazards related to the changes in flood timing.

Holocene paleoclimate variability in the eastern Mediterranean, inferred from the multi-proxy record of Lake Vouliagmeni, Greece

This study presents a Holocene multi-proxy record from Lake Vouliagmeni, eastern Gulf of Corinth, Greece. The lake is subjected to intense climatic and tectonic forces causing stratigraphic variations with laminated sediments frequently interrupted by homogenous sections and event deposits. Lamination couplets consist of aragonite layers alternating with detrital and organic residues formed during periods of seawater intrusion and stratification of the lake water. The discontinuous occurrence of laminated deposits excludes a varve based chronology from being established but highlights the susceptibility of the lake to record environmental and climatic changes. Our synthesis model for regional climatic reconstruction and local environmental changes derives from δ 18 O and δ 13 C data from laminated and homogenous sediments studied separately and depending on the dominant carbonate mineral . This is further strengthened by high-resolution geochemical proxies, diatom and sedimentological data. Regional climatic signals from key sites and possible links to the Lake Vouliagmeni record are explored in response to atmospheric circulation patterns. Phases of overall humid conditions are recorded by increased inflow of siliciclastic material to the lake and negative δ 18 O bulk values. In contrast, periods of marine intrusion and enhanced evaporation are recorded by aragonite precipitation, positive δ 18 O Ar values and laminations. The laminations formed in the lake seem to occur during periods of sea water intrusion into the lake, which led to pycnocline stabilization and stratified lake waters. • δ 18 O bulk and δ 13 C bulk reflect variations in precipitation and detrital influx. • Periods of stratified lake waters and pycnocline stabilization are displayed with aragonite laminations. • Humid phases are recorded from 10 to 7.8, 5.2 to 4.4 and 1.5 to 0.2 ka cal BP with lower δ 18 O bulk . • Increased summer temperatures occur from 7.4 to 6.8 and 5.4 to 4.5 ka cal BP and are reflected with increased carbonate accumulation.

Blowing in the Wind: Pollen's Mobility as a Challenge to Measuring Climate by Proxy, 1916-1939.

This article examines how geologists, botanists, and ecologists used pollen as a proxy for past climates in the first half of the twentieth century. It focuses on a particular challenge of measuring climate with pollen: pollen's mobility. As scientists came to learn, pollen from some vegetation is more mobile than others. Pollen's differential mobility challenged regional climatic conclusions because of the potential mixing of pollen from various locations. To minimize the effects of this problem, pollen analysts sought to decrease the noise produced by highly local or foreign pollen. Yet, many ground-truthing and calibration methods were not available to pollen analysts because of the temporal separation between the observer and the object of interest. Instead, pollen analysts had to make spatial meaning out of fossil pollen using empirical studies of modern pollen, inferences from macrofossils and successional history, and applying statistical theories to fossil pollen data. Many of these corrections factors relied on pollen analysts' knowledge of place, including elements like the location's topography, prevailing winds, and plant cover. These elements were a natural part of vegetation-pollen-climate interactions. Scientists needed to account for them to turn pollen into a proxy for climate. Pollen's movement was equally natural, but scientists decided to eliminate some pollen to augment the regional climate signal. These selective eliminations of place suggest that not all elements of place are equally important. Scientists had to omit some elements of place to make sense of the complexities of the natural world.

Effects of Mass Wasting on the Physiochemical Properties of Fluvial Sediments in Puerto Rico Following Hurricane Maria

AbstractMass wasting plays an important role in carbon cycling and sequestration by exposing fresh bedrock and delivering hillslope sediments to lowlands and fluvial systems. Chemical weathering signatures of landslide‐derived fluvial sediments can be used to understand linkages between hillslope and fluvial processes and thus to characterize spatiotemporal dynamics of sediments. However, chemical signatures of fluvial sediments derived by landslides are yet to be fully understood. Here, we compare the bulk chemistry, mineralogy, and grain size of fluvial sediments collected pre‐ and post‐Hurricane Maria in the Rio Guayanés and Rio Guayabo watersheds in southeastern Puerto Rico to help fill this knowledge gap. Comparison of the mud fraction (<63 μm) of fluvial sediments collected before Hurricane Maria with similar mud fractions collected after the storm reveals that the post‐hurricane muds exhibit a wider range and higher average weathering index values, but coarser grain size modes. We infer that small landslides triggered by Hurricane Maria transported slope materials from shallow depths, including weathered topsoil and saprolite, as opposed to previous deep‐seated landslides, which likely sampled regolith and bedrock. Variances in weathering indices observed that pre‐ and post‐hurricanes do not necessarily reflect average climate signatures, but rather reflect subtle differences in a transport mechanism, which produce significant differences in weathering indices recorded by fluvial sediments. We propose that weathering indices provide a means to understand sediment dynamics in mountainous regions, particularly for sediment transported immediately after landslides triggered by extreme events, such as precipitation and earthquakes, and also provide important data sets required for mapping potential carbon sequestration across landscapes.

On the choice of TLS versus OLS in climate signal detection regression

Total least squares (TLS) or multivariate orthogonal regression is widely used as a remedy for attenuation bias in climate signal detection or “optimal fingerprinting” regression. But under some circumstances it overcorrects and imparts an upward bias, as well as generating extremely unstable and imprecise coefficient estimates. While there has been increasing attention paid recently to the validity of TLS-based confidence intervals, there has been no corresponding examination of coefficient bias problems. This note explains why they are pertinent and presents a Monte Carlo simulation to illustrate the hazards of using TLS in a signal detection application without testing whether the modeling context makes it a suitable choice. TLS is not automatically preferred over OLS even when explanatory variables are believed to contain random errors. Notably it can be sufficiently biased to cause false positives when explanatory signals are negatively correlated, and the bias gets worse as the signal-noise ratio on the explanatory variables rises. Additionally TLS should not be used on its own for climate signal detection inferences since if the no-signal null is true, TLS is generally inconsistent whereas OLS attenuation bias disappears.

Two Nothofagus Species in Southernmost South America Are Recording Divergent Climate Signals

Recent climatic trends, such as warming temperatures, decrease in rainfall, and extreme weather events (e.g., heatwaves), are negatively affecting the performance of forests. In northern Patagonia, such conditions have caused tree growth reduction, crown dieback, and massive die-back events. However, studies looking at these consequences in the southernmost temperate forest (Nothofagus betuloides and Nothofagus pumilio) are much scarcer, especially in southernmost South America (SSA). These forests are also under the influence of the positive phase of Antarctic Oscillation (AAO, also known as Southern Annular Mode, SAM) that has been associated with increasing trends in temperature, drought, and extreme events in the last decades. This study evaluated the growth patterns and the climatic response of eight new tree-ring chronologies from Nothofagus species located at the upper treeline along different environmental gradients in three study areas: Punta Arenas, Yendegaia National Park, and Navarino Island in SSA. The main modes of the ring-width index (RWI) variation were studied using principal component analysis (PCA). We found that PC1 has the higher loadings for sites with precipitation values over 600 mm/yr, PC2 with N. betuloides sites, and PC3 with higher loadings for sites with precipitation values below 600 mm/yr. Our best growth-climate relationships are between N. betuloides and AAO and the most northeastern site of N. pumilio with relative humidity (which coincides with heatwaves and extreme drought). The climatic signals imprinted in the southernmost forests are sensitive to climatic variability, the climate forcing AAO, and the effects of climate change in the last decades.

A new high-resolution palaeotemperature record during the Middle–Late Ordovician transition derived from conodont δ 18 O palaeothermometry

Climate cooling has been commonly considered as one of the most plausible triggers of the Great Ordovician Biodiversification Event (GOBE). However, the details of coeval sea-surface temperature (SST) variation during and after the biodiversification peak are still unclear owing to lack of continuous, high-resolution palaeotemperature records. Here, we report the first high-resolution in situ secondary ion mass spectrometry conodont apatite oxygen isotope ( δ 18 O apatite ) curve from the Kalpin Shuinichang and Dawangou sections (the auxiliary Global Stratotype Section and Point (GSSP) for the base of the Upper Ordovician Series) to reconstruct the detailed Ordovician palaeotemperature history in the Tarim Basin, northwestern China. The new oxygen isotope data, based on mono-generic specimens, reveal a similar first-order variation trend to published records from other palaeocontinents, which is thus suggestive of a global signal. A −0.7‰ δ 18 O apatite shift ( c. 3.2°C warming) is identifiable in the Dawangou Formation (early–middle Darriwilian). This is followed by a long-term +2.2‰ positive shift in δ 18 O apatite ( c. 10°C cooling) in the overlying strata spanning the Saergan and the Kanling formations (late Darriwilian–Sandbian), probably indicating a global climatic signal. Examining the coeval marine 87 Sr/ 86 Sr records, the early–middle Darriwilian minor δ 18 O apatite decrease is coincident with the onset of a long-term negative 87 Sr/ 86 Sr excursion, possibly indicating a slight climate warming in response to increasing volcanic degassing in the context of accelerating spreading of mid-oceanic ridges. In contrast, the following long-term positive δ 18 O apatite excursion, in parallel with persistent 87 Sr/ 86 Sr drop, probably indicates a major climate cooling initially caused by the rapid tropical continental weathering, which in turn may have reduced the continental radiogenic Sr influx. Supplementary material : Three supplementary tables (S1, S2, and S3) indicating the in-situ oxygen isotopic results of conodont apatite from the Kalpin Shuinichang-Dawangou composite section, Qinghu standard, and Durango standard, respectively are available at https://doi.org/10.6084/m9.figshare.c.5924175

Climate shapes community flowering periods across biomes

AbstractAimClimate shapes the composition and function of plant communities globally, but it remains unclear how this influence extends to floral traits. Flowering phenology, or the time period in which a species flowers, has well‐studied relationships with climatic signals at the species level but has rarely been explored at a cross‐community and continental scale. Here, we characterise the distribution of flowering periods (months of flowering) across continental plant communities encompassing six biomes, and determine the influence of climate on community flowering period lengths.LocationAustralia.TaxonFlowering plants.MethodsWe combined plant composition and abundance data from 629 standardised floristic surveys (AusPlots) with data on flowering period from the AusTraits database and additional primary literature for 2983 species. We assessed abundance‐weighted community mean flowering periods across biomes and tested their relationship with climatic annual means and the predictability of climate conditions using regression models.ResultsCombined, temperature and precipitation (annual mean and predictability) explain 29% of variation in continental community flowering period. Plant communities with higher mean temperatures and lower mean precipitation have longer mean flowering periods. Moreover, plant communities in climates with predictable temperatures and, to a lesser extent, predictable precipitation have shorter mean flowering periods. Flowering period varies by biome, being longest in deserts and shortest in alpine and montane communities. For instance, desert communities experience low and unpredictable precipitation and high, unpredictable temperatures and have longer mean flowering periods, with desert species typically flowering at any time of year in response to rain.Main conclusionsCurrent climate conditions shape flowering periods across biomes, with implications for phenology under climate change. Shifts in flowering periods across climatic gradients reflect changes in plant strategies, affecting patterns of plant growth and reproduction as well as the availability of floral resources for pollinators across the landscape.

Consistent signals of a warming climate in occupancy changes of three insect taxa over 40 years in central Europe.

Recent climate and land-use changes are having substantial impacts on biodiversity, including population declines, range shifts, and changes in community composition. However, few studies have compared these impacts among multiple taxa, particularly because of a lack of standardized time series data over long periods. Existing data sets are typically of low resolution or poor coverage, both spatially and temporally, thereby limiting the inferences that can be drawn from such studies. Here, we compare climate and land-use driven occupancy changes in butterflies, grasshoppers, and dragonflies using an extensive data set of highly heterogeneous observation data collected in the central European region of Bavaria (Germany) over a 40-year period. Using occupancy models, we find occupancies (the proportion of sites occupied by a species in each year) of 37% of species have decreased, 30% have increased and 33% showed no significant trend. Butterflies and grasshoppers show strongest declines with 41% of species each. By contrast, 52% of dragonfly species increased. Temperature preference and habitat specificity appear as significant drivers of species trends. We show that cold-adapted species across all taxa have declined, whereas warm-adapted species have increased. In butterflies, habitat specialists have decreased, while generalists increased or remained stable. The trends of habitat generalists and specialists both in grasshoppers and semi-aquatic dragonflies, however did not differ. Our findings indicate strong and consistent effects of climate warming across insect taxa. The decrease of butterfly specialists could hint towards a threat from land-use change, as especially butterfly specialists' occurrence depends mostly on habitat quality and area. Our study not only illustrates how these taxa showed differing trends in the past but also provides hints on how we might mitigate the detrimental effects of human development on their diversity in the future.

Ostracods from upper Yacoraite Formation (Danian), Salta Basin, Western Argentina: Taxonomy and paleoenvironmental indicators of climatic signals in lacustrine deposits

This paper presents the first study of nonmarine ostracods recovered from the Danian of the upper Yacoraite Formation (Balbuena IV sequence) Salta Basin. Six species were identified: Ilyocypris triebeli, Ilyocypris argentiniensis, Neuquenocypris (Alleniella)? sp. 1; Neuquenocypris (Alleniella)? sp. 2; Penthesilenula sp. and four indeterminate species. The ostracod fauna shows fluctuations in abundance, diversity, and preservation associated with different phases of the paleolake evolution. This distribution, clearly delineated by the depositional facies, corroborates previous geochemical analyses and high-resolution sequence stratigraphy developed for the section. In general, the most abundant occurrences of ostracods coincide with high-frequency transgressive tracts of the lake system, which form long-term wettest interval of the upper Yacoraite Formation.

Fire as a Major Factor in Dynamics of Tree-Growth and Stable δ13C and δ18O Variations in Larch in the Permafrost Zone

Wildfires are one of the most important environmental factors controlling forest ecosystem physiology and the carbon balance in the permafrost zone of North Siberia. We investigated tree-ring width (TRW) and stable isotope chronologies in tree-ring cellulose (δ13CCell, δ18OCell) of Larix Gmelinii (Rupr.) Rupr. from a wet (WS) and a dry (DS) site. These sites are characterized by different fire histories (fire in 1852 at the wet and 1896 at the dry sites, respectively). TRW and δ18OCell are identified to be the most sensitive parameters in the changing tree growth conditions after fire. The differences in the soil seasonal thermal regime of sites after fires are shown in the relationship between the studied parameters. The δ13CCell values in tree rings from the two sites are positively correlated independently of the fire impact. This fact indicates that δ13CCell chronologies might be more adequate for climatic reconstruction in the region due to the climate signal consistency. Relationships of δ18OCell values between the two sites are still significantly positive 60 years after the fire impact. Dendroclimatic analysis indicates significant changes in tree-ring growth and isotopic ratio responses to climate due to the increased demand of water for trees during the post-fire period (deeper seasonal subsidence of permafrost).

Preface

International Conference on Applications of Intelligent Computing in Engineering and Science (AICES)-2022 12th - 13th February 2022National Institute of Technology (NIT) Raipur is proud to host the IOP International Conference on Applications of Intelligent Computing in Engineering and Science (AICES)-2022 from 12th to 13th February 2022 in virtual mode. It was jointly organised by the Department of Applied Geology, Department of Information Technology (IT) and Department of Biomedical Engineering of NIT Raipur.Intelligent computing is one of the emerging fields that can add new and better application in a wide range of sectors like healthcare, service sector, and processing industry to name some. The conference showcases advancements that will enable the researchers to develop improved approaches for solving science and engineering problems.The conference aims to provide a forum for researchers, practitioners and professionals from the industry and the academia to share their research trends, findings, and results in the multidisciplinary field of intelligent computing. Various applications of intelligent computing in earth and environment science, biomedical engineering, and information technology was covered. Topics like geospatial analysis, weather and climate forecasting, biomedical imaging and signal processing, internet of things, machine learning and deep learning applications, biomedical instrumentation, medical imaging physics etc. are in the scope of conference. The Conference highlights diverse perspectives to interested geologists, meteorologists, biomedical engineers, software engineers and computer professionals, medical professionals, biotechnologists, pharmaceutical experts, sustainability researchers and also provided a platform for potential knowledge exchange on recent trends, theories and practices in the field of intelligent computing.List of Chief Patron, Patron(s), Chairman, Secretary, Technical Advisory Committee, Technical Program Chair (Internal), Management Chair, Session Chair/Reviewer, Editors are available in the pdf

Increased population exposure to Amphan‐scale cyclones under future climates

AbstractSouthern Asia experiences some of the most damaging climate events in the world, with loss of life from some cyclones in the hundreds of thousands. Despite this, research on climate extremes in the region is substantially lacking compared to other parts of the world. To understand the narrative of how an extreme event in the region may change in the future, we consider Super Cyclone Amphan, which made landfall in May 2020, bringing storm surges of 2–4 m to coastlines of India and Bangladesh. Using the latest CMIP6 climate model projections, coupled with storm surge, hydrological, and socio‐economic models, we consider how the population exposure to a storm surge of Amphan's scale changes in the future. We vary future sea level rise and population changes consistent with projections out to 2100, but keep other factors constant. Both India and Bangladesh will be negatively impacted, with India showing >200% increased exposure to extreme storm surge flooding (>3 m) under a high emissions scenario and Bangladesh showing an increase in exposure of >80% for low‐level flooding (>0.1 m). It is only when we follow a low‐emission scenario, consistent with the 2°C Paris Agreement Goal, that we see no real change in Bangladesh's storm surge exposure, mainly due to the population and climate signals cancelling each other out. For India, even with this low‐emission scenario, increases in flood exposure are still substantial (>50%). While here we attribute only the storm surge flooding component of the event to climate change, we highlight that tropical cyclones are multifaceted, and damages are often an integration of physical and social components. We recommend that future climate risk assessments explicitly account for potential compounding factors.

Inferring Aquitard Hydraulic Conductivity Using Transient Temperature‐Depth Profiles Impacted by Ground Surface Warming

AbstractAquitard hydraulic properties are notoriously difficult to assess, yet accurate aquitard hydraulic conductivity estimates are critical to quantify recharge and discharge to and from semi‐confined aquifer systems via hydraulic head gradients. Such flux quantification is required to evaluate the risks of aquifer exploitation by groundwater abstraction and aquifer vulnerability to surface contamination. In this study, we consider a regionally important aquitard and compare existing hydraulic conductivity estimates obtained through traditional methods to those inferred from long‐term hydraulic head monitoring and thermally derived vertical groundwater fluxes (0.04–0.25 m/y). We estimate the fluxes using numerical modeling to analyze the propagation of decadal climate signals into temperature‐depth profiles and fitting the simulated and observed inflection point depths (location of minimum temperature). Results suggest that climate‐disturbed temperature‐depth profiles paired with multi‐level head data can yield accurate vertical fluxes and aquitard hydraulic conductivities. This approach for characterizing groundwater systems and quantifying flows to and from sedimentary aquifers is more efficient but yields results that are comparable to conventional methods.

Sedimentation pattern of kame terraces and its implication to climatic events in the Gangotri glacier region since 25 Ka BP, Garhwal Himalaya, India

• The sedimentation in the Kame terraces has taken place under low energy stagnant water conditions in a lacustrine environment . • The Kame terraces were evolved under glacial-fluvial at the base and lacustrine environment at the top. • The study demonstrates climate change since 25 Ka BP. • The study confirms the major climatic signatures such as Last Glacial Maximum , Older Dryas , Bølling-Allerød, Younger Dryas , Indus Valley Civilization Collapse, Medieval Warm Period and Little Ice Age. Gangotri glacier, located in the Uttarkashi district, is one of the longest valley glaciers of the Garhwal Himalaya. It exhibits lateral moraines, recessional moraines, outwash plains, kame terraces, and debris cones. Kame terraces are significant landforms that preserve the climatic records and geological history in their deposits. The sedimentary and mineral magnetic analysis on 165 cm thick trenched sections sampled at 2.5 cm interval of the kame terraces together with the AMS (Accelerator Mass Spectrometer) age indicate its response to the major climatic events in this region and sedimentation history of the kame terraces. The granulometric analysis describes that the mean grain size of these sediments varies from coarse to fine sand, which are poorly sorted with an excess of finer sediments. This indicates, low to moderate energy over a longer duration with fluctuation of the depositional environment. The mineral magnetic analysis reflects unimodal detrital modes governed by the energy conditions from meltwaters that are in turn controlled by the climatic conditions from warmer to colder episodes. Therefore, the sedimentation in the kame terraces has taken place under the low energy lacustrine environment during warmer climates. The kame terraces sedimentation therefore has recorded the major climatic events, such as Last Glacial Maximum (LGM) 21–19.5 Ka BP, Older Dryas (OD) 16.5–14.5 Ka BP, Bølling-Allerød (BA) 14.5–13.5 Ka BP, Younger Dryas (YD) 13.5–12 Ka BP, Indus Valley Civilization Collapse (IVCC) 5.0–3.0 Ka BP, Medieval Warm Period (MWP) 1.25–0.7 Ka BP and Little Ice Age (LIA) 0.7–0.2 Ka BP.

Climatic Signals on Growth Ring Variation in Salix herbacea: Comparing Two Contrasting Sites in Iceland

Salix herbacea, being such an adaptive species, has never been studied for its climatic response. The main purpose of this study is to examine the dendrochronological potential of S. herbacea. Furthermore, it aims to identify the main environmental factors that are influencing its growth. We selected two sampling sites that are different in terms of morphology and climate. Overall, 40 samples of dwarf willow were collected from two research sites and were analyzed by following the standard dendrochronological methods. The ring width chronology of the dwarf willow from the Afrétt site spans 1953–2017, i.e., 64 years. The correlations between air temperature and the ring width of dwarf willow indicate that this species responds positively to spring and summer temperatures for the Myrdal site. For the Afrétt site, this species responds positively to winter and summer precipitation. These effects may be related to tundra browning, a process that has appeared since the beginning of the 21st century. Our work is the first attempt to create a growth ring chronology of S. herbacea and to investigate its climate sensitivity. Despite the differences in local climate in both sites, this species shows its potentiality and a direct imprint of recent environmental changes in its ring width growth pattern.

The Prediction Algorithm and Characteristics Analysis of Kuroshio Sea Surface Temperature Anomalies

Based on 130 climate signal indexes provided by National Climate Center of China, this paper established a decision tree diagnostic prediction model for Spring Kuroshio Sea Surface Temperature (SST) from 1961 to 2015 (65 years) by using Chi-Squared Automatic Interaction Detector (CHAID) algorithm in data mining and obtained five rule sets to determine whether Spring Kuroshio SST is high or not. Considering the data of the 44 years from 1961 to 2004 as the training set of the model and the other years as the test set, the training accuracy of the model can reach to 95.45% and the test accuracy can reach to 81.82%. Three types of Spring Kuroshio SST are different in intensity and distribution. The results show that the prediction model of Spring Kuroshio SST based on CHAID algorithm has a high prediction accuracy, with the reasonable and effective model and the well-thought-out decision rules. Moreover, based on the results of decision classification, the SST anomalies correspond to different distribution characteristics of summer daily precipitation anomalies in eastern China, which can provide a new idea and method for climate prediction of regional summer precipitation.