Explore the vast range of titles available.

Missing values in land surface temperature (LST) data are often observed in the cloud-sheltered area, thereby seriously limiting the spatiotemporal continuity of LST. In this work, Remotely Sensed Daily Land Surface Temperature Reconstruction model(RSDAST) is used to gap-fill the pixels sheltered by clouds in FY-3 C/VIRR LST. Result shows that the cloud pixels in VIRR and MODIS original LST (OLST) product can be reconstructed accurately, but the reconstruction accuracy of MODIS LST is better compared to VIRR based on the RSDAST model. In addition, the reconstruction accuracy of VIRR and MODIS LST decreases with the increase in cloud coverage, and the reduction of the reconstruction accuracy of VIRR LST is larger than that of MODIS data. The number of effective dry-wet edge fitted by VIRR RLST/NDVI scatterplot was higher than that of OLST/NDVI, and the number of clear sky pixels in Reconstructed TVDI (RTVDI) images increased significantly, indicating that the RSDAST expands the temporal resolution and spatial coverage of infrared remote sensing data under cloudy conditions. Moreover, in DOY150-DOY243, the correlation between RTVDI and soil moisture is better than that of Original TVDI (OTVDI), indicating that the RSDAST improves the monitoring ability of soil moisture in these conditions.

The temperature field reconstruction of heat source systems (TFR-HSS) with limited monitoring sensors in thermal management plays an important role in the real-time health detection systems of electronic equipment in engineering. However, prior methods with common interpolations usually cannot provide accurate reconstruction performance as required. In addition, no public dataset exists for the wide research of reconstruction methods to further boost reconstruction performance and engineering applications. To overcome this problem, this work develops a machine learning surrogate modeling benchmark for the TFR-HSS task. First, the TFR-HSS task is mathematically modeled from a real-world engineering problem, and four types of computational modelings are constructed to transform the problem into discrete mapping forms. Then, this work proposes a set of machine learning surrogate modeling methods, including general machine learning methods and deep learning methods, to advance the state-of-the-art methods over temperature field reconstruction. More importantly, this work develops a novel benchmark dataset, namely the temperature field reconstruction dataset (TFRD), to evaluate these machine learning surrogate modeling methods for the TFR-HSS task. Finally, a performance analysis of typical methods is given on the TFRD, which can serve as the baseline results on this benchmark.

Tunable diode laser absorption spectroscopy (TDLAS) is extensively utilized in monitoring of trace gases in the environment. With the relative entropy tomographic reconstruction, simultaneous multiplicative algebraic reconstruction technique algorithm and optimization of existing functions and models, TDLAS has been applied to reconstruction of temperature and humidity field, combustion diagnosis, mass flow monitoring and other domains, this paper will analyze the existing TDLAS application and algorithm research.

Temperatures in Oceania have risen by 0.5-1°C over the past 100 years, resulting e.g. in significant retreat of New Zealand’s glaciers. In order to better understand natural and anthropogenic contributions to this warming process, the observed climatic change has to be placed in a longer-term palaeotemperature context. Of particular interest is the Medieval Climate Anomaly (MCA, 1000-1200 AD), a recognized period of natural pre-industrial climate change, associated with marked temperature and hydroclimatic variability that is best known from the Northern Hemisphere. Temperature reconstructions for Oceania were traditionally based on two classical tree ring series. Here, we are enlarging the Oceania reference dataset with another 13 published temperature reconstructions from SE Australia, New Zealand and West Papua. These are based on a variety of proxy types, and help to geographically and methodologically augment the regional palaeoclimate database. The proxy series have been thoroughly compared and the MCA trends palaeoclimatologically mapped. Ten out of the 15 sites show a relatively warm MCA, compared to the last 1500 years, with warming generally occurring in the envelope period 900-1500 AD. In some sites of SE Australia and at the west coast of New Zealand’s South Island, warming appears to be delayed by 200-300 years. The end of the medieval warming at around 1500 AD occurred about two centuries later than on most other continents, suggesting a possible interhemispheric climate lag mechanism possibly involving deepwater circulation. Likely drivers for the medieval warming in Oceania are atmospheric-ocean cycles such as the Southern Annular Mode (SAM) and El Niño-Southern Oscillation (ENSO), in combination with solar activity changes. MCA palaeotemperature data are still lacking for large parts of Oceania, namely the arid and tropical parts of Australia, Micronesia, central and northern Polynesia, as well as central and eastern Melanesia, highlighting the need for future research.

We present a revised and extended high Arctic air temperature reconstruction from a single proxy that spans the past ∼12,000 y (up to 2009 CE). Our reconstruction from the Agassiz ice cap (Ellesmere Island, Canada) indicates an earlier and warmer Holocene thermal maximum with early Holocene temperatures that are 4–5 °C warmer compared with a previous reconstruction, and regularly exceed contemporary values for a period of ∼3,000 y. Our results show that air temperatures in this region are now at their warmest in the past 6,800–7,800 y, and that the recent rate of temperature change is unprecedented over the entire Holocene. The warmer early Holocene inferred from the Agassiz ice core leads to an estimated ∼1 km of ice thinning in northwest Greenland during the early Holocene using the Camp Century ice core. Ice modeling results show that this large thinning is consistent with our air temperature reconstruction. The modeling results also demonstrate the broader significance of the enhanced warming, with a retreat of the northern ice margin behind its present position in the mid Holocene and a ∼25% increase in total Greenland ice sheet mass loss (∼1.4 m sea-level equivalent) during the last deglaciation, both of which have implications for interpreting geodetic measurements of land uplift and gravity changes in northern Greenland.

The spatial context is critical when assessing present-day climate anomalies, attributing them to potential forcings and making statements regarding their frequency and severity in a long-term perspective. Recent international initiatives have expanded the number of high-quality proxy-records and developed new statistical reconstruction methods. These advances allow more rigorous regional past temperature reconstructions and, in turn, the possibility of evaluating climate models on policy-relevant, spatio-temporal scales. Here we provide a new proxy-based, annually-resolved, spatial reconstruction of the European summer (June-August) temperature fields back to 755 CE based on Bayesian hierarchical modelling (BHM), together with estimates of the European mean temperature variation since 138 BCE based on BHM and composite-plus-scaling (CPS). Our reconstructions compare well with independent instrumental and proxy-based temperature estimates, but suggest a larger amplitude in summer temperature variability than previously reported. Both CPS and BHM reconstructions indicate that the mean 20th century European summer temperature was not significantly different from some earlier centuries, including the 1st, 2nd, 8th and 10th centuries CE. The 1st century (in BHM also the 10th century) may even have been slightly warmer than the 20th century, but the difference is not statistically significant. Comparing each 50 yr period with the 1951-2000 period reveals a similar pattern. Recent summers, however, have been unusually warm in the context of the last two millennia and there are no 30 yr periods in either reconstruction that exceed the mean average European summer temperature of the last 3 decades (1986-2015 CE). A comparison with an ensemble of climate model simulations suggests that the reconstructed European summer temperature variability over the period 850-2000 CE reflects changes in both internal variability and external forcing on multi-decadal time-scales. For pan-European temperatures we find slightly better agreement between the reconstruction and the model simulations with high-end estimates for total solar irradiance. Temperature differences between the medieval period, the recent period and the Little Ice Age are larger in the reconstructions than the simulations. This may indicate inflated variability of the reconstructions, a lack of sensitivity and processes to changes in external forcing on the simulated European climate and or an underestimation of internal variability on centennial and longer time scales.

This study develops the use of ‘blue rings’ (BR), reflecting incomplete cell wall lignification, as a sensitive thermal indicator in bristlecone pine (Pinus longaeva D.K. Bailey). Using double-stained anatomical thin-sections, we explore the climatic and topographical constraints governing BR formation by developing a time-series from 83 cores and comparing BR occurrence with the full temporal span of available climatic data (1895–2008 CE). Lignification is temperature-dependent and continues at a cellular level post-radial growth completion. As BRs reflect incomplete lignification, they can serve as a higher resolution and more sensitive proxy for past cooling than previously established tree-growth indicators. Results indicate that blue ring formation is primarily induced by low September temperatures and responds more sensitively to cooling than the well-established frost-ring record. Additionally, the occurrence and intensity of blue rings decreases gradually below the upper tree line. Bristlecone pine BRs are demonstrated to have significant capacity to enhance the reconstruction of past cooling events in North America connected with both localized and hemispheric scale forcing over multi-millennial timescales. Given its unmatched longevity, the species offers an unparalleled potential for Holocene length climate reconstruction. Findings also highlight the potential for blue rings to provide a more nuanced understanding of past temperature fluctuations across multi-millennial timescales.

This study presents a summer temperature reconstruction using Scots pine tree-ring chronologies for Scotland allowing the placement of current regional temperature changes in a longer-term context. ‘Living-tree’ chronologies were extended using ‘subfossil’ samples extracted from nearshore lake sediments resulting in a composite chronology >800 years in length. The North Cairngorms (NCAIRN) reconstruction was developed from a set of composite blue intensity high-pass and ring-width low-pass filtered chronologies with a range of detrending and disturbance correction procedures. Calibration against July–August mean temperature explains 56.4% of the instrumental data variance over 1866–2009 and is well verified. Spatial correlations reveal strong coherence with temperatures over the British Isles, parts of western Europe, southern Scandinavia and northern parts of the Iberian Peninsula. NCAIRN suggests that the recent summer-time warming in Scotland is likely not unique when compared to multi-decadal warm periods observed in the 1300s, 1500s, and 1730s, although trends before the mid-sixteenth century should be interpreted with some caution due to greater uncertainty. Prominent cold periods were identified from the sixteenth century until the early 1800s—agreeing with the so-called Little Ice Age observed in other tree-ring reconstructions from Europe—with the 1690s identified as the coldest decade in the record. The reconstruction shows a significant cooling response 1 year following volcanic eruptions although this result is sensitive to the datasets used to identify such events. In fact, the extreme cold (and warm) years observed in NCAIRN appear more related to internal forcing of the summer North Atlantic Oscillation.

Almost all proxy-based temperature reconstructions for East Asia have hitherto been designed to resolve summer or annual temperature variability. Reconstruction for the winter temperature is still lacking. Here, we report an annually resolved, winter-season (December-February, DJF) temperature field reconstruction for East Asia covering the period 1300–2000 CE, based on 260 temperature-sensitive tree-ring records. The most striking feature of our new reconstruction is a significant long-term warming trend since the 14th century, which is associated with winter solar insolation at mid-latitudes of the Northern Hemisphere and the global anthropogenic impact. The amplitude of reconstructed winter temperature change over the study period was ~4.7 times greater than that for summer temperature, and the rate of winter temperature increase was ∼6 times as much as that of summer temperature. The results from climate model simulations were consistent with the reconstruction, showing that the amplitude and rate of temperature change in winter were greater than those in summer. The reconstruction also suggests the possible influence of volcanic eruptions, anthropogenic activities and winter solar insolation on the winter temperature variations. Our result also suggests a long-term decrease in summer-to-winter temperature difference occurred in 1625 (±24 years) CE.

The Mediterranean has been identified as particularly vulnerable to climate change, yet a high-resolution temperature reconstruction extending back into the Medieval Warm Period is still lacking. Here we present such a record from a high-elevation site on Mt. Smolikas in northern Greece, where some of Europe’s oldest trees provide evidence of warm season temperature variability back to 730 CE. The reconstruction is derived from 192 annually resolved, latewood density series from ancient living and relict Pinus heldreichii trees calibrating at r1911–2015 = 0.73 against regional July–September (JAS) temperatures. Although the recent 1985–2014 period was the warmest 30-year interval (JAS Twrt.1961–1990 = + 0.71 °C) since the eleventh century, temperatures during the ninth to tenth centuries were even warmer, including the warmest reconstructed 30-year period from 876–905 (+ 0.78 °C). These differences between warm periods are statistically insignificant though. Several distinct cold episodes punctuate the Little Ice Age, albeit the coldest 30-year period is centered during high medieval times from 997–1026 (− 1.63 °C). Comparison with reconstructions from the Alps and Scandinavia shows that a similar cold episode occurred in central Europe but was absent at northern latitudes. The reconstructions also reveal different millennial-scale temperature trends (NEur = − 0.73 °C/1000 years, CEur = − 0.13 °C, SEur = + 0.23 °C) potentially triggered by latitudinal changes in summer insolation due to orbital forcing. These features, the opposing millennial-scale temperature trends and the medieval multi-decadal cooling recorded in Central Europe and the Mediterranean, are not well captured in state-of-the-art climate model simulations.