1. |
- Arndt, D. S., et al.
(author)
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STATE OF THE CLIMATE IN 2017
- 2018
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In: Bulletin of The American Meteorological Society - (BAMS). - : American Meteorological Society. - 0003-0007 .- 1520-0477. ; 99:8, s. S1-S310
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Research review (peer-reviewed)
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2. |
- Arndt, D. S., et al.
(author)
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State of the Climate in 2016
- 2017
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In: Bulletin of The American Meteorological Society - (BAMS). - 0003-0007 .- 1520-0477. ; 98:8, s. S1-S280
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Journal article (peer-reviewed)abstract
- In 2016, the dominant greenhouse gases released into Earth's atmosphere-carbon dioxide, methane, and nitrous oxide-continued to increase and reach new record highs. The 3.5 +/- 0.1 ppm rise in global annual mean carbon dioxide from 2015 to 2016 was the largest annual increase observed in the 58-year measurement record. The annual global average carbon dioxide concentration at Earth's surface surpassed 400 ppm (402.9 +/- 0.1 ppm) for the first time in the modern atmospheric measurement record and in ice core records dating back as far as 800000 years. One of the strongest El Nino events since at least 1950 dissipated in spring, and a weak La Nina evolved later in the year. Owing at least in part to the combination of El Nino conditions early in the year and a long-term upward trend, Earth's surface observed record warmth for a third consecutive year, albeit by a much slimmer margin than by which that record was set in 2015. Above Earth's surface, the annual lower troposphere temperature was record high according to all datasets analyzed, while the lower stratospheric temperature was record low according to most of the in situ and satellite datasets. Several countries, including Mexico and India, reported record high annual temperatures while many others observed near-record highs. A week-long heat wave at the end of April over the northern and eastern Indian peninsula, with temperatures surpassing 44 degrees C, contributed to a water crisis for 330 million people and to 300 fatalities. In the Arctic the 2016 land surface temperature was 2.0 degrees C above the 1981-2010 average, breaking the previous record of 2007, 2011, and 2015 by 0.8 degrees C, representing a 3.5 degrees C increase since the record began in 1900. The increasing temperatures have led to decreasing Arctic sea ice extent and thickness. On 24 March, the sea ice extent at the end of the growth season saw its lowest maximum in the 37-year satellite record, tying with 2015 at 7.2% below the 1981-2010 average. The September 2016 Arctic sea ice minimum extent tied with 2007 for the second lowest value on record, 33% lower than the 1981-2010 average. Arctic sea ice cover remains relatively young and thin, making it vulnerable to continued extensive melt. The mass of the Greenland Ice Sheet, which has the capacity to contribute similar to 7 m to sea level rise, reached a record low value. The onset of its surface melt was the second earliest, after 2012, in the 37-year satellite record. Sea surface temperature was record high at the global scale, surpassing the previous record of 2015 by about 0.01 degrees C. The global sea surface temperature trend for the 21st century-to-date of +0.162 degrees C decade(-1) is much higher than the longer term 1950-2016 trend of +0.100 degrees C decade(-1). Global annual mean sea level also reached a new record high, marking the sixth consecutive year of increase. Global annual ocean heat content saw a slight drop compared to the record high in 2015. Alpine glacier retreat continued around the globe, and preliminary data indicate that 2016 is the 37th consecutive year of negative annual mass balance. Across the Northern Hemisphere, snow cover for each month from February to June was among its four least extensive in the 47-year satellite record. Continuing a pattern below the surface, record high temperatures at 20-m depth were measured at all permafrost observatories on the North Slope of Alaska and at the Canadian observatory on northernmost Ellesmere Island. In the Antarctic, record low monthly surface pressures were broken at many stations, with the southern annular mode setting record high index values in March and June. Monthly high surface pressure records for August and November were set at several stations. During this period, record low daily and monthly sea ice extents were observed, with the November mean sea ice extent more than 5 standard deviations below the 1981-2010 average. These record low sea ice values contrast sharply with the record high values observed during 2012-14. Over the region, springtime Antarctic stratospheric ozone depletion was less severe relative to the 1991-2006 average, but ozone levels were still low compared to pre-1990 levels. Closer to the equator, 93 named tropical storms were observed during 2016, above the 1981-2010 average of 82, but fewer than the 101 storms recorded in 2015. Three basins-the North Atlantic, and eastern and western North Pacific-experienced above-normal activity in 2016. The Australian basin recorded its least active season since the beginning of the satellite era in 1970. Overall, four tropical cyclones reached the Saffir-Simpson category 5 intensity level. The strong El Nino at the beginning of the year that transitioned to a weak La Nina contributed to enhanced precipitation variability around the world. Wet conditions were observed throughout the year across southern South America, causing repeated heavy flooding in Argentina, Paraguay, and Uruguay. Wetter-than-usual conditions were also observed for eastern Europe and central Asia, alleviating the drought conditions of 2014 and 2015 in southern Russia. In the United States, California had its first wetter-than-average year since 2012, after being plagued by drought for several years. Even so, the area covered by drought in 2016 at the global scale was among the largest in the post-1950 record. For each month, at least 12% of land surfaces experienced severe drought conditions or worse, the longest such stretch in the record. In northeastern Brazil, drought conditions were observed for the fifth consecutive year, making this the longest drought on record in the region. Dry conditions were also observed in western Bolivia and Peru; it was Bolivia's worst drought in the past 25 years. In May, with abnormally warm and dry conditions already prevailing over western Canada for about a year, the human-induced Fort McMurray wildfire burned nearly 590000 hectares and became the costliest disaster in Canadian history, with $3 billion (U.S. dollars) in insured losses.
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3. |
- Ades, M., et al.
(author)
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Global Climate : in State of the climate in 2019
- 2020
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In: Bulletin of The American Meteorological Society - (BAMS). - : American Meteorological Society. - 0003-0007 .- 1520-0477. ; 101:8, s. S17-S127
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Journal article (peer-reviewed)
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4. |
- Ades, M., et al.
(author)
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GLOBAL CLIMATE
- 2020
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In: BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY. - 0003-0007 .- 1520-0477. ; 101:8
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Journal article (peer-reviewed)
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5. |
- Mahecha, Miguel D., et al.
(author)
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Earth system data cubes unravel global multivariate dynamics
- 2020
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In: Earth System Dynamics. - : Copernicus GmbH. - 2190-4979 .- 2190-4987. ; 11:1, s. 201-234
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Journal article (peer-reviewed)abstract
- Understanding Earth system dynamics in light of ongoing human intervention and dependency remains a major scientific challenge. The unprecedented availability of data streams describing different facets of the Earth now offers fundamentally new avenues to address this quest. However, several practical hurdles, especially the lack of data interoperability, limit the joint potential of these data streams. Today, many initiatives within and beyond the Earth system sciences are exploring new approaches to overcome these hurdles and meet the growing interdisciplinary need for data-intensive research; using data cubes is one promising avenue. Here, we introduce the concept of Earth system data cubes and how to operate on them in a formal way. The idea is that treating multiple data dimensions, such as spatial, temporal, variable, frequency, and other grids alike, allows effective application of user-defined functions to co-interpret Earth observations and/or model- data integration. An implementation of this concept combines analysis-ready data cubes with a suitable analytic interface. In three case studies, we demonstrate how the concept and its implementation facilitate the execution of complex workflows for research across multiple variables, and spatial and temporal scales: (1) summary statistics for ecosystem and climate dynamics; (2) intrinsic dimensionality analysis on multiple timescales; and (3) model-data integration. We discuss the emerging perspectives for investigating global interacting and coupled phenomena in observed or simulated data. In particular, we see many emerging perspectives of this approach for interpreting large-scale model ensembles. The latest developments in machine learning, causal inference, and model-data integration can be seamlessly implemented in the proposed framework, supporting rapid progress in data-intensive research across disciplinary boundaries.
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6. |
- Zhang, Weijie, et al.
(author)
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The effect of relative humidity on eddy covariance latent heat flux measurements and its implication for partitioning into transpiration and evaporation
- 2023
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In: Agricultural and Forest Meteorology. - : Elsevier BV. - 0168-1923. ; 330
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Journal article (peer-reviewed)abstract
- While the eddy covariance (EC) technique is a well-established method for measuring water fluxes (i.e., evaporation or 'evapotranspiration’, ET), the measurement is susceptible to many uncertainties. One such issue is the potential underestimation of ET when relative humidity (RH) is high (>70%), due to low-pass filtering with some EC systems. Yet, this underestimation for different types of EC systems (e.g. open-path or closed-path sensors) has not been characterized for synthesis datasets such as the widely used FLUXNET2015 dataset. Here, we assess the RH-associated underestimation of latent heat fluxes (LE, or ET) from different EC systems for 163 sites in the FLUXNET2015 dataset. We found that the LE underestimation is most apparent during hours when RH is higher than 70%, predominantly observed at sites using closed-path EC systems, but the extent of the LE underestimation is highly site-specific. We then propose a machine learning based method to correct for this underestimation, and compare it to two energy balance closure based LE correction approaches (Bowen ratio correction, BRC, and attributing all errors to LE). Our correction increases LE by 189% for closed-path sites at high RH (>90%), while BRC increases LE by around 30% for all RH conditions. Additionally, we assess the influence of these corrections on ET-based transpiration (T) estimates using two different ET partitioning methods. Results show opposite responses (increasing vs. slightly decreasing T-to-ET ratios, T/ET) between the two methods when comparing T based on corrected and uncorrected LE. Overall, our results demonstrate the existence of a high RH bias in water fluxes in the FLUXNET2015 dataset and suggest that this bias is a pronounced source of uncertainty in ET measurements to be considered when estimating ecosystem T/ET and WUE.
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