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  • American Meteorological Society  (19)
  • 1
    Online Resource
    Online Resource
    WMO Global Annual to Decadal Climate Update: A Prediction for 2021–25
    American Meteorological Society ; 2022
    In:  Bulletin of the American Meteorological Society Vol. 103, No. 4 ( 2022-04), p. E1117-E1129
    Details
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 103, No. 4 ( 2022-04), p. E1117-E1129
    Abstract: As climate change accelerates, societies and climate-sensitive socioeconomic sectors cannot continue to rely on the past as a guide to possible future climate hazards. Operational decadal predictions offer the potential to inform current adaptation and increase resilience by filling the important gap between seasonal forecasts and climate projections. The World Meteorological Organization (WMO) has recognized this and in 2017 established the WMO Lead Centre for Annual to Decadal Climate Predictions (shortened to “Lead Centre” below), which annually provides a large multimodel ensemble of predictions covering the next 5 years. This international collaboration produces a prediction that is more skillful and useful than any single center can achieve. One of the main outputs of the Lead Centre is the Global Annual to Decadal Climate Update (GADCU), a consensus forecast based on these predictions. This update includes maps showing key variables, discussion on forecast skill, and predictions of climate indices such as the global mean near-surface temperature and Atlantic multidecadal variability. it also estimates the probability of the global mean temperature exceeding 1.5°C above preindustrial levels for at least 1 year in the next 5 years, which helps policy-makers understand how closely the world is approaching this goal of the Paris Agreement. This paper, written by the authors of the GADCU, introduces the GADCU, presents its key outputs, and briefly discusses its role in providing vital climate information for society now and in the future.
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    URL: Article
    DOI: 10.1175/BAMS-D-20-0311.1
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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  • 2
    Online Resource
    Online Resource
    Monthly North Atlantic Sea Level Pressure Reconstruction Back to 1750 CE Using Artificial Intelligence Optimization
    American Meteorological Society ; 2022
    In:  Journal of Climate Vol. 35, No. 11 ( 2022-06), p. 3395-3410
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 35, No. 11 ( 2022-06), p. 3395-3410
    Abstract: Main modes of atmospheric variability exert a significant influence on weather and climate at local and regional scales on all time scales. However, their past changes and variability over the instrumental record are not well constrained due to limited availability of observations, particularly over the oceans. Here we couple a reconstruction method with an evolutionary algorithm to yield a new 1° × 1° optimized reconstruction of monthly North Atlantic sea level pressure since 1750 from a network of meteorological land and ocean observations. Our biologically inspired optimization technique finds an optimal set of weights for the observing network that maximizes the reconstruction skill of sea level pressure fields over the North Atlantic Ocean, bringing significant improvements over poorly sampled oceanic regions, as compared to non-optimized reconstructions. It also reproduces realistic variations of regional climate patterns such as the winter North Atlantic Oscillation and the associated variability of the subtropical North Atlantic high and the subpolar low pressure system, including the unprecedented strengthening of the Azores high in the second half of the twentieth century. We find that differences in the winter North Atlantic Oscillation indices are partially explained by disparities in estimates of its Azores high center. Moreover, our reconstruction also shows that displacements of the summer Azores high center toward the northeast coincided with extremely warm events in western Europe including the anomalous summer of 1783. Overall, our results highlight the importance of improving the characterization of the Azores high for understanding the climate of the Euro-Atlantic sector and the added value of artificial intelligence in this avenue.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    URL: Article
    DOI: 10.1175/JCLI-D-21-0155.1
    DOI: 10.1175/JCLI-D-21-0155.s1
    RVK:
    UA 4548
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 3
    Online Resource
    Online Resource
    On the Internal Variability of Simulated Daily Precipitation*
    American Meteorological Society ; 2015
    In:  Journal of Climate Vol. 28, No. 9 ( 2015-05-01), p. 3624-3630
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 28, No. 9 ( 2015-05-01), p. 3624-3630
    Abstract: Climate model simulations are currently the main tool to provide information about possible future climates. Apart from scenario uncertainties and model error, internal variability is a major source of uncertainty, complicating predictions of future changes. Here, a suite of statistical tests is proposed to determine the shortest time window necessary to capture the internal precipitation variability in a stationary climate. The length of this shortest window thus expresses internal variability in terms of years. The method is applied globally to daily precipitation in a 200-yr preindustrial climate simulation with the CMCC-CM coupled general circulation model. The two-sample Cramér–von Mises test is used to assess differences in precipitation distribution, the Walker test accounts for multiple testing at grid cell level, and field significance is determined by calculating the Bejamini–Hochberg false-discovery rate. Results for the investigated simulation show that internal variability of daily precipitation is regionally and seasonally dependent and that regions requiring long time windows do not necessarily coincide with areas with large standard deviation. The estimated time scales are longer over sea than over land, in the tropics than in midlatitudes, and in the transitional seasons than in winter and summer. For many land grid cells, 30 seasons suffice to capture the internal variability of daily precipitation. There exist regions, however, where even 50 years do not suffice to sample the internal variability. The results show that diagnosing daily precipitation change at different times based on fixed global snapshots of one climate simulation might not be a robust detection method.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    URL: Article
    DOI: 10.1175/JCLI-D-14-00745.1
    DOI: 10.1175/JCLI-D-14-00745.s1
    RVK:
    UA 4548
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2015
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 4
    Online Resource
    Online Resource
    Tree-Ring Amplification of the Early Nineteenth-Century Summer Cooling in Central Europea
    American Meteorological Society ; 2015
    In:  Journal of Climate Vol. 28, No. 13 ( 2015-07-01), p. 5272-5288
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 28, No. 13 ( 2015-07-01), p. 5272-5288
    Abstract: Annually resolved and absolutely dated tree-ring chronologies are the most important proxy archives to reconstruct climate variability over centuries to millennia. However, the suitability of tree-ring chronologies to reflect the “true” spectral properties of past changes in temperature and hydroclimate has recently been debated. At issue is the accurate quantification of temperature differences between early nineteenth-century cooling and recent warming. In this regard, central Europe (CEU) offers the unique opportunity to compare evidence from instrumental measurements, paleomodel simulations, and proxy reconstructions covering both the exceptionally hot summer of 2003 and the year without summer in 1816. This study uses 565 Swiss stone pine (Pinus cembra) ring width samples from high-elevation sites in the Slovakian Tatra Mountains and Austrian Alps to reconstruct CEU summer temperatures over the past three centuries. This new temperature history is compared to different sets of instrumental measurements and state-of-the-art climate model simulations. All records independently reveal the coolest conditions in the 1810s and warmest after 1996, but the ring width–based reconstruction overestimates the intensity and duration of the early nineteenth-century summer cooling by approximately 1.5°C at decadal scales. This proxy-specific deviation is most likely triggered by inflated biological memory in response to reduced warm season temperature, together with changes in radiation and precipitation following the Tambora eruption in April 1815. While suggesting there exists a specific limitation in ring width chronologies to capture abrupt climate perturbations with increased climate system inertia, the results underline the importance of alternative dendrochronological and wood anatomical parameters, including stable isotopes and maximum density, to assess the frequency and severity of climatic extremes.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    URL: Article
    DOI: 10.1175/JCLI-D-14-00673.1
    DOI: 10.1175/JCLI-D-14-00673.s1
    RVK:
    UA 4548
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2015
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 5
    Online Resource
    Online Resource
    Instrumental Meteorological Records before 1850: An Inventory
    American Meteorological Society ; 2020
    In:  Bulletin of the American Meteorological Society Vol. 101, No. 1 ( 2020-01), p. 43-47
    Details
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 101, No. 1 ( 2020-01), p. 43-47
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    URL: Article
    DOI: 10.1175/BAMS-D-19-0040.A
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2020
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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  • 6
    Online Resource
    Online Resource
    Planning for Compound Hazards during the COVID-19 Pandemic: The Role of Climate Information Systems
    American Meteorological Society ; 2022
    In:  Bulletin of the American Meteorological Society Vol. 103, No. 3 ( 2022-03), p. E704-E709
    Details
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 103, No. 3 ( 2022-03), p. E704-E709
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    URL: Article
    DOI: 10.1175/BAMS-D-21-0215.1
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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  • 7
    Online Resource
    Online Resource
    Atmospheric Forcing of Debris Flows in the Southern Swiss Alps
    American Meteorological Society ; 2013
    In:  Journal of Applied Meteorology and Climatology Vol. 52, No. 7 ( 2013-07), p. 1554-1560
    Details
    In: Journal of Applied Meteorology and Climatology, American Meteorological Society, Vol. 52, No. 7 ( 2013-07), p. 1554-1560
    Abstract: This article addresses the role of large-scale circulation and thermodynamical features in the release of past debris flows in the Swiss Alps by using classification algorithms, potential instability, and convective time scale. The study is based on a uniquely dense dendrogeomorphic time series of debris flows covering the period 1872–2008, reanalysis data, instrumental time series, and gridded hourly precipitation series (1992–2006) over the area. Results highlight the crucial role of synoptic and mesoscale forcing as well as of convective equilibrium on triggering rainfalls. Two midtropospheric synoptic patterns favor anomalous southwesterly flow toward the area and high potential instability. These findings imply a certain degree of predictability of debris-flow events and can therefore be used to improve existing alert systems.
    Type of Medium: Online Resource
    ISSN: 1558-8424 , 1558-8432
    URL: Article
    DOI: 10.1175/JAMC-D-13-077.1
    RVK:
    UA 4547
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2013
    detail.hit.zdb_id: 2227779-1
    detail.hit.zdb_id: 2227759-6
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  • 8
    Online Resource
    Online Resource
    On the Long-Term Climate Memory in the Surface Air Temperature Records over Antarctica: A Nonnegligible Factor for Trend Evaluation
    American Meteorological Society ; 2015
    In:  Journal of Climate Vol. 28, No. 15 ( 2015-08-01), p. 5922-5934
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 28, No. 15 ( 2015-08-01), p. 5922-5934
    Abstract: In this study, observed temperature records of 12 stations from Antarctica island, coastline, and continental areas are analyzed by means of detrended fluctuation analysis (DFA). After Monte Carlo significance tests, different long-term climate memory (LTM) behaviors are found: temperatures from coastal and island stations are characterized by significant long-term climate memory whereas temperatures over the Antarctic continent behave more like white noise, except for the Byrd station, which is located in the West Antarctica. It is argued that the emergence of LTM may be dominated by the interactions between local weather system and external slow-varying systems (ocean), and therefore the different LTM behaviors between temperatures over the Byrd station and that over other continental stations can be considered as a reflection of the different climatic environments between West and East Antarctica. By calculating the trend significance with the effect of LTM taken into account, and further comparing the results with those obtained from assumptions of autoregressive (AR) process and white noise, it is found that 1) most of the Antarctic stations do not show any significant trends over the past several decades, and 2) more rigorous trend evaluation can be obtained if the effect of LTM is considered. Therefore, it is emphasized that for air temperatures over Antarctica, especially for the Antarctica coastline, island, and the west continental areas, LTM is nonnegligible for trend evaluation.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    DOI: 10.1175/JCLI-D-14-00733.1
    RVK:
    UA 4548
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2015
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 9
    Online Resource
    Online Resource
    A Pseudoproxy Evaluation of Bayesian Hierarchical Modeling and Canonical Correlation Analysis for Climate Field Reconstructions over Europe*
    American Meteorological Society ; 2013
    In:  Journal of Climate Vol. 26, No. 3 ( 2013-02-01), p. 851-867
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 26, No. 3 ( 2013-02-01), p. 851-867
    Abstract: A pseudoproxy comparison is presented for two statistical methods used to derive annual climate field reconstructions (CFRs) for Europe. The employed methods use the canonical correlation analysis (CCA) procedure presented by Smerdon et al. and the Bayesian hierarchical model (BHM) method adopted from Tingley and Huybers. Pseudoproxy experiments (PPEs) are constructed from modeled temperature data sampled from the 1250-yr paleo-run of the NCAR Community Climate System Model (CCSM) version 1.4 model by Ammann et al. Pseudoproxies approximate the distribution of the multiproxy network used by Mann et al. over the European region of interest. Gaussian white noise is added to the temperature data to mimic the combined signal and noise properties of real-world proxies. Results indicate that, while both methods perform well in areas with good proxy coverage, the BHM method outperforms the CCA method across the entire field and additionally returns objective error estimates.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    DOI: 10.1175/JCLI-D-12-00016.1
    RVK:
    UA 4548
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2013
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 10
    Online Resource
    Online Resource
    Climate Model Biases and Modification of the Climate Change Signal by Intensity-Dependent Bias Correction
    American Meteorological Society ; 2018
    In:  Journal of Climate Vol. 31, No. 16 ( 2018-08), p. 6591-6610
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 31, No. 16 ( 2018-08), p. 6591-6610
    Abstract: Climate change impact research and risk assessment require accurate estimates of the climate change signal (CCS). Raw climate model data include systematic biases that affect the CCS of high-impact variables such as daily precipitation and wind speed. This paper presents a novel, general, and extensible analytical theory of the effect of these biases on the CCS of the distribution mean and quantiles. The theory reveals that misrepresented model intensities and probability of nonzero (positive) events have the potential to distort raw model CCS estimates. We test the analytical description in a challenging application of bias correction and downscaling to daily precipitation over alpine terrain, where the output of 15 regional climate models (RCMs) is reduced to local weather stations. The theoretically predicted CCS modification well approximates the modification by the bias correction method, even for the station–RCM combinations with the largest absolute modifications. These results demonstrate that the CCS modification by bias correction is a direct consequence of removing model biases. Therefore, provided that application of intensity-dependent bias correction is scientifically appropriate, the CCS modification should be a desirable effect. The analytical theory can be used as a tool to 1) detect model biases with high potential to distort the CCS and 2) efficiently generate novel, improved CCS datasets. The latter are highly relevant for the development of appropriate climate change adaptation, mitigation, and resilience strategies. Future research needs to focus on developing process-based bias corrections that depend on simulated intensities rather than preserving the raw model CCS.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    URL: Article
    DOI: 10.1175/JCLI-D-17-0765.1
    DOI: 10.1175/JCLI-D-17-0765.s1
    RVK:
    UA 4548
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2018
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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