pinecone/core-2020-05-10-deduplication huggingface dataset:
ENSO teleconnections to the Indian summer monsoon in observations and models

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this recordThe teleconnections of different types of El Niño Southern Oscillation (ENSO) to the Indian summer monsoon are investigated in observations and models. We find that, not all regions in India are strongly affected by ENSO, so we focus on two regional teleconnections: (1) a negative rainfall signal around central north east (CNE) India and ‘hilly’ region during El Niño (and vice versa for La Niña) and (2) similar signal for parts of southern peninsular region. Using correlations, it is found that >50% of the fifth phase of the Coupled Model Inter-comparison Project models capture these two regional teleconnections, with first captured by >80% of models. Furthermore, using a compositing technique that may better capture asymmetries in response to warm and cold events, the authors find that most models again agree on the sign of regional teleconnection around the CNE and hilly region, suggesting the robustness of ENSO signal in that region. The peninsular teleconnection is less well simulated in models. We find a clear connection between the Walker circulation and Indian summer monsoon rainfall around central India in models.This work is done under SAPRISE (South Asian precipitation: a seamless assessment) project, NERC number NE/I022841/1. I.R. also acknowledges the funding from ReCoVER project, UK
Surface temperature trends from homogenized time series in South Africa : 1931-2015

Previous assessments of historical trends of measured surface temperature in South Africa have all
shown a general upward trend, in both mean and extreme values, over recent decades. In addition,
some regional differences in trends have been identified. Most of these studies focused on the period
from about 1961 up to the last year that could be included before publication, as only climate stations
situated in the same position for the entire analysis period were analysed. A data homogenisation
procedure enabled the combination of time series of stations from which trend analysis could be
applied, extending the common analysis period for this study back to around 1931. The trend results,
based on the WMO ETCCDI indices, continue to show the general warming trend shown in previous
analyses, with a general increase in extreme warm events, and a general decrease in extreme cold
events across South Africa. The analysis of seasonal trends show that, while there are noteworthy
differences on a regional basis, austral summer shows on average the strongest warming, followed by
autumn, winter and spring. The central interior, which exhibited significant cooling in previous
analyses, now shows non-significant or similar trends when compared to the other parts of South
Africa. There is no countrywide acceleration in the warming trends, but some regional consistencies
in the temporal changes in trends could be determined, i.e. increases in trends in the central interior
and decreases in trends along most of the coastal region.http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-00882018-04-30hb2017Geography, Geoinformatics and Meteorolog
Decrease in climatic conditions favouring floods in the south-east of Belgium over 1959-2010 using the regional climate model MAR

The Ourthe River, in the south-east of Belgium, has a catchment area of 3,500 km2 and is one of the main tributaries of the Meuse River. In the Ourthe, most of the flood events occur during winter and about 50% of them are due to heavy rainfall events combined to an abrupt melting of the snowpack covering the Ardennes massif during winter. This study aims to determine whether trends in extreme hydroclimatic events generating floods can be detected over the last century in Belgium, where a global warming signal can be observed. Hydroclimatic conditions favourable to floods were reconstructed over 1959- 2010 using the regional climate model MAR (“Modèle Atmosphérique Régional”) forced by the ERA-Interim/ERA-40, the ERA-20C and the NCEP/NCAR-v1 reanalyses. Extreme run-off events, which could potentially generate floods, were detected using run-off caused by precipitation events and snowpack melting from the MAR model. In the validation process, the MAR-driven temperature, precipitation and snow depth were successfully compared to daily weather data over the period 2008-2014 for 20 stations in Belgium. MAR also showed its ability to detect up to 90% of the hydroclimatic conditions which effectively generated observed floods in the Ourthe River over the period 1974- 2010. Conditions favourable to floods in the Ourthe River catchment present a negative trend over the period 1959-2010 as a result of a decrease in snow accumulation and a shortening of the snow season. This trend is expected to accelerate in a warmer climate. However, regarding the impact of the extreme precipitation events evolution on conditions favouring floods, the signal is less clear since the trends depend on the reanalysis used to force the MAR model.Peer reviewe
Hierarchical structures in Northern Hemispheric extratropical winter ocean-atmosphere interactions

In recent years extensive studies on the Earth’s climate system have been carried out by means of advanced\ud
complex network statistics. The great majority of these studies, however, have been focusing on investigating correlation\ud
structures within single climatic fields directly on or parallel to the Earth’s surface. Here, we develop a novel approach of\ud
node weighted coupled network measures to study correlations between ocean and atmosphere in the Northern Hemisphere\ud
extratropics and construct 18 coupled climate networks, each consisting of two subnetworks. In all cases, one subnetwork\ud
represents monthly sea-surface temperature (SST) anomalies, while the other is based on the monthly geopotential height\ud
(HGT) of isobaric surfaces at different pressure levels covering the troposphere as well as the lower stratosphere. The\ud
weighted cross-degree density proves to be consistent with the leading coupled pattern obtained from maximum covariance\ud
analysis. Network measures of higher order allow for a further analysis of the correlation structure between the two fields and\ud
consistently indicate that in the Northern Hemisphere extratropics the ocean is correlated with the atmosphere in a hierarchical\ud
fashion such that large areas of the ocean surface correlate with multiple statistically dissimilar regions in the atmosphere.\ud
Ultimately we show that this observed hierarchy is linked to large-scale atmospheric variability patterns, such as the Pacific\ud
North American pattern, forcing the ocean on monthly time scales
Uncertainty assessment for climate change impact on intense precipitation: How many model runs do we need?

Programme’s Working Group on Coupled Modelling – phase 5 (CMIP5), and the climate modeling centres involved in that programme. The work has been funded by projects for the Belgian Science Policy Office (CORDEX.be), the Flemish Environment Agency, and the European Union’s Horizon 2020 research and innovation programmes under grant agreement No 700699, project BRIGAID (BRIdges the GAp for Innovations in Disaster project PUCS (Pan-European Urban Climate Service).Precipitation projections are typically obtained from general circulation model (GCM) outputs under different future scenarios, then downscaled for hydrological applications to a watershed or site-specific scale. However, uncertainties in projections are known to be present and need to be quantified. Although GCMs are commonly considered the major contributor of uncertainty for hydrological impact assessment of climate change, other uncertainty sources must be taken into account for a thorough understanding of the hydrological impact. This study investigates uncertainties related to GCMs, GCM initial conditions and representative concentration pathways (RCPs) and their sensitivity to the selection of GCM runs in order to quantify the impact of climate change on extreme precipitation and intensity/duration/frequency statistics. The results from a large ensemble of 140 CMIP5 GCM runs including 15 GCMs, 3–10 GCM initial conditions and 4 RCPs are analysed. Albeit the choice of GCM is the major contributor (up to 65% for some cases) to intense precipitation change uncertainty for all return periods (1 year, 10 years) and aggregation levels (1-, 5-, 10-, 15- and 30-day), uncertainties related to the GCM initial
conditions and RCPs of up to 38 and 23%, respectively, are found in some cases. The sensitivity analysis reveals that the GCM, RCP and GCM initial condition uncertainties are greatly influenced by the set of climate model runs considered, especially for more extreme precipitation at finer time scales.status: publishe
Changing U.S. Extreme Temperature Statistics

The rise in global mean temperature is an incomplete description of warming.
For many purposes, including agriculture and human life, temperature extremes
may be more important than temperature means and changes in local extremes may
be more important than mean global changes. We define a nonparametric statistic
to describe extreme temperature behavior by quantifying the frequency of local
daily all-time highs and lows, normalized by their frequency in the null
hypothesis of no climate change. We average this metric over 1218 weather
stations in the 48 contiguous United States, and find significantly fewer
all-time lows than for the null hypothesis of unchanging climate. Record highs,
by contrast, exhibit no significant trend. The metric is evaluated by Monte
Carlo simulation for stationary and warming temperature distributions,
permitting comparison of the statistics of historic temperature records with
those of modeled behavior.Comment: 10 pp., 3 fig
Changing patterns of daily precipitation totals at the Coweeta Hydrologic Laboratory, North Carolina, USA.

A pattern of increasing frequency and intensity of heavy rainfall over land has been documented for several temperate regions and is associated with climate change. This study examines the changing patterns of daily precipitation at the Coweeta Hydrologic Laboratory, North Carolina, USA, since 1937 for four rain gauges across a range of elevations. We analyse seasonal total rainfall, number of rain days and the frequency of heavy rainfall. We compare these with several teleconnections, including the Bermuda High Index (BHI), the West BHI, the North Atlantic Oscillation (NAO) and the El Niño-Southern Oscillation. Our data show a tendency for increased variability, including major periods of drought, with fewer rain days recently, especially in summer. Only autumn tended to have increases in rainfall frequency and magnitude; this is the season when orographic enhancement is at its strongest. The major driver of precipitation at Coweeta is the strength of the Bermuda High. The strength of the NAO is important in summer. The results are relevant to the southeast United States in general, given that the region comes under the influence of similar air masses during the year. The findings are applicable to the wider Appalachian Mountains and to other mountainous regions where there is significant orographic enhancemen
EURO-CORDEX regional climate model simulation of precipitation on Scottish islands (1971-2000): Model performance and implications for decision-making in topographically complex regions

Due to their scale and complex topography, islands such as the Hebrides and Shetland Islands are not fully resolved by global climate models, which may impact the quality of data that can be provided about future climate in such locations. In principle, dynamical downscaling may provide helpful additional detail about future local climate. However, there is also the potential for error and uncertainty to cascade through to the regional simulation. Here, we evaluate the simulative skill of the EURO-CORDEX regional climate model ensemble on regional and local scales in the Hebrides and Shetland Islands, and consider the potential for such models to aid decision-making in island settings, and other locations characterised by complex topography. Several precipitation indices (accumulated precipitation amount, mean daily precipitation amount, max 1-day and 5-day precipitation amounts, simple daily intensity, number of heavy and very heavy precipitation days) are used to assess model performance and identify bias relative to observations. Models are compared regionally, and at specific locations, namely Stornoway in the Hebrides and Lerwick in Shetland, for the period 1971-2000.  Regional evaluation utilises the UKCP09 gridded observational dataset and local evaluation at Stornoway Airport and Lerwick utilises observed mean precipitation and extreme indices from the European Climate Assessment & Dataset project. While no models perform skilfully across all the metrics studied, some models capture aspects of the precipitation climate at each location particularly well. Differences in model performance between the two case study sites highlight the value of evaluating models on multiple spatial scales. The implications of model uncertainty for decision-making are also discussed
North Atlantic circulation indices: links with summer and winter UK temperature and precipitation and implications for seasonal forecasting

UK seasonal mean temperature and precipitation conditions are extremely variable from one year to the next but in the last decade have featured several cool, wet summers and mild, wet winters interspersed with some notable cold winter episodes. Jet stream variability is a major determinant of these fluctuations, and is often represented by the North Atlantic Oscillation (NAO) index. Recent work has shown some evidence of promising predictability in the winter NAO from one to two months ahead, while summer predictability remains very limited. Although the phase and magnitude of the NAO influences total UK rainfall, there are regional variations which it does not explain. Here we examine the relationship between UK regional summer and winter precipitation and temperature and a range of North Atlantic atmospheric circulation indices. While the NAO shows a significant relationship with temperature in both seasons and summer rainfall over most of the UK, the picture in winter is more complicated with other circulation indices such as the East Atlantic pattern explaining rainfall anomalies in southern England. Other indices also show significant relationships with precipitation in regions where the NAO does not.\ud
Since UK weather is determined by the interplay between different circulation indices, attention should be given to developing seasonal forecasts of other circulation indices to complement the NAO forecasts. We also find that some potential drivers of jet stream variability are significantly associated with UK temperature and rainfall variability,\ud
particularly in summer. This provides further scope for producing seasonal forecasts based directly on these drivers. Improved seasonal forecasts will be useful to a range of end users in agriculture, energy supply, transport and insurance industries and can be extended to other UK weather variables such as extreme rainfall events and storm frequency, and related metrics such as wind power capacity and solar energy
Estimation of near‐surface air temperature lapse rates over continental Spain and its mountain areas

40 Pags.- 8 Figs.- 3 Tabls.  The definitive version is available at:  https://rmets.onlinelibrary.wiley.com/journal/10970088Although the mean environmental lapse rate (MELR) value (a linear decrease of −6.5 °C/km) is the most widely used, near‐surface (i.e., non‐free atmosphere) air temperature lapse rates (NSLRs; measured at ~1.5 m height) are variable in space and time because of their dependence on topography and meteorological conditions. In this study we conducted the first analysis of the spatial and temporal variability of NSLRs for continental Spain and their relationship to synoptic atmospheric circulation (circulation weather types [CWTs]), focusing on major mountain areas including the Pyrenees, Cantabrian, Central, Baetic, and Iberian ranges.\ud
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The results showed that the NSLR varied markedly at spatial and seasonal scales and depended on the dominant atmospheric conditions. The median NSLR values were weaker (less negative) than the MELR for the mountain areas (Pyrenees −5.17 °C/km; Cantabrian range −5.22 °C/km; Central range −5.78 °C/km; Baetic range −4.83 °C/km; Iberian range −5.79 °C/km) and for the entire continental Spain (−5.28 °C/km). For the entire continental Spain the steepest NSLR values were found in April (−5.80 °C/km), May (−5.58 °C/km), and October (−5.54 °C/km) because of the dominance of northerly and westerly advections of cold air. The weakest NSLR values were found in July (−4.67 °C/km) and August (−4.78 °C/km) because of the inland heating, and in winter because of the occurrence of thermal inversions. As the use of the MELR involves the assumption of large errors, we propose 1 zonal, 12 monthly, 11 CWTs, and 132 hybrid monthly–CWTs NSLRs for each of the mountain ranges and for the entire continental Spain. More regional studies are urgently needed to accurately assess the NSLR as a function of atmospheric circulation conditions.This study was funded by the research projects CGL2014‐52599‐P “Estudio del manto de nieve en la montaña española y su respuesta a la variabilidad y cambio climatico” and CLIMPY “Characterization of the evolution of climate and provision of information for adaptation in the Pyrenees” (FEDER‐POCTEFA). F.N.‐S. and M.T.‐B. are granted with a pre‐doctoral FPU grant (Spanish Ministry of Education, Culture and Sports) and C.A.‐M. has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska‐Curie grant agreement no. STILLING project‐703733.Peer reviewe
Tree-ring-based precipitation reconstruction in the source region of Weihe River, northwest China since AD 1810

A tree-ring width chronology of Picea purpurea Mast from Mt. Shouyang in the source region of Weihe River (SWR), northwest China, was developed in this study. Correlation analysis showed that the precipitation from previous August to current July was the limiting climate factor of tree growth. Using a reliable and stable linear regression model, which explained 42.6% of the variance of the actual precipitation during the calibration period from 1958 to 2014, a 205-year long precipitation series was reconstructed for the SWR. The dry years in the reconstruction were well supported by historical documents, and famous historical droughts were also recorded in the dry periods of a low-frequency scale of the reconstructed precipitation. As demonstrated by the spatial correlation patterns, the reconstructed series compared well with other hydroclimate records for northwest China, indicating that it could represent large-scale hydroclimate changes. The 2-8-year interannual cycles and the interdecadal quasiperiods of 15.9 years and 18.6 years revealed that the precipitation in this region was probably affected by the El Nino-Southern Oscillation and North Atlantic Oscillation. The dry/wet years corresponded well with the El Nino/La Nina events and the SWR commonly experienced droughts during the low periods of North Atlantic Oscillation
Adjustment of measurement errors to reconcile precipitation distribution in the high-altitude Indus basin

Precipitation in the high‐altitude Indus basin governs its renewable water resources affecting water, energy and food securities. However, reliable estimates of precipitation climatology and associated hydrological implications are seriously constrained by the quality of observed data. As such, quantitative and spatio‐temporal distributions of precipitation estimated by previous studies in the study area are highly contrasting and uncertain. Generally, scarcity and biased distribution of observed data at the higher altitudes and measurement errors in precipitation observations are the primary causes of such uncertainties. In this study, we integrated precipitation data of 307 observatories with the net snow accumulations estimated through mass balance studies at 21 major glacier zones. Precipitation observations are adjusted for measurement errors using the guidelines and standard methods developed under the WMO's international precipitation measurement intercomparisons, while net snow accumulations are adjusted for ablation losses using standard ablation gradients. The results showed more significant increases in precipitation of individual stations located at higher altitudes during winter months, which are consistent with previous studies. Spatial interpolation of unadjusted precipitation observations and net snow accumulations at monthly scale indicated significant improvements in the quantitative and spatio‐temporal distribution of precipitation over the unadjusted case and previous studies. Adjustment of river flows revealed only a marginal contribution of net glacier mass balance to river flows. The adjusted precipitation estimates are more consistent with the corresponding adjusted river flows. The study recognized that the higher river flows than the corresponding precipitation estimates by the previous studies are mainly due to underestimated precipitation. The results can be useful for water balance studies and bias correction of gridded precipitation products for the study area
Tropical rainfall predictions from multiple seasonal forecast systems

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We quantify seasonal prediction skill of tropical winter rainfall in 14 climate forecast systems. High levels of seasonal prediction skill exist for year‐to‐year rainfall variability in all tropical ocean basins. The tropical East Pacific is the most skilful region, with very high correlation scores, and the tropical West Pacific is also highly skilful. Predictions of tropical Atlantic and Indian Ocean rainfall show lower but statistically significant scores.\ud
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We compare prediction skill (measured against observed variability) with model predictability (using single forecasts as surrogate observations). Model predictability matches prediction skill in some regions but it is generally greater, especially over the Indian Ocean. We also find significant inter‐basin connections in both observed and predicted rainfall. Teleconnections between basins due to El Niño–Southern Oscillation (ENSO) appear to be reproduced in multi‐model predictions and are responsible for much of the prediction skill. They also explain the relative magnitude of inter‐annual variability, the relative magnitude of predictable rainfall signals and the ranking of prediction skill across different basins.\ud
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These seasonal tropical rainfall predictions exhibit a severe wet bias, often in excess of 20% of mean rainfall. However, we find little direct relationship between bias and prediction skill. Our results suggest that future prediction systems would be best improved through better model representation of inter‐basin rainfall connections as these are strongly related to prediction skill, particularly in the Indian and West Pacific regions. Finally, we show that predictions of tropical rainfall alone can generate highly skilful forecasts of the main modes of extratropical circulation via linear relationships that might provide a useful tool to interpret real‐time forecasts.\u