pinecone/core-2020-05-10-deduplication huggingface dataset:
A cyclone climatology of the British-Irish Isles 1871-2012

This is the peer reviewed version of the following article: MATTHEWS, T.K.R. ... et al, 2015. A cyclone climatology of the British-Irish Isles 1871-2012. International Journal of Climatology, 36(3), pp. 1299–1312., which has been published in final form at http://dx.doi.org/10.1002/joc.4425. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.The British-Irish Isles (BI) lie beneath the North Atlantic storm track year-round and thus are impacted by the passage of extra-tropical cyclones. Given recent extreme storminess and projections of enhanced winter cyclone activity for this region, there is much interest in assessing the extent to which the cyclone climate of the region may be changing. We address this by assessing a 142-year (1871-2012) record of cyclone frequency, intensity and 'storminess' derived from the 20th Century Reanalysis V2 (20CR) dataset. We also use this long-term record to examine associations between cyclone activity and regional hydroclimate. Our results confirm the importance of cyclone frequency in driving seasonal precipitation totals which we find to be greatest during summer months. Cyclone frequency and storminess are characterized by pronounced interannual and multi-decadal variability which are strongly coupled to atmospheric blocking in the Euro-Atlantic region, but we detect no evidence of an increasing trend. We observe an upward trend in cyclone intensity for the BI region, which is strongest in winter and consistent with model projections, but promote caution interpreting this given the changing data quality in the 20CR over time. Nonetheless, we assert that long-term reconstruction is helpful for contextualizing recent storminess and for identifying emerging changes in regional hydroclimate linked to cyclones
Seasonal precipitation forecast skill over Iran

This paper examines the skill of seasonal precipitation forecasts over Iran using one two-tiered model, three
National Multi-Model Ensemble (NMME) models, and two coupled ocean–atmosphere or one-tiered models. These models
are, respectively, the ECHAM4.5 atmospheric model that is forced with sea surface temperature (SST) anomalies forecasted
using constructed analogue SSTs (ECHAM4.5-SSTCA); the IRI-ECHAM4.5-DirectCoupled, the NASA-GMAO-062012
and the NCEP-CFSv2; and the ECHAM4.5 Modular Ocean Model version 3 (ECHAM4.5-MOM3-DC2) and the
ECHAM4.5-GML-NCEP Coupled Forecast System (CFSSST). The precipitation and 850 hPa geopotential height fields of
the forecast models are statistically downscaling to the 0.5∘ × 0.5∘ spatial resolution of the Global Precipitation Climatology
Centre (GPCC) Version 6 gridded precipitation data, using model output statistics (MOS) developed through the canonical
correlation analysis (CCA) option of the Climate Predictability Tool (CPT). Retroactive validations for lead times of up
to 3 months are performed using the relative operating characteristic (ROC) and reliability diagrams, which are evaluated
for above- and below-normal categories and defined by the upper and lower 75th and 25th percentiles of the data record
over the 15-year test period of 1995/1996 to 2009/2010. The forecast models’ skills are also compared with skills obtained
by (a) downscaling simulations produced by forcing the ECHAM4.5 with simultaneously observed SST, and (b) the 850
hPa geopotential height NCEP-NCAR (National Centers for Environmental Prediction-National Center for Atmospheric
Research) reanalysis data. Downscaling forecasts from most models generally produce the highest skill forecast at lead times
of up to 3 months for autumn precipitation – the October-November-December (OND) season. For most seasons, a high skill
is obtained from ECHAM4.5-MOM3-DC2 forecasts at a 1-month lead time when the models’ 850 hPa geopotential height
fields are used as the predictor fields. For this model and lead time, the Pearson correlation between the area-averaged of the
observed and forecasts over the study area for the OND, November-December-January (NDJ), December-January-February
(DJF) and January-February-March (JFM) seasons were 0.68, 0.62, 0.42 and 0.43, respectivelyThe Fars Regional Water Organizationhttp://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-00882017-09-30hb2017Geography, Geoinformatics and Meteorolog
Complexity and predictability of the monthly Western Mediterranean oscillation index

The complexity, predictability and predictive instability of the Western Mediterranean Oscillation index (WeMOi) at monthly scale, years 1856-2000, are analysed from the viewpoint of monofractal and multifractal theories. The complex physical mechanism is quantified by: (1) the Hurst exponent, H, of the rescaled range analysis; (2) correlation and embedding dimensions, mu* and d(E), together with Kolmogorov entropy, kappa, derived from the reconstruction theorem; and (3) the critical Holder exponent, alpha(o), the spectral width, W, and the asymmetry of the multifractal spectrum, f(alpha). The predictive instability is described by the Lyapunov exponents, lambda, and the Kaplan-Yorke dimension, D-KY, while the self-affine character is characterized by the Hausdorff exponent, H-a. Relationships between the exponent beta, which describes the dependence of the power spectrum S(f) on frequency f, and the Hurst and Hausdorff exponents suggest fractional Gaussian noise (fGn) as a right simulation of empiric WeMOi. Comparisons are made with monthly North-Atlantic Oscillation and Atlantic Multidecadal Oscillation indices. The analysis is complemented with an ARIMA(p,1,0) autoregressive process, which yields a more accurate prediction of WeMOi than that derived from fGn simulations.Postprint (author's final draft
Prediction of inflows into Lake Kariba using a combination of physical and empirical models

Seasonal climate forecasts are operationally produced at various climate prediction centres around the world.
However, these forecasts may not necessarily be objectively integrated into application models in order to help
with decision-making processes. The use of hydro- meteorological models may be proven effective for reservoir
operations since accurate and reliable prediction of reservoir inflows can provide balanced solution to the
problems faced by dam or reservoir managers. This study investigates the use of a combination of physical and
empirical models to predict seasonal inflows into Lake Kariba in southern Africa. Two predictions systems are
considered. The first uses antecedent seasonal rainfall totals over the upper Zambezi catchment as predictor in a
statistical model for estimating seasonal inflows into Lake Kariba. The second and more sophisticated method
uses predicted low-level atmospheric circulation of a coupled ocean-atmosphere general circulation model
(CGCM) downscaled to the inflows. Forecast verification results are presented for five run-on 3-month seasons;
from September to June over an independent hindcast period of 14 years (1995/6 to 2008/9). Verification is
conducted using the relative operating characteristic (ROC) and the reliability diagram. In addition to the
presented verification statistics, the hindcasts are also evaluated in terms of their economic value as a usefulness
indicator of forecast quality for bureaucrats and to the general public. The models in general perform best during
the austral mid-summer season of DJF (seasonal onset of inflows) and the autumn season of MAM (main inflow
season). Moreover, the prediction system that uses the output of the CGCM is superior to the simple statistical
approach. An additional forecast of a recent flooding event (2010/11), which lies outside of the 14-year
verification window, is presented to further demonstrate the forecast system’s operational capability during a
season of high inflows that caused societal and infrastructure problems over the region.Applied Center for Climate and Earth
Systems Science (ACCESS)http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-00882017-05-30hb201
An evaluation of persistent meteorological drought using a homogeneous Island of Ireland precipitation network

This is the peer reviewed version of the following article: WILBY, R.L. ... et al, 2016. An evaluation of persistent meteorological drought using a homogeneous Island of Ireland precipitation network. International Journal of Climatology, 36 (8), pp. 2854-2865., which has been published in final form at http://dx.doi.org/10.1002/joc.4523. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.This paper investigates the spatial and temporal properties of persistent meteorological droughts using the homogeneous Island of Ireland Precipitation (IIP) network. Relative to a 1961–1990 baseline period it is shown that the longest observed run of below average precipitation since the 1850s lasted up to 5 years (10 half-year seasons) at sites in southeast and east Ireland, or 3 years across the network as a whole. Dry spell and wet spell length distributions were represented by a first-order Markov model which yields realistic runs of below average rainfall for individual sites and IIP series. This model shows that there is relatively high likelihood (p = 0.125) of a 5-year dry spell at Dublin, and that near unbroken dry runs of 10 years or more are conceivable. We suggest that the IIP network and attendant rainfall deficit modelling provide credible data for stress testing water supply and drought plans under extreme conditions
Long-term trends in precipitation and temperature across the Caribbean

This study considers long-term precipitation and temperature variability across the Caribbean using two gridded data sets (CRU TS 3.21 and GPCCv5). We look at trends across four different regions (Northern, Eastern, Southern and Western), for three different seasons (May to July, August to October and November to April) and for three different periods (1901–2012, 1951–2012 and 1979–2012). There are no century-long trends in precipitation in either data set, although all regions (with the exception of the Northern Caribbean) show decade-long periods of wetter or drier conditions. The most significant of these is for the Southern Caribbean region which was wetter than the 1961–1990 average from 1940 to 1956 and then drier from 1957 to 1965. Temperature in contrast shows statistically significant warming everywhere for the periods 1901–2012, 1951–2012 and for over half the area during 1979–2012. Data availability is a limiting issue over much of the region and we also discuss the reliability of the series we use in the context of what is known to be available in the CRU TS 3.21 data set. More station data have been collected but have either not been fully digitized yet or not made freely available both within and beyond the region
Interannual variability of heat waves in South Korea and their connection with large-scale atmospheric circulation patterns

This study investigates the interannual variation of heat wave frequency (HWF) in South Korea during the past 42 years (1973-2014) and examines its connection with large-scale atmospheric circulation changes. Korean heat waves tend to develop most frequently in late summer during July and August. The leading Empirical Orthogonal Function accounting for 50% of the total variance shows a mono-signed pattern over South Korea, suggesting that the dominant mechanisms responsible for the heat wave are linked in a spatial scale much larger than the nation. It also exhibits a regional variation with more occurrences in the southeastern inland area. The regression of the leading principal component (PC) time series of HWF with large-scale atmospheric circulation identifies a north-south dipole pattern between the South China Sea and Northeast Asia. When this large-scale circulation mode facilitates deep convection in South China Sea, it tends to weaken moisture transport from the South China Sea to Northeast Asia. Enhanced deep convection in the South China Sea triggers a source of Rossby wave train along southerly wind that generates positive geopotential height anomalies around Korea. The anomalous high pressure pattern is accompanied by large-scale subsidence in Korea, thereby providing a favourable condition for extreme hot and dry days in Korea. This study highlights that there is a decadal change of the relationship between Korean heat waves and large-scale atmospheric circulation patterns. The tropical forcing tends to be weakened in the recent decade, with more influences from the Arctic variability from the mid-1990s.ope
Greenland Blocking Index 1851-2015: a regional climate change signal

We present an extended monthly and seasonal Greenland Blocking Index (GBI) from January 1851 to December 2015, which more than doubles the length of the existing published GBI series. We achieve this by homogenizing the Twentieth Century Reanalysis version 2c-based GBI and splicing it with the NCEP/NCAR Reanalysis-based GBI. For the whole time period, there are significant decreases in GBI in autumn, October and November, and no significant monthly, seasonal or annual increases. More recently, since 1981 there are significant GBI increases in all seasons and annually, with the strongest monthly increases in July and August. A recent clustering of high GBI values is evident in summer, when 7 of the top 11 values in the last 165 years, including the two latest years 2014 and 2015, occurred since 2007. Also, 2010 is the highest GBI year in the annual, spring, winter and December series but 2011 is the record low GBI value in the spring and April series. Moreover, since 1851 there have been significant increases in GBI variability in May and especially December. December has also shown a significant clustering of extreme high and low GBI values since 2001, mirroring a similar, recently identified phenomenon in the December North Atlantic Oscillation index, suggesting a related driving mechanism. We discuss changes in hemispheric circulation that are associated with high compared with low GBI conditions. Our GBI time series should be useful for climatologists and other scientists interested in aspects and impacts of Arctic variability and change. Â© 2016 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society
Observed trends and changes in daily temperature and precipitation extremes over the Koshi river basin

The Koshi river basin is a sub-basin of the Ganges shared among China, Nepal, and India. The river system has a high potential for investment in hydropower development and for irrigation in downstream areas. The upper part of the basin contains a substantial reserve of freshwater in the form of snow and glaciers. Climate variability, climate change, and climate extremes might impact on these reserves, and in turn impact on systems that support livelihoods, such as agriculture, biodiversity and related ecosystem services. Climatological variability and trends over the Koshi river basin were studied using RClimDex. Daily temperature data (20 stations) and precipitation data (50 stations) from 1975 to 2010 were used in the analysis. The results show that the frequency and intensity of weather extremes are increasing. The daily maximum temperature (TXx) increased by 0.1 °C decade−1 on average between 1975 and 2010 and the minimum (TNn) by 0.3 °C decade−1. The number of warm nights increased at all stations. Most of the extreme temperature indices showed a consistently different pattern in the mountains than in the Indo-Gangetic plains, although not all results were statistically significant. The warm days (TX90p), warm nights (TN90p), warm spell duration (WSDI), and diurnal temperature range (DTR) increased at most of the mountain stations; whereas monthly maximum and minimum values of daily maximum temperature, TX90p, cool nights (TN10p), WSDI, cold spell duration indicator (CSDI), DTR decreased at the stations in the Indo-Gangetic plains, while the number of cold days increased. There was an increase in total annual rainfall and rainfall intensity, although no clear long-term linear trend, whereas the number of consecutive dry days increased at almost all stations. The results indicate that the risk of extreme climate events over the basin is increasing, which will increase people's vulnerability and has strong policy implications
ICOADS Release 3.0: a major update to the historical marine climate record

We highlight improvements to the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) in the latest Release 3.0 (R3.0; covering 1662–2014). ICOADS is the most widely used freely available collection of surface marine observations, providing data for the construction of gridded analyses of sea surface temperature, estimates of air–sea interaction and other meteorological variables. ICOADS observations are assimilated into all major atmospheric, oceanic and coupled reanalyses, further widening its impact. R3.0 therefore includes changes designed to enable effective exchange of information describing data quality between ICOADS, reanalysis centres, data set developers, scientists and the public. These user-driven innovations include the assignment of a unique identifier (UID) to each marine report – to enable tracing of observations, linking with reports and improved data sharing. Other revisions and extensions of the ICOADS' International Maritime Meteorological Archive common data format incorporate new near-surface oceanographic data elements and cloud parameters. Many new input data sources have been assembled, and updates and improvements to existing data sources, or removal of erroneous data, made. Coupled with enhanced ‘preliminary’ monthly data and product extensions past 2014, R3.0 provides improved support of climate assessment and monitoring, reanalyses and near-real-time applications
Tropospheric moisture in the Southwest Pacific as revealed by homogenized radiosonde data : climatology and decadal trend.

Radiosonde data are valuable to the research community because they provide observations for multiple decades and can be used to validate model output. However radiosonde data often suffer from quality issues, which has undermined their credibility. Therefore, corrections for biases and changepoints are needed to remedy the situation. Homogenization of monthly radiosonde specific humidity (q) from the 1970s to the present has been performed on selected stations over the Southwest Pacific (SWP) at three pressure levels (i.e. 850, 700 and 500 hPa). A three-step procedure involving (1) adjustments for two sampling biases, (2) detecting secular changepoints (i.e. discontinuities) using both statistical techniques and metadata validation, and (3) an innovative break size estimate approach, has been implemented to achieve this aim. In the last step, a discontinuity-free pseudo-q is constructed from saturated specific humidity qs which itself is derived from an already homogenized temperature (T) time series. This pseudo-q serves as a reference that not only distinguishes artificial from natural changepoints but also helps to estimate the magnitudes of the discontinuity. On the decadal time scale, the adjusted q (qadj) exhibits spatially more consistent moistening at the 850 hPa level over most of the region and a contrast at 500 hPa between the moistening in the tropics and a drying in the subtropical South Pacific. Mean regional trend estimates are ∼1.8% (850 hPa), −0.2% (700 hPa) and 1.3% (500 hPa) per decade. A climatological comparison with the three latest reanalysis products – CFSR, ERA-Interim and MERRA, suggests the reanalyses have significant negative biases over Southeast Asia (SEA) at all three levels. Over Australia the biases are negative at 850 hPa while positive at 500 hPa. The reanalysis products tend to be more similar among themselves in the estimates of q, as compared to the radiosonde measurements of q and qadj. The homogenized radiosonde q, when assimilated into reanalysis, is likely to lead to a more realistic model of the hydrological cycle
Factors causing climatologically high temperatures in a hottest city in Japan: a multi-scale analysis of Tajimi

In this study, multi-scale climatological features of extreme high temperature (EHT) events in Tajimi, the hottest cities in Japan, were investigated using observational data collected by the Japan Meteorological Agency over the past 23 years, and original data observed by the authors over the last 3 years. Results revealed the background factors that lead to climatologically high temperatures in Tajimi: the occurrence of a characteristic pressure pattern called ‘whale’: the synoptic-scale factors, and the urbanization of Tajimi: the meso-γ-scale factors. In addition, the high temperatures measured in Tajimi are affected by the foehn-like westerly airflow coming from the mountains located in the northwest/west towards the Nobi Plain where Tajimi is located at the east end: the meso-β-scale factors, and the location of the Tajimi observation site, which is within an urbanized area where the highest temperatures tend to be observed: the micro-scale factors. In contrast, statistical analysis demonstrated that the small-scale basin effects and soil dryness around Tajimi were of lesser importance than aforementioned factors, in the occurrence of EHT events in Tajimi
Spatial reconstruction of Scottish summer temperatures from tree rings

The authors wish to thank The Carnegie Trust for the Universities of Scotland for providing funding for Miloš Rydval’s PhD. The Scottish pine network expansion has been an ongoing task since 2006 and funding must be acknowledged to the following projects: EU project ‘Millennium’ (017008-2), Leverhulme Trust project ‘RELiC: Reconstructing 8000 years of Environmental and Landscape change in the Cairngorms (F/00 268/BG)’ and the NERC project ‘SCOT2K: Reconstructing 2000 years of Scottish climate from tree rings (NE/K003097/1)’. We also thank Rider University for a faculty research fellowship that supported Daniel Druckenbrod, and Paul J. Krusic for compiling and making available a PC version of the point-by-point PCR software. Lamont-Doherty Earth Observatory contribution No. 8032.A detailed understanding of past temporal patterns and spatial expression of temperature variations is important to place recent anthropogenic climate change into a longer term context. In order to fill the current gap in our understanding of northwest European temperature variability, point-by-point principal component regression was used to reconstruct a spatial field of 0.5° temperature grids across Scotland. A sequence of reconstructions utilizing several combinations of detrending and disturbance correction procedures, and a selection of tree-ring parameters [including ring width (RW), maximum latewood density (MXD) and blue intensity (BI)] was used in an evaluation of reconstruction skill. The high resolution of the reconstructed field serves also as a diagnostic tool to spatially assess the temperature reconstruction potential of local chronologies. Best reconstruction results, reaching calibration r2 = 65.8% and verification r2 = 63.7% in central Scotland over the 1901–1976 period, were achieved using disturbance-corrected and signal-free detrended RW chronologies merged with BI data after low-pass (high-pass) filtering the RW (BI) chronologies. Calibration and verification r2 > 50% was attained for central, north and east Scotland, >40% in west and northwest, and >30% in southern Scotland with verification of nearly all grids showing some reconstruction skill. However, the full calibration potential of reconstructions outside central Scotland was reduced either due to residual disturbance trends undetected by the disturbance correction procedure or due to other climatic or non-climatic factors which may have adversely affected the strength of the climate signal.PostprintPeer reviewe