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There is an urgent need to understand and predict how extreme precipitation events (EPEs) will change at high latitudes, both for local climate change adaptation plans and risk mitigation and as a potential proxy "anticipating" the impact of climate change elsewhere in the world. This paper illustrates that a combination of non‐stationary modelling approaches can be adopted to evaluate trends in EPEs under uncertainty. A large database of daily rainfall events from 281 sparsely distributed weather stations in Finland between 1961 and 2016 was analysed. Among the tested methods, Poisson distributions provided a powerful method to evaluate the impacts of multiple physical covariates, including temperature and atmospheric circulation patterns (ACPs), on the resulting trends. The analysis demonstrates that non‐stationarity is statistically valid for the majority of observations, independently of their location in the country and the season of the year. However, subsampling can severely hinder the statistical validity of the trends, which can be easily confused with random noise and therefore complicate the decision‐making processes regarding long‐term planning. Scaling effects have a strong impact on the estimates of non‐stationary parameters, as homogenizing the data in space and time reduces the statistical validity of the trends. Trends in EPE statistics (mean, 90 and 99% percentiles) and best‐fitted Generalized Pareto parameters in the tails of the distributions appear to be stronger when approaching the Polar region (Lapland) than away from it, consistent with the Arctic amplification of climate change. ACPs are key covariates in physically explaining these trends. In particular, the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) can explain statistically significant increases in extreme precipitation in Lapland, Bothnian and South regions of Finland, particularly during summer and fall seasons. Non‐stationarity is statistically valid in the majority of observations but masked by subsampling and spatio‐temporal heterogeneity. Trends on extremes and non‐stationary generalized Pareto parameters stronger when approaching the Polar region (Lapland). Artic Oscillation (AO) and North Atlantic Oscillation (NAO) can explain statistically significant trends. [ABSTRACT FROM AUTHOR]

In the paper we focus on the notes of botanist and meteorologist Gottfried Reyger on the weather conditions in Gdańsk, Poland. In our estimation, this chronicle, covering the period from December 1721 to June 1786 (the longest weather chronicle recorded by a single person), is a reliable source of information with the potential to contribute to the understanding of climate variability in 18th‐century Gdańsk, the significant old Hanseatic city in northern Poland. The temperature and precipitation series for the period 1721–1786 were indexed against contemporary conditions using the calculated percentages of cold, normal and warm decades. The climate in the 18th century in Gdańsk was colder than nowadays; the springs were much cooler, as were the winters, while the summers were warmer. A few relatively cold periods and several warm periods were identified. The first half of the analysed period was very humid, whereas the second was quite dry. The reconstructed indexed data series were compared to annual and seasonal mean values of air temperature and precipitation derived from regular instrumental observations made in Gdańsk since 1739. The linear regression method was applied to calibrate the reconstructed index series against anomalies from the 1961–1990 average. The correlation coefficient, standard error of estimate and the root‐mean‐square error statistics were used to diagnose the quality of calibration and verification. The highest correlation between the temperature indices and the observational series was found for winter. The reconstructed series for precipitation has a smaller variability than in reality. The reconstructed values for the years prior to 1739 indicate cold years for 1725–1732 and a wet period in the 1730s. The chronicle of botanist and meteorologist Gottfried Reyger, covering the period 1721–1786, characterizes the thermal and precipitational conditions in Gdańsk, Poland. The series were indexed against contemporary conditions, compared with instrumental data and reconstructed for early non‐instrumental period. The 18th‐century Gdańsk was colder than nowadays, particularly on case of springs, while the summers were warmer. The first decades of the period were very humid, whereas the latter ones quite dry. In the figure, annual air temperature (left panel) and precipitation (right panel) reconstruction for Gdańsk for the period 1722–1785 presented in the context of observational series, 1739–1785 for air temperature and 1739–1772 for precipitation. Solid line shows observational data; dotted line shows reconstructed series. [ABSTRACT FROM AUTHOR]

Recent studies have focused on identifying the spatial coverage of heavy rainfall associated with tropical cyclones (TCs) and their remnants (TC‐events) throughout the southwestern United States from eastern North Pacific storms. Yet little is known about the larger spatial contribution of these storms among extreme floods over the western United States. This paper examines the spatial and fractional contribution of 103 TC‐events among annual maximum streamflow at 1,429 long‐term U.S. Geological Survey (USGS) streamgages with at least 30 years of daily discharge data over the 1958–2010 water years. The highest fractional contributions to annual daily maxima by these storms (~5–14%) are found in southern California, Arizona, southernmost Nevada and Utah, southern and western New Mexico, central Colorado, and Texas. While nearly 32% of the streamgages have at least one annual maximum that was generated by a TC‐event, TC‐events play a limited role in contributing to the upper tail of the flood peak distribution across the western United States. [ABSTRACT FROM AUTHOR]

In recent years, numerous studies have investigated the relationship of extreme precipitation intensities with temperature derived from a binning method using present‐day weather data. The aim of this approach is that these dependencies, or so‐called apparent scaling rates, provide insights on how precipitation extremes could evolve in the future climate. In a recent paper, Bao et al. showed that there is a large discrepancy between the present‐day apparent scaling rates—showing a negative dependency of daily rainfall extremes on temperature for Darwin—and the climate change response showing a substantial increase in daily rainfall extremes. Their results provide compelling evidence that it may not be straightforward to predict the climate change response from the temperature scaling. We agree with this statement, but disagree with the physical explanation put forward in that study and think that moisture limitations are the most likely cause. Therefore, we advocate the use of dew point temperatures in scaling studies as a much more direct proxy of the absolute humidity of the air in which precipitation extremes develop, which we think is physically more consistent with the underlying mechanism causing the increase in precipitation extremes with global warming. [ABSTRACT FROM AUTHOR]

There are two aims of this paper: First, the relationship between daily and hourly precipitation extremes and air temperature is investigated for the validity of Clausius–Clapeyron (C–C) scaling; second, the impact of the atmospheric circulation and transport of humidity on the extreme precipitation events occurrence in Poland is analysed based on data obtained from 26 stations across Poland in the period 1951–2015. It was shown that daily‐scale extreme rainfall is less sensitive to changes in local atmospheric temperature but the hourly intensities reveal a similar behaviour at all stations showing a robust signal over the entire country. Regarding the impact of the large‐scale atmospheric circulation, three types were distinguished in cool part of the year: one connected with the positive phase of the North Atlantic Oscillation (NAO), second with a low‐pressure zone in the north and high‐pressure in the south of Europe and the northern Atlantic and third with a low over central Europe. Each time high precipitation in Poland was connected with the advection of humid air from the western sectors (SW, W or NW). In the warm part of the year three types were distinguished too, Poland was always in the scope of low‐pressure systems with the advection of warm air from the southern sectors or when the warm air from the south meets the colder air from the north. Similar localizations of low centres have been found in the case of local‐scale atmospheric circulation types during events with extreme precipitation. Both in cool and warm part of the year such events are connected with the increase of water vapour in the air. In cool season the wet and warm air masses inflow to Poland the most often from Atlantic, in the warm season—from Mediterranean and/or Black Seas. [ABSTRACT FROM AUTHOR]

In this paper we analyse the relationship between the mean and extreme precipitation for five stations in Hungary and the circulation types at the 500 hPa level, for a 52‐year period, 1958–2010. We used daily rainfall data for each station and a calendar of the daily circulation types at the 500 hPa geopotential height for Hungary based on an automatic classification scheme. A trend analysis showed that, in general, the mean and extreme precipitation rarely exhibit significant trends, similarly to previous studies. The only exception was found for the number of annual and summer rainy days in Budapest with significant negative trends (p = .05), as well as the number of days with rainfall amounts greater than the 95% probability level for Debrecen with a significant positive trend. It was found that the circulation types that are mainly responsible for the largest precipitation amounts overall show (in some cases significant) negative trends, as well as the precipitation amounts that are associated with them (Cwsw, Cse, Cwnw). In most cases, the circulation types that are prevailing during the extreme precipitation events are associated with western or almost‐western atmospheric circulations (Cwsw, Ase) and Mediterranean‐ or Atlantic‐origin depressions. [ABSTRACT FROM AUTHOR]

The precipitation over arid regions may be low, but its environmental impacts can be very dramatic. The decadal variability in precipitation can also effectively disturb climatic environmental regimes. To advance the understanding of precipitation variability over arid regions, this paper focuses on decadal variability in summer precipitation over arid northwest China and its associated atmospheric circulations, using observation‐based data and atmospheric reanalysis during the period 1961–2016. The results show that climatologically, precipitation over this region has a strong seasonality and that 60.2% falls in summer. The summer precipitation increased 15.5 mm, accounting for 52.4% of the total annual increase in this part of China from 1961 to 2016. Decadal changes in summer precipitation occurred in approximately 1991 with a north–south difference structure modulated by large‐scale circulation anomalies over the Indian Ocean and central Asia as well as a shift in water vapour transport. In a positive phase, anticyclonic circulation anomalies occupy the Indian Ocean with cyclonic anomalies over central Asia, favouring stronger northwards moisture transport towards northwest China, and vice versa. Moreover, the significantly enhanced northwards water vapour transport from low‐latitude seas is also critical to the decadal changes approximately in 1991 summer precipitation in arid northwest China. These findings contribute to the understanding of decadal precipitation variability over arid regions, especially the increasing influence of low‐latitude circulations and moisture transport processes. [ABSTRACT FROM AUTHOR]

ABSTRACT: Extreme precipitation events are widely thought to intensify in a warmer atmosphere through the Clausius‐Clapeyron equation. The temperature‐extreme precipitation scaling was proposed to analyse the temperature dependency of short‐duration extreme precipitation and since then, the concept has been widely used in climatology. Bao et al. (2017) suggest that the apparent scaling reflects not only how surface air properties affect extreme precipitation, but also reflects how synoptic conditions and localized cooling due to the storm itself affect the scaling – implying two‐way causality. We address here critical issues of this paper and provide evidence that dew point temperature drives extreme precipitation, with the direction of causality reversed only for the storm's peak intensity. This physical inference may serve as a basis to better quantify scaling rates and to help establish the relationship between extreme precipitation and environmental conditions in the current climate, and thereby provide insights into future changes to precipitation extremes due to climate change. [ABSTRACT FROM AUTHOR]

ABSTRACT: The estimated future changes of precipitation and precipitation‐related climate indices for the Carpathian Region are analysed in this paper. Eleven regional climate model (RCM) simulations from the ENSEMBLES project taking into account the intermediate A1B emission scenario are used, hence, the analysis also includes uncertainty assessments. Validation results showed that in the target area RCM simulations overestimate precipitation throughout the year, except in summer, when underestimation occurs. In order to eliminate these systematic errors before the detailed analysis, percentile‐based bias correction is applied to the raw RCM outputs, for which the high‐quality CARPATCLIM database (1961–2010) serves as a reference. Using the bias‐corrected RCM simulations, precipitation totals and several precipitation‐related indices (describing both wet and dry climatic conditions) are calculated for the 1961–2100 time period on seasonal scale for the entire Carpathian Region, and also for five subregions (Slovakia, Ukraine, Hungary, Romania, and Serbia) within this area. The results from RCM simulations are inconsistent for some indices in some seasons, thus introducing uncertainties to the climatic projections. However, according to our results, drier summers are very likely to occur in the future, mainly in the southern parts of the selected domain. More frequent and more intense extreme precipitation events are estimated for winter and autumn, especially in the northern regions. Our conclusions suggest that the spatial distribution of precipitation is not likely to change remarkably in the future, however, the annual distribution of precipitation is projected to be restructured. [ABSTRACT FROM AUTHOR]

This paper analyses the daily precipitation data recorded for the last 75-80 years in SE Spain. Prior to statistical analysis, homogeneity tests were performed to determine the usefulness of the data (recorded in six pluviometric stations). If the data were homogeneous, the Mann–Kendall test was performed to detect monotonic trends for variables such as total precipitation, number of days with precipitation greater than 1, 20 or 40 mm, number of consecutive dry days and number of consecutive wet days. Moreover, the linear tendency was calculated and accepted (or rejected) by performing a Student's t-test of the calculated residual values. The results showed, on average, a clear change in precipitation patterns for the last 20 years. Annual rainfall had decreased, with values ranging from 0 to 15%, dry periods had increased in length, and the number of rainy days had decreased (especially when high daily precipitation was considered). This latter notion did not exactly concur with the conclusions of the Intergovernmental Panel on Climate Change (IPCC) 2014 Synthesis Report related to the study area. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper analyses the influence of different types of El Niño-Southern Oscillation ( ENSO) events on South American precipitation under a climate change scenario. We use two sub-selections of Coupled Model Intercomparison Project Phase 5 (CMIP5) models that have a good representation of teleconnections to the region, albeit with reduced magnitude anomalies. Comparing historical simulations and the RCP 8.5 scenario experiments, after removing the trend in the mean due climate change, the sub-ensemble means show similar global sea surface temperature anomalies and South American precipitation anomaly patterns in the future. No robust changes in the pattern or magnitude of precipitation anomalies are found, despite significant ENSO-related shifts in the Pacific basin, as highlighted in other studies. However, if the models are analysed individually, some show relatively strong changes in ENSO-related precipitation anomalies for both canonical and Modoki events. We show that, in individual models, tropical teleconnection changes associated with ENSO are primarily driven by changes in the magnitude of ENSO-related circulation but with no agreement on the sign. Increases in background moisture, which have been hypothesized to drive an intensification of ENSO-related precipitation anomalies, are of secondary importance. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper documents the changes in climate extremes over Indonesia during the past three decades (1983-2012) based on a subset of extreme indices recommended by the Expert Team on Climate Change Detection and Indices ( ETCCDI). The extreme indices were calculated based on the quality controlled daily observational data (minimum and maximum temperature and precipitation) from 88 weather stations. Overall, we found significant and spatially coherent trends of warming in the temperature indices over Indonesia, consistent with other studies conducted at different countries within the Southeast Asia. The frequency of cool days ( TX10p) and cools nights ( TN10p) had decreased whereas warm days ( TX90p) and warm nights ( TN90p) were observed more frequently. Averaged over the country, the annual mean of daily maximum ( TXmean) and minimum temperature ( TNmean) had increased significantly by 0.18 and 0.30 °C decade−1, respectively. Other temperature indices also showed significant warming trends. In contrast, trends in the precipitation extremes indices were generally not significant and less spatially coherent. However, a tendency towards wetter conditions was observed, in agreement with the results at the global scale. The daily precipitation intensity ( SDII) had increased significantly over the country by 0.21 mm day−1 decade−1 during the period studied. At the regional scale, we observed a significant wetting trend in the annual highest daily amount ( RX1day) and the rainfall amount contributed by the extremely very wet days (R99p) in the northern part of the country. The wetting trends of a number of extreme precipitation indices were depicted prominently in December-January-February ( DJF) and/or March-April-May ( MAM) seasons, both at country and regional levels. However, for the southern region of Indonesia, a drying tendency was observed for June-July-August ( JJA), September-October-November ( SON) and MAM. [ABSTRACT FROM AUTHOR]

ABSTRACT The temporal concentration of precipitation may be characterized using several methods. For climate-scale precipitation, concentration measures are usually performed by means of dimensionless indices such as the Gini index ( GI) or the Theil index. For the purposes of the present paper, a set of 66 409 daily time series from around the world were analysed to estimate the climatic concentration of precipitation. To this end, some of the most widely used indices were tested, i.e. the Theil index, the Gini index, the concentration index, the classic n index and an ordered version of the n index. Results show a strong connection between several indices, mainly between the GI and the ordered n index. The high correlation of these indices ( R = 0.98) reflects a theoretical connection between the shape and integration of the Lorenz curve. With regard to spatial distribution, the three main indices present the same relative areas of high and low concentration. The high temporal concentration of precipitation is generally linked to the rapid pace of physical processes such as convection in areas with a high degree of insolation and warm seas. The low temporal concentration of rainfall can be interpreted as a consequence of regular patterns (maritime flows or highly recurrent storms). A relationship between the number of rainy days and concentration indices was noted; however, their correlation depends on the region analysed. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper revisits the strength and stationarity of linear statistical relationships between indices of monsoon rainfall derived from rain gauge data for three regions in tropical West Africa [West Sahel (WS), Central Sahel (CS), and Guinea Coast (GC)] and various indices describing remote variations in the ocean-atmosphere climate systems from 1921 to 2009. The results reveal that both the Atlantic Multi-decadal Oscillation ( AMO) and the Atlantic Meridional Mode ( AMM) show a positive linear correlation to Sahel rainfall. The percent variance explained ( PVE) ranges from 10 to 25%. The correlation stems from periods longer than 8 years for AMO, but AMM does show a correlation on interannual time scales for WS that was absent in the 1970s and 1980s. The PVE by El Niño Southern Oscillation ( ENSO) indices is, though statistically significant, on the order of 10% and found mainly on the interannual time scale. A strong and stable correlation with PVEs larger than 50% is found between the sea surface temperatures (SSTs) in the Atlantic 3 region ( ATL3, 0°-20°W, 3°S-3°N) and the GC rainfall. On the other hand, the correlation between ATL3 and WS rainfall changed from significantly negative to significantly positive after the 1970s. The Eastern Mediterranean SSTs are found to be significantly related to CS rainfall, especially in recent years with PVEs between 36 and 47%. Multi-linear regression analyses reveal that the relative importance of the Indian Ocean is 42% in the optimal regression model. For the CS, this value is 37% for the Eastern Mediterranean SSTs and 70% in case of the GC using the ATL3 index. However, except for the GC, non-stationarities in the correlation between the climate state indexes and West African monsoon ( WAM) rainfall suggest the need of the application of different regression models depending on the active 'teleconnection regime'. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper presents an analysis of winter climate variability based on daily mean temperature and precipitation data since 1970 in the Chic-Chocs Mountain range (located in the Gaspé Peninsula, Eastern Quebec, Canada). Mountain environments are particularly sensitive to rapid climate change and are therefore good indicators of recent global warming. The main goal of this study is to demonstrate how joint probability temperature/precipitation distributions can be used to estimate winter condition changes (trends) for six meteorological stations in the study area (the altitudinal range for the stations is from 5 to 574 m). The presence and persistence of snow cover was also estimated. Previous studies have shown a lack of evidence of significant trends in snow-cover characteristics (density, depth and snow water equivalent (SWE)) from the early 1980s to the present, despite an increase in temperature over the same period. A reanalysis of these data sets in addition to the use of a combination of temperature and precipitation data categorized into four modes (warm/wet, warm/dry, cold/wet and cold/dry) was also performed. Despite this new analysis, no clear evidence of climate change could be found in the study area over the last four decades. The results revealed that patterns and trends are quite different from one station to another, but when the environment is taken into account (valley or plateau, coastal versus inland) some apparent patterns emerge. [ABSTRACT FROM AUTHOR]

In a changing climate, it is likely that precipitation patterns will experience shifts in amount and seasonality, with a tendency towards increased drought in many parts of Europe. In order to investigate what could be some of the feedbacks of dry conditions on temperature, this paper has investigated close to 30 European locations to assess the influence of observed dry summer days on daily maximum temperature ( Tmax) as well as a clustering of rainless days, and finally the temperature impact related to drought conditions as defined by the Standardized Precipitation Index. The results show that for the three main European climatic regions investigated ('Mediterranean', 'Maritime', 'Continental'), the influence of rainless days is discernible, with an average difference between mean summer Tmax and Tmax during rainless days only of up to 1.5 °C. A further aim of the study is to determine whether recent shifts in the occurrence of rainless days during the summer have a bearing on temperature trends. Results show that shifts in rainless days explain only a fraction of the observed temperature change at the locations studied, thereby hinting that the enhanced greenhouse effect remains the dominant mechanism for temperature change. Finally, using a regional climate model, very preliminary insight into a 'greenhouse climate' highlights the fact that changes in dry conditions seem to confirm the findings for current climate, i.e. they account for only a fraction of the increase in temperatures. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Empirical statistical downscaling has been widely used to produce finer-resolution climate data. This approach, in general, is derived from an implicit stationarity assumption. This paper aims at proving a statistical method that is fully applicable of generating daily precipitation in non-stationary conditions using historical station data. Daily records at five Oklahoma stations were split into calibration and validation periods. Linear relationships between transition probabilities of wet-following-wet ( P w/ w) and wet-following-dry ( P w/ d) days and mean monthly precipitation were established by connecting the two endpoints (one for the 30 driest months and another for the 30 wettest months of the calibration period) for each calendar month, and were then used to interpolate P w/ w and P w/ d for the validation period. The mean and standard deviation of daily precipitation were estimated using the mean and standard deviation of monthly precipitation of the validation periods as well as the interpolated P w/ w and P w/ d. The adjusted parameters were used to generate daily series using a weather generator. Statistics of the disaggregated daily precipitation amounts and frequency, as well as dry/wet spell sequence, agreed with those of the observed values of the validation periods reasonably well. The disaggregation method preserved statistics of monthly precipitation amounts extremely well, demonstrating the validity of the method for temporal disaggregation of non-stationary climate. The accuracy of the presented method is within the weather generator's expected performance. Overall, a straight line connecting the two endpoints, implicitly incorporating non-stationarity of climate states, is adequate for interpolating P w/ w and P w/ d to any climatic conditions within the entire range. However, a linear regression including data points in between would generally improve the P w/ w and P w/ d interpolations slightly if long records (e.g. > 60 years) are available for estimating the intermediate points. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

One way in which global climate model (GCM) output can be utilized to infer local impacts is through the use of synoptic climatology: creating a set of atmospheric patterns that capture the variability in the climate system, and then analyzing trends and variability in the frequency of these patterns moving into the future. In this paper, we demonstrate a new synoptic climatological technique for classifying atmospheric patterns that can be used in conjunction with GCM output data (in this case, the Community Climate System Model 3). We apply this method to 850-hPa temperature patterns over the contiguous United States to derive daily categorizations. A total of 15 clusters are created from the data set; once the mean GCM bias is removed, historical cluster frequencies in the GCM data set are not statistically different from those of the reanalysis data set. In the future, significant changes in frequency are observed across most of the transition season clusters, as they broaden in seasonality at the expense of winter clusters, some of which nearly entirely disappear. Changes are greater moving further into the future, and greater for the more carbon-intensive special report on emissions scenarios (SRES) scenarios (A1FI, A2) than the less-intensive scenario tested (B1). Diagnostics test how well the mean patterns of the reanalysis data set, GCM historical data set and the future GCM data sets resemble each other. For some clusters, mean bias between the historical and future data sets grows substantially by the end of the 21st century under the more carbon-intensive scenarios. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The study of the temporal-spatial variability of dry sequences and the probability of their occurrence are particularly important in understanding the impact of climate change on droughts. This paper analyses the different properties of dry sequences, focussing on extreme condition, analysing their degree of spatial coherence, and their temporal variability. For the study, daily precipitation data are used for the period 1961-2000 throughout Argentina. The region north of 40°S is divided in two from the meridian of 63°W with highly differentiated 'dry' properties. The eastern region is more homogeneous where mean dry sequences last less than six days and long sequences of about 60 days. The Andean region shows a marked east-west gradient in any of the above properties, with extreme values of over 10 days (mean sequences) and 150 days (the longest sequences). At the seasonal level the above properties reflect a differential pattern according to the time of year under study. In the case of summer, when the dry sequences can be more harmful to crops, the maximum duration in the Pampa region can extend to about 25 days. Owing to the problems that dry sequences of over 30 days can produce in the different ecosystems and based on the above findings, the temporal-spatial variability is analysed, and a variability over the years, together with a progressive decrease in the occurrence of such events, is found. The study of extreme dry events provides useful tools that can be applied to different hydrological and agricultural needs. Furthermore, our climatological findings help validate climate models. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Climate change is commonly evaluated as the difference between simulated climates under future and current forcings, based on the assumption that systematic errors in the current-climate simulation do not affect the climate-change signal. In this paper, we investigate the Canadian Regional Climate Model (CRCM) projected climate changes in the climatological means and extremes of selected basin-scale surface fields and its sensitivity to model errors for Fraser, Mackenzie, Yukon, Nelson, Churchill and Mississippi basins, covering the major climate regions in North America, using current (1961-1990) and future climate simulations (2041-2070; A2 and IS92a scenarios) performed with two versions of CRCM. Assessment of errors in both model versions suggests the presence of nonnegligible biases in the surface fields, due primarily to the internal dynamics and physics of the regional model and to the errors in the driving data at the boundaries. In general, results demonstrate that, in spite of the errors in the two model versions, the simulated climate-change signals associated with the long-term monthly climatology of various surface water balance components (such as precipitation, evaporation, snow water equivalent (SWE), runoff and soil moisture) are consistent in sign, but differ in magnitude. The same is found for projected changes to the low-flow characteristics (frequency, timing and return levels) studied here. High-flow characteristics, particularly the seasonal distribution and return levels, appear to be more sensitive to the model version. CRCM climate-change projections indicate an increase in the average annual precipitation for all basins except Mississippi, while annual runoff increases in Fraser, Mackenzie and Yukon basins. A decrease in runoff is projected for Mississippi. A significant decrease in snow cover is projected for all basins, with maximum decrease in Fraser. Significant changes are also noted in the frequency, timing and return levels for low flows. Copyright © 2006 Royal Meteorological Society. [ABSTRACT FROM AUTHOR]

This paper combines a wide‐area assessment of forecast changes in wintertime synoptic conditions over western North America with a meso‐scale alpine hydrometeorology model to evaluate the impacts of forecast climate change on snowpack conditions in an alpine watershed. The synoptic analysis was used to generate long‐term climate time series scenarios using the Canadian Centre for Climate Modelling and Analysis first‐generation coupled general circulation model (GCM). The alpine hydrometeorology model SIMGRID is used to predict changes in wintertime precipitation at the watershed scale. The SNOPAC model is a simple snow model that predicts the overall snow accumulation throughout a watershed based on the output from SIMGRID. A vapour transfer model has been incorporated into the SNOPAC model to estimate snow volumes more accurately. The model is applied to a small alpine watershed in the southern Canadian Rockies. The synoptic analysis and GCM output forecasts a modest increase in both winter precipitation and temperatures in the study area. The hypothesis herein is that the increase in winter precipitation due to synoptic conditions will not compensate for regional changes in the rain‐to‐snow ratios. The net result will be a decline in winter accumulations of precipitation as snow, and hence an expected decline in spring runoff. Copyright © 2005 Royal Meteorological Society. [ABSTRACT FROM AUTHOR]

This paper studies the temporal and spatial patterns of precipitation anomalies over southern central South America (SCSA; 22–40°S and 54–70°W), and their relationship with the sea-surface temperature (SST) variability over the surrounding tropical and subtropical Atlantic and Pacific Oceans. The data include monthly precipitation from 68 weather stations in central–northern Argentina and neighbouring Brazil, Paraguay and Uruguay, and monthly SSTs from the NOAA dataset with a 2° resolution for the period 1961–93. We use the method of canonical correlation analysis (CCA) to study the simultaneous relationship between bi-monthly precipitation and SST variability. Before applying the CCA procedure, standardized anomalies are calculated and a prefiltering is applied by means of an empirical orthogonal function (EOF) analysis. Thus, the CCA input consists of 10 EOF modes of SST and between 9 and 11 modes for precipitation and their corresponding principal components, which are the minimum number of modes necessary to explain at least 80% of the variance of the corresponding field. The results show that November–December presents the most robust association between the SST and SCSA precipitation variability, especially in northeastern Argentina and southern Brazil, followed by March–April and May–June. The period January–February, in contrast, displays a weak relationship with the oceans and represents a temporal minimum of oceanic influence during the summer semester. Based on the CCA maps, we identify the different oceanic and SCSA regions, the regional averages of SST and precipitation are calculated, and linear correlation analysis are conducted. The periods with greater association between the oceans and SCSA precipitation are November–December and May–June. During November–December, every selected region over SCSA reflects the influence of several oceanic regions, whereas during May–June only a few regions show a direct association with the oceans. The Pacific Ocean regions have a greater influence and are more widespread over SCSA; the Atlantic Ocean regions have an influence only over the northwestern and the southeastern parts of SCSA. In general, the relationship with the equatorial and tropical Atlantic and Pacific Oceans is of the type warm–wet/cold–dry, whereas the subtropical regions of both oceans show the opposite relationship, i.e. warm–dry/cold–wet. Copyright © 2004 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

This paper describes a limited-area, reduced-process model of the large-scale physics of precipitation developed for predicting over climatic timescales. It represents an intermediate approach between a general circulation model (GCM) and full-physics model of precipitation at high resolutions. The model is designed for application in palaeoclimate modelling, specifically as input to ice-sheet models. The model is used to predict seasonal precipitation for the UK, using sea-surface temperatures, topography, mean wind speed and direction. Modelled data are compared with the United Kingdom Climate Impacts Programme (UKCIP) baseline climatologies for the UK and are shown, for westerly and southwesterly winds, to produce precipitation distributions and magnitudes which are in good agreement with the UKCIP data. The modelled data are much more spatially heterogeneous, reflecting the physical nature of the parameterization of the influence of orography. The model's sensitivity to temperature, wind speed and wind direction and its potential for driving ice-sheet models over long timescales are demonstrated. Copyright © 2000 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

When a correlation-based circulation pattern classification was applied to daily 700 hPa heights for 25 summer seasons, and the circulation types were related to surface temperature and precipitation for the Lake Superior basin, within-type variability was found to be high. Regarding temperature, the difference between warm and cold days of a type is a positive height anomaly centred to the east of the lake, which is very similar to the height anomaly for winter temperatures identified in an earlier study. The difference between wet and dry days of a type is a pattern quite unlike that for temperature. It is a dipole pattern consisting of a negative anomaly to the northwest of the lake and a positive anomaly to the east and southeast. These small-scale circulation components were missed by the correlation-based classification because they are much smaller than the differences in height between circulation types. Regression models, relating monthly mean temperature anomalies to circulation type frequencies, produced results comparable to those obtained for winter temperature. For precipitation, the variance explained by the regression models is only half that obtained for temperature. Two approaches were used to reduce within-type variability and to improve the regression results: the division of the first few circulation types into warm/cold and wet/dry subtypes on the basis of differences in 700 hPa vorticity (an approach introduced in the earlier paper), and a modified correlation-based circulation pattern classification. The modification consisted of raising the correlation threshold for a few selected grid-points to capture the small-scale circulation component and also, of lowering the threshold for the comparison between maps and map sectors in order to minimize the number of unclassified days. Of the two approaches used to reduce within-type variability, the modified classification scheme produced superior results. In particular, the variance in precipitation explained by the regression models is about 30% higher than that achieved using vorticity to create subtypes. Copyright © 2000 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

This paper is part of a research programme devoted to the analysis of historical climate in Spain. A reconstruction of rainfall characteristics in Southern Spain from 1500 to the present is described. Weather information was taken from original documentary sources in the region. A numerical index was established to characterize the rainfall and its evolution. Results were calibrated with modern precipitation data and with the results of other studies of historical climate. The main objective is to obtain a long precipitation record. A preliminary analysis of the obtained series shows a fluctuating behavior with alternating dry and wet periods. The wettest periods occurred at the end of 16th century, the beginning of 17th century, and at the end of 19th century. The driest periods in the pre-instrumental era occurred during the first half of the 16th century, and around 1750. A general decreasing trend in precipitation can be observed from 1960 onwards. Copyright © 1999 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Interest in climatic change has never been greater and it is inevitable that the search for periodicities in the climatic record should be a popular means of attempting to unravel at least some of the complexities of the atmospheric system. This paper reviews aspects of the methodologies of spectral analysis and takes the example of the Barcelona precipitation series (1850–1991) to illustrate how both spectral analysis and other statistical analyses can provide information on climatic evolution as expressed through the medium of this one variable. Copyright © 1999 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

ABSTRACT In a recent article, Diem (2012) examined the impact of the North Atlantic Subtropical High ( NASH) and atmospheric moistening on summer rainfall variability in the Atlanta, Georgia region. In his paper, he indicated that the results concerning the variability of the NASH western ridge discussed in Li et al. (2011) are incorrect. We present new evidence here to show that the comments by Diem (2012) are unjustified; the main conclusions in Li et al. (2011) were drawn according to the data over a 60-year (1948-2007) and 45-year (1958-2002) periods of NCEP/ NCAR and ERA-40 reanalysis, whereas conclusions of Diem (2011) were based upon the trend analysis of a similar but different index of the NASH using sub-periods of 1948-2009 (since late 1970s). The comment emphases the importance of climate dynamics to study precipitation variability over the Southeastern US and further strengthens the conclusions originally put forth in Li et al. (2011): over the last 60 years (1948-2007), the NASH has shown a significant trend of westward movement, and the meridional movement of the NASH western-ridge (i.e. its latitudinal change) has enhanced in the recent three decades. [ABSTRACT FROM AUTHOR]

Spatial‐resolution errors are inherent in gridded precipitation (P) fields—such as those produced by climate models and from satellite observations—and they can be sizeable when P is averaged spatially onto a coarse grid. They can also vary dramatically over space and time. In this paper, we illustrate the importance of evaluating resolution errors associated with gridded P fields by investigating the relationships between grid resolution and resolution error for monthly P within the Amazon Basin.Spatial‐resolution errors within gridded‐monthly and average‐monthly P fields over the Amazon Basin are evaluated for grid resolutions ranging from 0.1° to 5.0°. A resolution error occurs when P is estimated for a location of interest within a grid‐cell from the unbiased, grid‐cell average P. Graphs of January, July and annual resolution errors versus resolution show that, at the higher resolutions (<3° ), aggregation quickly increases resolution error. Resolution error then begins to level off as the grid becomes coarser. Within the Amazon Basin, the largest resolution errors occur during January (summer), but the largest percentage errors appear in July (winter). In January of 1980, e.g., resolution errors of 29, 52 and 65 mm—or 11, 19 and 24% of the grid‐cell means—were estimated at resolutions of 1.0°, 3.0° and 5.0°. In July of 1980, however, the percentage errors at these three resolutions were considerably larger, that is, 15%, 27% and 33% of the grid‐cell means. Copyright © 2005 Royal Meteorological Society [ABSTRACT FROM AUTHOR]