Search

This paper highlights detailed projected changes in rainfall over Thailand for the early (2011–2040), middle (2041–2070) and late (2071–2099) periods of the 21st century under the representative concentration pathways (RCP) 4.5 and RCP 8.5 using the high‐resolution multi‐model simulations of the Coordinated Regional Climate Downscaling Experiment (CORDEX) Southeast Asia. The ensemble mean is calculated based on seven members consisting of six general circulation models (GCMs) and three regional climate models (RCMs). Generally, the ensemble mean precipitation agrees reasonably well with observations, best represented by the Global Precipitation Climatology Center (GPCC) data, over Thailand during the historical period (1976–2005). However, inter‐model variations can be large among ensemble members especially during dry months (December to March) for northern‐central‐eastern parts, and throughout the year for the southern parts of Thailand. Similarly for future projection periods, inter‐model variations in the sign and magnitude of changes exist. The ensemble means of projected changes in rainfall for both RCPs during dry months show distinct contrast between the northern‐central‐eastern parts and the southern parts of Thailand with generally wetter and drier conditions, respectively. The magnitude of change can be as high as 15% of the historical period, which varies depending on the sub‐region, season, projection period, and RCP scenario. In contrast, generally drier conditions are projected during the wet season (June to September) throughout the country for both RCPs where the rainfall reduction can be as high as 10% in some areas. However, the magnitude of projected rainfall changes of some individual models can be much larger than the ensemble means, exceeding 40% in some cases. These projected changes are related to the changes in regional circulations associated with the winter and summer monsoons, which are projected to weaken. The drier (wetter) condition is associated with the enhanced subsidence (rising motion). [ABSTRACT FROM AUTHOR]

In this paper, we evaluate a 48‐member multiphysics ensemble using the Weather Research and Forecasting (WRF) model for the JJA extreme precipitation and temperature in 2003 over the CORDEX‐EA‐II domain. The simulated precipitation and temperature are reasonable in the subregions controlled by a large‐scale circulation, yet the biases for both precipitation and temperature are evident over the subregions where the effects of mesoscale processes are important. The performance of various combinations of WRF physical schemes for simulating the JJA precipitation is dependent on the region. Meanwhile, the cumulus and microphysical schemes have substantial influences on the simulation of precipitation, and the land surface models and cumulus schemes play crucial roles in the surface temperature. Our analysis shows that the combination of Noah for the land surface process, Lin for the microphysics, G3D for the cumulus parameterization, and CAM for the radiation scheme can provide the most reliable reproduction of both precipitation and temperature extremes over China. Ensemble analysis shows that the simulated climate extremes are usually accompanied by a large ensemble spread, implying sensitivities to the model physical processes in some subregions. The simulated wind fields at low‐to‐middle atmospheric levels display responses to the options of the land surface models and cumulus schemes. The essential impact of the land–atmospheric interaction on simulating the extremes can be largely attributed to the active convective processes. WRF has difficulties in reproducing the observed temporal evolution of the rainfall process, which consists of continuous large rainfall episodes in the observation data set during the simulation period. [ABSTRACT FROM AUTHOR]

The 1981–2010 monthly precipitation climatologies for Norway at 1 km resolution are presented. They are computed by an interpolation procedure (HCLIM+RK) combining the output from a numerical model with the in situ observations. Specifically, the regional climate model data set HCLIM‐AROME, based on the dynamical downscaling of the global ERA‐Interim reanalysis onto 2.5 km resolution, is considered together with 2009 rain‐gauges located within the model domain. The precipitation climatologies are defined by superimposing the grid of 1981–2010 monthly normals from the numerical model and the kriging interpolation of station residuals. The combined approach aims at improving the quality of gridded climatologies and at providing reliable precipitation gradients also over those remote Norwegian regions not covered by observations, especially over the northernmost mountainous areas. The integration of rain‐gauge data greatly reduces the original HCLIM‐AROME biases. The HCLIM+RK errors obtained from the leave‐one‐out station validation turn out to be lower than those provided by two considered interpolation schemes based on observations only: a multi‐linear local regression kriging (MLRK) and a local weighted linear regression (LWLR). As average over all months, the mean absolute (percentage) error is 10.0 mm (11%) for HCLIM+RK, and 11.4 (12%) and 11.6 mm (12%) for MLRK and LWLR, respectively. In addition, by comparing the results at both station and grid cell level, the accuracy of MLRK and LWLR is more sensitive to the spatial variability of station distribution over the domain and their interpolated fields are more affected by discontinuities and outliers, especially over those areas not covered by the rain‐gauge network. The obtained HCLIM+RK climatologies clearly depict the main west‐to‐east gradient occurring from the orographic precipitation regime of the coast to the more continental climate of the inland and it allows to point out the features of the climatic subzones of Norway. The paper presents the 1981–2010 monthly precipitation climatologies over Norway at 1‐km grid spacing. The climatologies are computed by an interpolation scheme (HCLIM+RK) combining the in situ observations with the regional climate model data set HCLIM‐AROME, based on the dynamical downscaling of the global ERA‐Interim reanalysis. The comparison with methods using observations only proved that HCLIM+RK improves the accuracy of Norwegian climatologies and provides reliable precipitation patterns also over the remote areas not covered by rain‐gauges. [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]

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 The development of Adapted Caussinus-Mestre Algorithm for homogenising Networks of Temperature series ( ACMANT), one of the most successful homogenisation methods tested by the European project COST ES0601 ( HOME) has been continued. The third generation of the software package ' ACMANT3' contains six programmes for homogenising temperature values or precipitation totals. These incorporate two models of the annual cycle of temperature biases and homogenisation either on a monthly or daily time scale. All ACMANT3 programmes are fully automatic and the method is therefore suitable for homogenising large datasets. This paper describes the theoretical background of ACMANT and the recent developments, which extend the capabilities, and hence, the application of the method. The most important novelties in ACMANT3 are: the ensemble pre-homogenisation with the exclusion of one potential reference composite in each ensemble member; the use of ordinary kriging for weighting reference composites; the assessment of seasonal cycle of temperature biases in case of irregular-shaped seasonal cycles. ACMANT3 also allows for homogenisation on the daily scale including for break timing assessment, gap filling and ANOVA application on the daily time scale. Examples of efficiency tests of monthly temperature homogenisation using artificially developed but realistic test datasets are presented. ACMANT3 can be characterized by improved efficiency in comparison with earlier ACMANT versions, high missing data tolerance and improved user friendliness. Discussion concerning when the use of an automatic homogenisation method is recommended is included, and some caveats in relation to how and when ACMANT3 should be applied are provided. [ABSTRACT FROM AUTHOR]

An important limitation of commonly used single-site rainfall models is that they are not able to reflect spatial characteristics, while many impact studies demand the accommodation of spatial rainfall correlations. As a result, a number of stochastic models have been developed to produce precipitation simultaneously at multiple sites. One of these models is the Wilks approach [1998. Journal of Hydrology 210: 178-191], which was the first method that sufficiently reproduces the main statistics of rainfall at a number of sites. So far, however, the literature does not provide many details about the 'step by step' procedure proposed by Wilks. In this paper, the Wilks approach is demonstrated for multi-site, daily rainfall occurrences and amounts in the Gaza Strip. The paper demonstrates a complete methodology taking into account the original Wilks approach and suggests solutions for enhancing the model. The first improvement concerns an analytical calculation of the desired correlations in the random numbers that reproduce the observed correlations between the rainfall occurrence series, through a gamma coefficient. Secondly, the correlations between the rainfall amount series are specified using a rank correlation and then linearly transformed into product-moment correlations to obtain the required correlations in the random numbers. Statistical analyses on the historical and generated rainfall series confirm that the model generally performs well, as it preserves all major characteristics of daily rainfall, as well as spatial characteristics. Major advantages of this model include its simplicity, its increased efficiency, a significant improvement in computational speed and a considerable gain in the effort for the implementation. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, a 10-year daily accumulated precipitation analysis of Madeira highland is presented, as well as the relationship between meridional water vapour transport during 10 winter seasons and the precipitation recorded in the island during the same period. Here, the meridional water vapour transport is considered as occurring in narrow corridors known as atmospheric rivers - ARs - which were visually identified in the total precipitable water vapour field extracted from Atmospheric Infrared Sounder ( AIRS) data within a domain covering the North Atlantic Ocean. European Centre for Medium-range Weather Forecasts ( ECMWF) analysis was also used when necessary. Daily precipitation during the period covered by the study evidenced generally dry summers, whereas the highest values for daily accumulated precipitation were recorded mainly during the winter and also during the autumn and spring. Image analysis shows that moist air originating mainly in the Caribbean Sea flows northward or eastward, intersecting, on some occasions, the island during the winter season, often during a stage of dissipation. The orientation of the flow and the amount of water vapour transported to the island are important features, contributing to the occurrence of significant precipitation events. In fact, the moist environment created by ARs may favour the occurrence of precipitation, but this is not the sole factor favouring high rainfall over Madeira. [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]

ABSTRACT In Simpson and Jones (2012) we introduced new, homogenized UK national and regional rainfall series derived from 5 km gridded daily and monthly precipitation data. The monthly series were extended back to 1766 for monthly England and Wales ( EW) precipitation, to 1873 for monthly values for each of the five EW sub-regions, and to 1931 for daily values in all regions. Using data from those series, this paper provides analysis of how mean precipitation totals and extremes have changed over the respective periods. The results showed statistically significant upward trends in mean and extreme winter, spring and autumn precipitation for some Scottish regions, but trends over England and Wales were mostly insignificant, though England and Wales had a significant increase in winter precipitation over 1766-2011. The trend in summer precipitation over 1931-2011 has been statistically insignificant, though with a significant long-term downward trend for England and Wales over 1766-2011. Prior observations of a trend towards drier summers and wetter winters have been complicated by a recent succession of wet summers and dry winters. Many of the observed changes in seasonal precipitation totals are most likely associated with changes in the North Atlantic Oscillation. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper describes the construction of an updated gridded climate dataset (referred to as CRU TS3.10) from monthly observations at meteorological stations across the world's land areas. Station anomalies (from 1961 to 1990 means) were interpolated into 0.5° latitude/longitude grid cells covering the global land surface (excluding Antarctica), and combined with an existing climatology to obtain absolute monthly values. The dataset includes six mostly independent climate variables (mean temperature, diurnal temperature range, precipitation, wet-day frequency, vapour pressure and cloud cover). Maximum and minimum temperatures have been arithmetically derived from these. Secondary variables (frost day frequency and potential evapotranspiration) have been estimated from the six primary variables using well-known formulae. Time series for hemispheric averages and 20 large sub-continental scale regions were calculated (for mean, maximum and minimum temperature and precipitation totals) and compared to a number of similar gridded products. The new dataset compares very favourably, with the major deviations mostly in regions and/or time periods with sparser observational data. CRU TS3.10 includes diagnostics associated with each interpolated value that indicates the number of stations used in the interpolation, allowing determination of the reliability of values in an objective way. This gridded product will be publicly available, including the input station series ( and ). © 2013 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

ABSTRACT This paper investigates winter (DJF) precipitation variability over East Anglia at the daily and 2 d timescales using rain gauge data from 134 sites. The first three principal components (PCs) explain 80.2% (82.0%) of the variance in daily (2 d totals). Precipitation displays higher spatial coherence in winter, with the first three PCs of summer daily totals (Neal and Phillips, 2009, International Journal of Climatology 29: 1661-1679) explaining only 72.3% of the variance. The winter PCs for both 24- and 48-h timescales display precipitation maxima in South Essex (PC 1), NE Norfolk (PC 2), and NW Cambridgeshire (PC 3). The rainfall maximum over South Essex is more important in winter than in summer. Lamb Weather Types and synoptic charts are used to explain the causes of the PCs. A precipitation regionalization is also produced. Discharge for 11 rivers is then modelled as a linear function of the rainfall patterns (as represented by the PC scores). With the exception of the River Babingley, whose discharge is not significantly related to the PCs, these models explain on average 26.5% of the variance. For most rivers, there are significant relationships between discharge and precipitation that fell up to 4 d ago on average. In general, East Anglian river flows show persistence over 6-8 d. [ABSTRACT FROM AUTHOR]

This paper examines the contribution of tropical--extratropical cloudbands, and of interactions between tropical cloud and mid-latitude systems, to cool season (April--October) rainfall in agriculturally marginal areas of Australia. A following paper describes inter- and intra-annual variability of these features. A classification scheme for these tropical influences based on GMS satellite imagery is described, and used to compile a 15-year archive of events. It is shown that cloudbands extending from the tropical oceans bordering Australia ('Oceanic' Cloudbands) are most frequent and influential between April and July, but decrease sharply after August, at which time bands originating over the continental interior ('Continental' Cloudbands) increase. The contribution of these systems to rainfall at stations representing agriculturally marginal areas is assessed. Oceanic Cloudbands originating west of 120 deg.E contribute 70--90 per cent of cool-season rain in north-western Australia, with the contribution decreasing to the south and east. North-eastern Australia receives a significant portion of its rain from Cloudbands originating east of 120 deg.E. Tropical--mid-latitude interactions are more important over eastern than western Australia, and produce some 30--40 per cent of rain over much of inland eastern Australia. The overall tropical influence (Cloudbands plus interactions) on rainfall is least in South Australia and western Victoria, but still amounts to some 35--40 per cent of cool-season rain in those areas. The proportion of events producing significant rainfall (>10 mm) is also examined: almost two- thirds of the Oceanic Cloudbands to affect western Australia produce significant rain, and about half of those affecting eastern Australia. [ABSTRACT FROM AUTHOR]

Statistical models have been used to provide operational seasonal forecasts of rainfall over southern Africa since 1992. The Climatology Research Group has been using a quadratic discriminant analysis modelsince November 1994. The model relates rainfall over different areasof South Africa to principal components of sea-surface temperatures in the Indian, South Atlantic and Pacific Oceans. Details of the model are described in this paper. High forecast-skill levels can be achieved for much of the country throughout the year. The mostly successful performance of the model over a 15-year independent testing periodindicates that the model can be used successfully in an operational environment. [ABSTRACT FROM AUTHOR]

The pre-monsoon thermal field over the Indian landmass has an important bearing on the land-sea heating contrast in the region, consequently influencing the establishment, advance and overall performance ofthe Indian summer monsoon rainfall. This paper examines the relationship between the pre-monsoon thermal field over India and the following summer monsoon rainfall, in order to identify possible predictors for long-range forecasting of Indian summer monsoon rainfall. Based on the spatial patterns of correlations of monsoon rainfall with maximum and minimum temperatures at 121 stations well distributed over India, during the recent period 1951--80, two predictors showing a significant contribution to the variance in monsoon rainfall have been identified. They are (i) March minimum temperature in east peninsula India and (ii) May minimum temperature in west central India. These two predictors have performed very well in terms of their significant contribution to the multiple regression models during 1951--1987, vis-a-vis several other known predictors. They have also shown a consistently significant relationship with the monsoon rainfall during the recent period, from the mid-1940s till the end of the data period. A stepwise regression model for long-range forecasting of all-India summer monsoon rainfall, involving three regional predictors, has been developed, and has shown a multiple correlation of 0.89. ) 1997 by the Royal Meteorological Society. [ABSTRACT FROM AUTHOR]

Much of New Zealand's precipitation is modulated by windflow, over its orography. Rain-gauge networks are normally sparse, and because measurement programmes are relatively expensive, there are considerablebenefits in modelling and mapping spatial patterns of precipitation in order to provide information at sites where no data exists. In this paper a simple, numerically robust diagnostic model (VDEL) for estimating orographic precipitation is used to estimate annual precipitation normals for a mountainous region of the southern North Island, New Zealand . The VDEL model, developed initially to analyse storm precipitation patterns, is based on the estimation of orographically forced vertical motion as V s -VZ s where VZ s is the height of the terrain and V s the low-level horizontal windflow upstream of the mountain range. Precipitation patterns were diagnosed by VDEL for four main windflow directions andcalibrated against annual precipitation normals by means of a multivariate regression mapping function. Areal average precipitation, mated from catchment runoffs, was reproduced with errors in the 5 to 10 per cent range. [ABSTRACT FROM AUTHOR]

In his comment on my paper, Whetton argues that precipitation estimates for the Southern Ocean (high latitudes of the Southern Hemisphere) in the Legates and Willmott climatology are implausible owing to its large seasonality. Justification for this assertion includes comparisons with island observations and methodological limitations he feels exist in the Legates and Willmott climatology. In this reply, the methodology used by Legates and Willmott is examined carefully and Whetton's concerns about it are shown to be his misinterpretation of theintent of the air temperature correction. Our (Whetton's and my) arguments serve to illustrate that observational evidence of precipitation over the ocean expanse of the Southern Hemisphere is a major limiting factor of all observation-based climatologies. [ABSTRACT FROM AUTHOR]

This paper updates precipitation series for England and Wales, Scotland and Northern Ireland for 1990 to 1995. A new precipitation seriesfor the whole of Ireland for 1840 to 1995 is developed. Recent changes in seasonal precipitation totals in all three regions are discussed. In all regions, recent precipitation in winter (DJF) has increasedand summer (JJA) precipitation has decreased. This trend is most evident in Scotland, where the November to April total for 1986 to 1995 is 30 per cent more than corresponding values in 1951 to 1980. For England and Wales the 1995 summer was the driest on record, with 7 mm less rainfall than in 1976, the previous driest summer. Over Scotland and Ireland the 1995 summer was also dry but not as exceptional. [ABSTRACT FROM AUTHOR]

The paper addresses issues relating to the design and calibration ofprecipitation models for down-scaling General Circulation Model (GCM) output. First, the significance of non-stationary daily circulation-pattern-precipitation relationships will be described for two UK sites, each with records beginning in 1881. Second, the cause(s) of the observed non-stationarity will be investigated using lengthy air flow, synoptic, temperature, and standardized teleconnection indices. Third, the prospects for incorporating these factors within down-scalingmethods will be discussed with reference to several alternative techniques. Finally, a multivariate approach incorporating teleconnectionand airflow indices within precipitation models is advocated. [ABSTRACT FROM AUTHOR]