Search

Extreme temperature and precipitation events occurring in Australia in recent decades have caused significant socio-economic and environmental impacts, and thus determining the factors contributing to these extremes is an active area of research. Many recently occurring record-breaking temperature and rainfall events have now been examined from an extreme event attribution (EEA) perspective. This paper describes a set of studies that have examined the causes of extreme climate events using various general circulation models (GCMs), presenting a comprehensive methodology for GCM-based attribution of extremes of temperature and precipitation observed on large spatial and temporal scales in Australia. First, we review how Coupled Model Intercomparison Project Phase 5 (CMIP5) models have been used to examine the changing odds of observed extremes. Second, we review how a large perturbed initial condition ensemble of a single climate model (CESM) has been used to quantitatively examine the changing characteristics of Australian heat extremes. For each approach, methodological details and applications are provided and limitations highlighted. The conclusions of this methodological review discuss the limitations and uncertainties associated with this approach and identify key unexplored applications of GCM-based attribution of extremes. Ideally, this information will be useful for the application of the described extreme event attribution approaches elsewhere. [ABSTRACT FROM AUTHOR]

Climate variability has been a threat to the socio-economic development of Ethiopia. This paper examined the changes in rainfall, minimum, and maximum temperature extremes of Jemma Sub-Basin of the Upper Blue Nile Basin for the period of 1981 to 2014. The nonparametric Mann-Kendall, seasonal Mann-Kendall, and Sen's slope estimator were used to estimate annual trends. Ten rainfall and 12 temperature indices were used to study changes in rainfall and temperature extremes. The results showed an increasing trend of annual and summer rainfall in more than 78% of the stations and a decreasing trend of spring rainfall in most of the stations. An increase in rainfall extreme events was detected in the majority of the stations. Several rainfall extreme indices showed wetting trends in the sub-basin, whereas limited indices indicated dryness in most of the stations. Annual maximum and minimum temperature and extreme temperature indices showed warming trend in the sub-basin. Presence of extreme rainfall and a warming trend of extreme temperature indices may suggest signs of climate change in the Jemma Sub-Basin. This study, therefore, recommended the need for exploring climate induced risks and implementing appropriate climate change adaptation and mitigation strategies. [ABSTRACT FROM AUTHOR]

This paper describes results of an experiment that perturbed the initial conditions for the ocean's temperature field of the Community Earth System Model (CESM) with a well defined design. The resulting 30-member ensemble of CESM simulations, each of 10 years in length, is used to create an emulator (a nonlinear regression relating the initial conditions to various outcomes) from the simulators. Through the use of the emulator to expand the output distribution space, we estimate the spatial uncertainties at 10 years for surface air temperature, 25m ocean temperature, precipitation, and rain. Outside the tropics, basin averages for the uncertainty in the ocean temperature field range between 0.48 °C (Indian Ocean) and 0.87 °C (North Pacific) (2 standard deviation). The tropical Pacific uncertainty is the largest due to different phasings of the ENSO signal. Over land areas, the regional temperature uncertainty varies from 1.03 °C (South America) to 10.82 °C (Europe) (2 standard deviation). Similarly, the regional average uncertainty in precipitation varies from 0.001 cm day-1 over Antarctica to 0.163 cm day-1 over Australia with a global average of 0.075 cm day-1. In general, both temperature and precipitation uncertainties are larger over land than over the ocean. A maximum covariance analysis is used to examine how ocean temperatures affect both surface air temperatures and precipitation over land. The analysis shows that the tropical Pacific influences the temperature over North America, but the North America surface temperature is also moderated by the state of the North Pacific outside the tropics. It also indicates which regions show a high degree of variance between the simulations in the ensemble and are, therefore, less predictable. The calculated uncertainties are also compared to an estimate of internal variability within CESM. Finally, the importance of feedback processes on the solution of the simulation over the 10 years of the experiment is quantified. These estimates of uncertainty do not take into consideration the anthropogenic effect on warming of the atmosphere and ocean. [ABSTRACT FROM AUTHOR]

Abstract The paper summarizes an end-to-end activity connecting the global climate modeling enterprise with users of climate information in Alaska. The effort included retrieval of the requisite observational datasets and model output, a model evaluation and selection procedure, the actual downscaling by the delta method with its inherent bias-adjustment, and the provision of products to a range of users through visualization software that empowers users to explore the downscaled output and its sensitivities. An additional software tool enables users to examine skill metrics and relative rankings of 21 global models for Alaska and six other domains in the Northern Hemisphere. The downscaled temperatures and precipitation are made available as calendar-month decadal means under three different greenhouse forcing scenarios through 2100 for more than 4000 communities in Alaska and western Canada. The visualization package displays the uncertainties inherent in the multi-model ensemble projections. These uncertainties are often larger than the projected changes. Highlights • Downscaled climate data for more than 4000 communities are viewable by users. • A software tool allows users to evaluate skill 22 climate models for eight regions. • Across-model uncertainties often exceed changes of temperature and precipitation. • Projected warming and wetting are largest in winter and summer, respectively. • Emission scenario is a key determinant of future warming of Arctic communities. [ABSTRACT FROM AUTHOR]

Serbia is situated at Balkan Peninsula, and currently majority of the territory is under warm temperate - fully humid climate type with warm summers (Cfb type, according to Koppen-Geiger Climate Classification). Observed changes in climate conditions since 1961 until present time show significant increase in temperature change and change in precipitation patterns. Disturbances in heat conditions, which are recorded to affect human health, agricultural production and forest ecosystem, are priority in climate change analysis and application in adaptation planning. Future change analysis show accelerated increase of temperature by the end of the 21st century, which proves the needs for immediate measures for mitigation of negative impacts. Temperature increase averaged over the territory of Serbia is 1.2 °C for the period 1996-2015 with respect to the period 1961-1980, with highest increase of maximum daily temperature during the summer season, 2.2 °C. Using high resolution multi-model ensemble approach for analysis of the future changes with respect to the base period 1986-2005, in compliance with Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5), it is estimated that temperature may increase by 1.9 °C according to Representative Concentration Pathway 4.5 (RCP4.5) scenario and by 4.4 °C according to RCP8.5 by the end of the century. Spatial distribution of temperature increase, intensification of high precipitation events and decrease of summer precipitation, show intrusion of subtropical climate over the Serbia and increase of high temperature and high precipitation risks. Results presented in this paper, using high-resolution multi-model ensemble approach, provide climate change information for short term to long term planning in different sectors of economy and preservation of human health and environment. [ABSTRACT FROM AUTHOR]

Drought (similarly as flooding) is considerably the gravest agrometeorological extreme connected with climate change and bringing the highest losses in an agricultural production. The objective of this paper is to study the spatial and temporal variability of the Aridity Index (AI) in the Czech Republic, per decade, during the 55-year period (1961 - 2015). AI is a climatic index, which is important for recording of the drought phenomenon evolution. The climatic data used, include monthly precipitation totals and air temperature from 120 meteorological stations operated by the Czech Hydrometeorological Institute. The potential evapotranspiration was calculated based on the modified algorithm Penman-Monteith. The data processing was done by the statistical tools of Microsoft Excel and the Geographical Information Systems (Clidata GIS, ArcGIS 10). The results of the analysis showed, that during the decade 1961 - 1970, almost the whole area of the Czech Republic is classified as "wet" with AI values ranging above 0.60, but over the next years (1971 - 2015), areas of the south Moravia (e.g. Dyjsko-svratecký ravine, Valticko-lednický area, surroundings of Brno city), and also Prague city and Poohří river basin shifted gradually to "sub-humid" climate zone with AI < = 0.60. Especially, during the pre-last decade of the study period 1991 - 2000. [ABSTRACT FROM AUTHOR]

In the context of climate change, scientists discuss the relevant reference periods for the assessment of changes in climate. Recently, many studies have been published comparing recent conditions with the last reference period 1961-1990. In this paper, the trends of annual, seasonal and monthly average air temperature, as well as annual, seasonal and monthly precipitation totals in Slovakia, are presented to point out changes which will probably show up in the next reference period 1991-2020. In the second part of paper, changes in the climate regions in Slovakia are analysed, comparing spatial distributions in the period 1961-1990 and in the period 1961-2010. [ABSTRACT FROM AUTHOR]

This paper examines an asymmetric spatiotemporal connection and climatic impact between the winter atmospheric blocking activity in the Euro-Atlantic sector and the life cycle of the North Atlantic Oscillation (NAO) during the period 1950-2012. Results show that, for positive NAO (NAO+) events, the instantaneous blocking (IB) frequency exhibits an enhancement along the southwest-northeast (SW-NE) direction from the eastern Atlantic to northeastern Europe (SW-NE pattern, hereafter), which is particularly evident during the NAO+ decaying stage. By contrast, for negative NAO (NAO−) events, the IB frequency exhibits a spatially asymmetric southeast-northwest (SE-NW) distribution from central Europe to the North Atlantic and Greenland (SE-NW pattern, hereafter). Moreover, for NAO− (NAO+) events, the most marked decrease (increase) in the surface air temperature (SAT) in winter over northern Europe is in the decaying stage. For NAO+ events, the dominant positive temperature and precipitation anomalies exhibit the SW-NE-oriented distribution from western to northeastern Europe, which is parallel to the NAO+-related blocking frequency distribution. For NAO- events, the dominant negative temperature anomaly is in northern and central Europe, whereas the dominant positive precipitation anomaly is distributed over southern Europe along the SW-NE direction. In addition, the downward infrared radiation controlled by the NAO’s circulation plays a crucial role in the SAT anomaly distribution. It is further shown that the NAO’s phase can act as an asymmetric impact on the European climate through producing this asymmetric spatiotemporal connection with the Euro-Atlantic IB frequency. [ABSTRACT FROM AUTHOR]

Reliable knowledge of the near-future climate change signal of extremes is important for adaptation and mitigation strategies. Especially compound extremes, like heat and drought occurring simultaneously, may have a greater impact on society than their univariate counterparts and have recently become an active field of study. In this paper, we use a 12-member ensemble of high-resolution (7 km) regional climate simulations with the regional climate model COSMO-CLM over central Europe to analyze the climate change signal and its uncertainty for compound heat and drought extremes in summer by two different measures: one describing absolute (i.e., number of exceedances of absolute thresholds like hot days), the other relative (i.e., number of exceedances of time series intrinsic thresholds) compound extreme events. Changes are assessed between a reference period (1971–2000) and a projection period (2021–2050). Our findings show an increase in the number of absolute compound events for the whole investigation area. The change signal of relative extremes is more region-dependent, but there is a strong signal change in the southern and eastern parts of Germany and the neighboring countries. Especially the Czech Republic shows strong change in absolute and relative extreme events. [ABSTRACT FROM AUTHOR]

In the last years coupled atmospheric ocean climate models have remarkably improved medium range seasonal forecasts, especially on middle latitude areas such as Europe and the Mediterranean basin. In this study a new framework for medium range seasonal forecasts is proposed. It is based on circulation types extracted from long range global ensemble models and it aims at two goals: (i) an easier use of the information contained in the complex system of atmospheric circulations, through their reduction to a limited number of circulation types and (ii) the computation of high spatial resolution probabilistic forecasts for temperature and precipitation. The proposed framework could be also useful to lead predictions of weather-derived parameters, such as the risk of heavy rainfall, drought or heat waves, with important impacts on agriculture, water management and severe weather risk assessment. Operatively, starting from the ensemble predictions of mean sea level pressure and geopotential height at 500 hPa of the NCEP – CFSv2 long range forecasts, the third-quantiles probabilistic maps of 2 m temperature and precipitation are computed through a Bayesian approach by using E-OBS 0.25 ∘ gridded datasets. Two different classification schemes with nine classes were used: (i) Principal Component Transversal (PCT9), computed on mean sea level pressure and (ii) Simulated Annealing Clustering (SAN9), computed on geopotential height at 500 hPa. Both were chosen for their best fit concerning the ground-level precipitation and temperature stratification for the Italian peninsula. Following this approach an operative chain based on a very flexible and exportable method was implemented, applicable wherever spatially and temporally consistent datasets of weather observations are available. In this paper the model operative chain, some output examples and a first attempt of qualitative verification are shown. In particular three case studies (June 2003, February 2012 and July 2014) were examined, assuming that the ensemble seasonal model correctly predicts the circulation type occurrences. At least on this base, the framework here proposed has shown promising performance. [ABSTRACT FROM AUTHOR]

There is still considerable uncertainty about precipitation at high elevation in mountain terrain due to the relatively few in situ measurements available and to the particular variability of the parameter. In this study, several spatialization techniques were tested, some for climatological time scale and others for daily fields, for precipitation over the western Alps for the period of 1990-2012. The study domain and period were chosen for the quality of available in situ observations and density of the network. First, a weather-type classification was established with a technique based on canonical correlation analysis combining large- and regional-scale data. The spatialization techniques applied for the climatological time scale were adapted from the Aurelhy method which uses elevation and principal components of the topography as predictors. The spatialization techniques applied to daily fields were based on kriging of daily rain gauges and used the climatological fields as predictors. This study aims to validate the advantage of using the climatology of the weather type of the day as predictor for daily fields over a monthly climatology. The climatology of the weather type of the day seems to demonstrate some small improvement. Finally, annual means over the period of 1990-2012 were produced using several methods, including some from accumulation of daily fields and others from the spatialization of in situ station means. Precipitation at high elevations and vertical climatological gradients were particularly scrutinized. Annual means based on sums of daily fields seem to have better performances. This paper only presents results for precipitation but temperature was also analysed. [ABSTRACT FROM AUTHOR]

This paper demonstrates that an operational forecast model can skillfully predict week-3-4 averages of temperature and precipitation over the contiguous United States. This skill is demonstrated at the gridpoint level (about 1° × 1°) by decomposing temperature and precipitation anomalies in terms of an orthogonal set of patterns that can be ordered by a measure of length scale and then showing that many of the resulting components are predictable and can be predicted in observations with statistically significant skill. The statistical significance of predictability and skill are assessed using a permutation test that accounts for serial correlation. Skill is detected based on correlation measures but not based on mean square error measures, indicating that an amplitude correction is necessary for skill. The statistical characteristics of predictability are further clarified by finding linear combinations of components that maximize predictability. The forecast model analyzed here is version 2 of the Climate Forecast System (CFSv2), and the variables considered are temperature and precipitation over the contiguous United States during January and July. A 4-day lagged ensemble, comprising 16 ensemble members, is used. The most predictable components of winter temperature and precipitation are related to ENSO, and other predictable components of winter precipitation are shown to be related to the Madden-Julian oscillation. These results establish a scientific basis for making week-3-4 weather and climate predictions. [ABSTRACT FROM AUTHOR]

Global warming and climate change have increased the frequency of heavy precipitation. Heavy rainfall results in a large amount of water entering roadways within a short time period. Water remains in the pavement system for a certain time period, reduces strengths and moduli of granular bases and subgrades, and induces pavement distresses. Geotextiles are commonly used in roadways for drainage purposes, which require soil saturation. However, soil saturation does not always exist in roadways to enable gravity drainage of water by conventional geotextiles. Wicking geotextile, a new type of woven geotextile, was recently introduced to the market to remove moisture from unsaturated soils. The wicking geotextile includes special hydrophilic and hygroscopic 4 deep groove fibers with multichannel cross sections, which can induce high capillary force to wick water out of moist soil without saturation of soil. The ability and rate of this geotextile to remove water from moist soil depends on several factors, including temperature and relative humidity. In this study, a series of laboratory tests under controlled temperature and relative humidity were conducted to quantify the water removal rate of the wicking geotextile. A half length of the wicking geotextile was submerged in water tanks, and the other half was hung outside of the tanks. The water wicked from the tank into the geotextile evaporated into the air. Such tests were conducted under 12 different test conditions (i.e., different temperatures and relative humidities). Test results demonstrated that the wicking geotextile could remove water from the water tank at a certain rate. Three commonly used methods available in the literature were adopted to quantify the water removal rate of the wicking geotextile based on vapor pressure, temperature, and relative humidity. A new concept of equivalent water evaporation length of a wicking geotextile is proposed in this study. It should be pointed out that the tests presented in this paper aimed to determine the maximum water removal capacity of the geotextile given sufficient water supply. [ABSTRACT FROM AUTHOR]

Middle and eastern routes of the South-North Water Diversion Project (SNWDP) of China, which are approximately located within the area 28°-42°N and 110°-122°E, are being constructed. This paper investigates the past climatic variations on various time scales using instrumental and proxy data. It is found that annual mean surface air temperature has increased significantly during the past 50-100 years, and winter and spring temperatures in the northern part of the region have undergone the most significant changes. A much more significant increase occurs for annual mean minimum temperature and extreme low temperature than for annual mean maximum temperature and extreme high temperature. No significant trend in annual precipitation is found for the region as a whole for the last 50 and 100 years, although obvious decadal and spatial variation is detectable. A seesaw pattern of annual and summer precipitation variability between the north and the south of the region is evident. Over the last 100 years, the Haihe River basin has witnessed a significant negative trend of annual precipitation, but no similar trend is detected for the Yangtze and Huaihe River basins. Pan evaporation has significantly decreased since the mid-1960s in the region in spite of the fact that the trend appears to have ended in the early 1990s. The negative trend of pan evaporation is very significant in the plain area between the Yangtze and Yellow Rivers. There was a notable series of dry intervals lasting decades in the north of the region. The northern drought of the past 30 years is not the most severe in view of the past 500 years; however, the southern drought during the period from the 1960s to the 1980s may have been unprecedented. The dryness-wetness index (DWI) shows significant oscillations with periodicities of 9.5 and 20 years in the south and 10.5 and 25 years in the north. Longer periodicities in the DWI series include 160-170- and 70-80-yr oscillations in the north, and 100-150-yr oscillations in the south. The observed climate change could have implications for the construction and management of the SNWDP. The official approval and start of the hydro project was catalyzed by the severe multiyear drought of 1997-2003 in the north, and the operation and management of the project in the future will also be influenced by climate change-in particular by precipitation variability. This paper provides a preliminary discussion of the potential implications of observed climate change for the SNWDP. [ABSTRACT FROM AUTHOR]

In a changing climate, there is an interest in predicting how extreme rainfall events may change. Using historical records, several recent papers have evaluated whether high-intensity precipitation scales with temperature in accordance with the Clausius--Clapeyron (C--C) relationship. For varying locations in Europe, these papers have identified both super C--C relationships as well as a breakdown of the C--C relationship under dry conditions. In this paper, a similar analysis is carried out for the United States using data from 14 weather stations clustered in four different hydroclimatic regions: the coastal northeast, interior New York, the central plains, and the western plains. In all regions except interior New York state, 99th percentile 1-h precipitation generally followed the C--C relation. In interior New York, there was evidence that intensity scaled with a super C--C relationship. For the 99.9th percentile precipitation, interior New York displayed some moderate evidence of a super C--C relationship, the western plains showed little relation between precipitation and temperature, and the remainder of sites generally scaled with the C--C relationship. Also, if only July, August, and September precipitation is considered, all stations except those in interior New York have little relation between temperature and precipitation, suggesting that precipitation intensity during summer months may not be well constrained by the C--C relationship. Overall, the C--C relationship (or a variation thereof) does not appear to constrain extreme precipitation in all regions and in all seasons, and its ability to aid in constraining future predictions of extreme precipitation may only be relevant to certain locales and time periods. [ABSTRACT FROM AUTHOR]

The aim of the present series of papers is to develop a density current parameterization for global circulation models. This first paper is devoted to the presentation of this new wake parameterization coupled with Emanuel’s convective scheme. The model represents a population of identical circular cold pools (the wakes) with vertical frontiers. The wakes are cooled by the precipitating downdrafts while the outside area is warmed by the subsidence induced by the saturated drafts. The budget equations for mass, energy, and water yield evolution equations for the prognostic variables (the vertical profiles of the temperature and humidity differences between the wakes and their exterior). They also provide additional terms for the equations of the mean variables. The driving terms of the wake equations are the differential heating and drying due to convective drafts. The action of the convection on the wakes is implemented by splitting the convective tendency and attributing the effect of the precipitating downdrafts to the wake region and the effect of the saturated drafts to their exterior. Conversely, the action of the wakes on convection is implemented by introducing two new variables representing the convergence at the leading edge of the wakes. The available lifting energy (ALE) determines the triggers of deep convection: convection occurs when ALE exceeds the convective inhibition. The available lifting power (ALP) determines the intensity of convection; it is equal to the power input into the system by the collapse of the wakes. The ALE/ALP closure, together with the splitting of the convective heating and drying, implements the full coupling between wake and convection. The coupled wake–convection scheme thus created makes it possible to represent the moist convective processes more realistically, to prepare the coupling of convection with boundary layer and orographic processes, and to consider simulating the propagation of convective systems. [ABSTRACT FROM AUTHOR]

Statistical postprocessing techniques such as model output statistics are used by national weather centers to improve the skill of numerical forecasts. However, many of these techniques require an extensive database to develop, maintain, and update the postprocessed forecasts. This paper explores alternative postprocessing techniques for temperature and precipitation based on weighted-average and recursive formulations of forecast–observation paired data that do not require extensive database management, yet provide distinct error reduction over direct model output. For maximum and minimum daily temperatures, seven different postprocessing methods were tested based on direct model output error for forecast days 1–8. The methods were tested on a 1-yr series of daily temperature values averaged over 19 stations in complex terrain in southwestern British Columbia, Canada. For daily quantitative precipitation forecasts, three different postprocessing methods were tested over a 6-month wet season period. The different postprocessing methods were compared using several verification metrics, including mean error (for temperature), degree of mass balance (for precipitation), mean absolute error, and threshold error. All of the postprocessing methods improved forecast skill over direct model output. The postprocessing methods for temperature forecasts require a much shorter training period (14 days) than precipitation forecasts (40 days) to accomplish error reduction over direct model output forecasts. The postprocessing methods that weight recent error estimates most heavily perform better in the short term (days 1–4) while methods that weight recent and earlier error estimates more evenly show improving relative performance in the midterm (days 5–8). For temperature forecasts, Kalman filtering produced slightly better verification scores than the other methods. For precipitation forecasts, a 40-day moving-average weighting function and the best easy systematic estimator method produced the best degree of mass balance results, while a seasonally averaged method produced the lowest mean absolute errors and lowest threshold errors. The methods described in this paper require minimal database management or computer resources to update forecasts, and are especially viable for hydrometeorological applications that require calibrated daily temperature and precipitation forecasts. [ABSTRACT FROM AUTHOR]

Atmospheric drought in lowlands in Slovakia is analyzed on the bases of Standardised Precipitation Index (SPI) and Standardised Precipitation Evapotranspiration Index (SPEI). This paper gives information about the dynamic, intensity, seasonal and territorial differences in occurrence of drought with various intensity: mild (near to normal), moderate, severe and extreme for the period 1961-2011. Future changes in occurrence of drought are determined on the basis of model data (regional circulation models KNMI and MPI) for temperature and precipitation for two periods: 2001-2050 and 2051-2100. The results show that temperature has an important role for occurrence of moderate and severe drought at monthly level and precipitation is the main factor for occurrence of extreme drought. There are an increasing number of cases with severe or extreme drought in summer for most of the investigated stations. Future projection of drought shows general tendency to increasing frequency of severe dry events in 2001-2050 and 2051-2100 while there will be a little decreasing of extremely dry months in comparison to 1961-2010. [ABSTRACT FROM AUTHOR]

Drought is among the least understood natural hazards and requires particular notice in the context of climate change. While the Mediterranean climate is by itself prone to droughts, a rise of temperatures and alteration of rainfall patterns already render the southern parts of continental Portugal and Spain highly susceptible to desertification. Precipitation in the Iberian Peninsula is mainly controlled by the large-scale mode of North Atlantic Oscillation (NAO) and is distributed with elevated variability over the cold months. Most drought studies of this region rely on meteorological data or apply information on vegetation dynamics, such as the Normalised Differenced Vegetation Index (NDVI), to indirectly investigate droughts. This paper evaluates the influence of the NAO winter index on the spatiotemporal occurrence of droughts in the Iberian Peninsula during the spring and summer seasons (March to August) for the years 2001-2005, 2007 and 2010. We applied the Vegetation Temperature Condition Index (VTCI) to identify local droughts. VTCI is a remote sensing drought index developed for reflecting soil moisture conditions in agricultural areas and combines information on land surface temperature (LST) and NDVI. As such, VTCI overcomes the shortcomings of NDVI in terms of drought monitoring. We derived biweekly information on LST and NDVI from MODIS/Terra and produced VTCI-NAO correlation maps at a confidence level of at least 90 % based on the VTCI time series. The results reflect a typical Mediterranean pattern in most parts of Iberia that is highly influenced by relief. Spring seasons are marked by great variability of precipitation, while summers persistently become dry, particularly in the south. NAO exerts its greatest influence in April and June, clearly delineating high correlation areas in the northwest and southeast with reverse patterns between the spring and early summer months. Due to the impact on water availability, the spring months are important for plant growth. At the same time, agricultural lands were found with types of land cover less resilient to droughts. The knowledge acquired in studies like the one reported here is therefore likely to be used in drought warning models for agriculture in spring. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to provide a summary of Morocco's climate extreme trends during the last four decades. Indices were computed based on a daily temperature and precipitation using a consistent approach recommended by the ETCCDI. Trends in these indices were calculated at 20 stations from 1970 to 2012. Twelve indices were considered to detect trends in temperature. A large number of stations have significant trends and confirm an increase in temperature, showing increased warming during spring and summer seasons. The results also show a decrease in the number of cold days and nights and an increase in the number of warm days and nights. Increasing trends have also been found in the absolute warmest and coldest temperatures of the year. A clear increase is detected for warm nights and diurnal temperature range. Eight indices for precipitation were also analyzed, but the trends for these precipitation indices are much less significant than for temperature indices and show more mixed spatial patterns of change. Heavy precipitation events do not exhibit significant trends except at a few locations, in the north and central parts of Morocco, with a general tendency towards drier conditions. The correlation between these climate indices and the large-scale atmospheric circulations indices such as the NAO, MO, and WEMO were also analyzed. Results show a stronger relationship with these climatic indices for the precipitation indices compared to the temperature indices. The correlations are more significant in the Atlantic regions, but they remain moderate at the whole country scale. [ABSTRACT FROM AUTHOR]

In this paper, we present regional climate change projections for the Tamil Nadu state of India, simulated by the Met Office Hadley Centre regional climate model. The model is run at 25 km horizontal resolution driven by lateral boundary conditions generated by a perturbed physical ensemble of 17 simulations produced by a version of Hadley Centre coupled climate model, known as HadCM3Q under A1B scenario. The large scale features of these 17 simulations were evaluated for the target region to choose lateral boundary conditions from six members that represent a range of climate variations over the study region. The regional climate, known as PRECIS, was then run 130 years from 1970. The analyses primarily focus on maximum and minimum temperatures and rainfall over the region. For the Tamil Nadu as a whole, the projections of maximum temperature show an increase of 1.0, 2.2 and 3.1 °C for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095), respectively, with respect to baseline period (1970-2000). Similarly, the projections of minimum temperature show an increase of 1.1, 2.4 and 3.5 °C, respectively. This increasing trend is statistically significant (Mann-Kendall trend test). The annual rainfall projections for the same periods indicate a general decrease in rainfall of about 2-7, 1-4 and 4-9 %, respectively. However, significant exceptions are noticed over some pockets of western hilly areas and high rainfall areas where increases in rainfall are seen. There are also indications of increasing heavy rainfall events during the northeast monsoon season and a slight decrease during the southwest monsoon season. Such an approach of using climate models may maximize the utility of high-resolution climate change information for impact-adaptation-vulnerability assessments. [ABSTRACT FROM AUTHOR]

The paper has examined the impact of variations of Atlantic multidecadal oscillation on the change in air temperature during the summer season on the territory of Montenegro. Starting from the fact that in recent years more and more extreme weather events occur, as well as from the intention to comprehensively consider the temperature conditions in the territory of Montenegro, first analysis is of changes in air temperature in 8 parameters, of which 5 climate indices; connections with Atlantic multidecadal oscillation have also been analyzed. To study changes in temperature extreme indexes proposed by the WMO CCL/CLIVAR are used. Research within the listed topics was realized using data from 23 meteorological stations for the period 1951-2010 and the calculations are done for the summer season. The results show that there is increased number of maximum and minimum daily temperatures of warmer value. The impact assessment Atlantic multidecadal oscillation, teleconnection pattern that is quite distant, showed that its variability affects changes in summer temperatures in Montenegro, both in terms of mean values, and the frequency of extreme actions presented by climate indices. [ABSTRACT FROM AUTHOR]

The authors note that: "Fig. 5 in the published paper appeared incorrectly. The correct figure and the figure caption are provided below. The main message and the interpretation of our paper remain unaffected by this correction." [ABSTRACT FROM AUTHOR]

This paper presents projected changes in temperature and precipitation extremes in China by the end of the twenty-first century based on the Coupled Model Intercomparison Project phase 5 (CMIP5) simulations. The temporal changes and their spatial patterns in the Expert Team on Climate Change Detection and Indices (ETCCDI) indices under the RCP4.5 and RCP8.5 emission scenarios are analyzed. Compared to the reference period 1986-2005, substantial changes are projected in temperature and precipitation extremes under both emission scenarios. These changes include a decrease in cold extremes, an increase in warm extremes, and an intensification of precipitation extremes. The intermodel spread in the projection increases with time, with wider spread under RCP8.5 than RCP4.5 for most indices, especially at the subregional scale. The difference in the projected changes under the two RCPs begins to emerge in the 2040s. Analyses based on the mixed-effects analysis of variance (ANOVA) model indicate that by the end of the twenty-first century, at the national scale, the dominant contributor to the projection uncertainty of most temperature-based indices, and some precipitation extremes [including maximum 1-day precipitation (RX1day) and maximum 5-day precipitation (RX5day), and total extremely wet day total amount (R95p)], is the difference in emission scenarios. By the end of the twenty-first century, model uncertainty is the dominant factor at the regional scale and for the other indices. Natural variability can also play very important role. [ABSTRACT FROM AUTHOR]

In order to support political and economical decision makers by providing climate information for the future, it is essential to analyze regional climate model results. These models are capable to describe the regional climate conditions of individual countries using 25 km horizontal resolution, whereas global climate models are too coarse for such details. This paper discusses the regional effects of global warming using regional climate model experiments from the PRECIS model developed at the Hadley Centre of the UK Met Office. Since PRECIS was adapted at the Department of Meteorology, Eötvös Loránd University in the recent years, important regional/local conditions could be taken into account during the modelling process. In the experiments of PRECIS, three different emission scenarios (A2, A1B, B2) are considered to provide estimations for the 21st century. Our conclusions highlight the significant warming tendency in Hungary, especially in summer. The frequency of cold temperature extremes is projected to decrease significantly while warm extremes tend to occur more oft en in the future. Furthermore, significant drying is projected in the region, especially, in summer. In winter the precipitation is likely to increase. [ABSTRACT FROM AUTHOR]

This paper presents a simple approach for the temporal disaggregation from daily to 3-hourly observed gridded temperature and precipitation (1 × 1 km2) on the national scale. The intended use of the disaggregated 3-hourly data is to recalibrate the hydrological model currently used by the Norwegian Water Resources and Energy Directorate (NVE) for daily flood forecasting. By adapting the hydrological model to a 3-hourly temporal scale, the flood forecasting can benefit from available meteorological forecasts with finer temporal resolution and can better represent critical events of short duration and at small spatial scales. By consulting the temporal patterns of a High-Resolution Limited-Area Model (HIRLAM) hindcast series for northern Europe with an hourly temporal and a 0.1° spatial resolution, existing daily 1 × 1 km2 grids for temperature and precipitation covering all of Norway (the seNorge data) were disaggregated into 3-hourly values for the time period September 1957 to December 2010. For the period 2000-05, the disaggregated 3-hourly temperature and precipitation data are validated against observed values from five meteorological stations and against 3-hourly data from the HIRLAM hindcast and daily seNorge data simply split into eight fractions. The results show that the disaggregated data perform best with anomaly correlation coefficients between 0.89 and 0.92 for temperature. With regard to precipitation, the disaggregated data also provide the highest correlations and the lowest errors. In addition, the disaggregated data prove to be best in estimating intervals without precipitation and tend to be most appropriate in estimating extreme precipitation with low occurrence probability (<20%). [ABSTRACT FROM AUTHOR]

In this paper, we estimate the trends and variability in Advanced Very High Resolution Radiometer (AVHRR)-derived terrestrial net primary productivity (NPP) over India for the period 1982-2006. We find an increasing trend of 3.9% per decade (r = 0.78, R2 = 0.61) during the analysis period. A multivariate linear regression of NPP with temperature, precipitation, atmospheric CO2 concentration, soil water and surface solar radiation (r = 0.80, R2 = 0.65) indicates that the increasing trend is partly driven by increasing atmospheric CO2 concentration and the consequent CO2 fertilization of the ecosystems. However, human interventions may have also played a key role in the NPP increase: non-forest NPP growth is largely driven by increases in irrigated area and fertilizer use, while forest NPP is influenced by plantation and forest conservation programs. A similar multivariate regression of interannual NPP anomalies with temperature, precipitation, soil water, solar radiation and CO2 anomalies suggests that the interannual variability in NPP is primarily driven by precipitation and temperature variability. Mean seasonal NPP is largest during post-monsoon and lowest during the pre-monsoon period, thereby indicating the importance of soil moisture for vegetation productivity [ABSTRACT FROM AUTHOR]

This paper analyzes climate variability and change in the Urmia Lake Basin, northwest of Iran. Annual average of the following data time series has been analyzed by statistical methods: dry bulb temperature, maximum and minimum temperature, precipitation, and number of rainy and snowy days. We have also used mean monthly temperature and precipitation data for analysis of drought spells for the period 1964-2005 to find out whether fluctuations in the lake level are attributable to natural drought. Our results indicate that mean precipitation has decreased by 9.2 % and the average maximum temperature has increased by 0.8°C over these four decades. The seasonal changes are particularly visible in winter and spring. Results of the Palmer Drought Severity Index show that on average, drought episodes have hit the Urmia Lake Basin every 5 years and most of them reached severe levels, but recent droughts have become more intense and last longer. [ABSTRACT FROM AUTHOR]

The NOAA National Climatic Data Center maintains tables for temperature and precipitation extremes in each of the U.S. states. Many of these tables were several years out of date, however, and therefore did not include a number of recent record-setting meteorological observations. Furthermore, there was no formal process for ensuring the currency of the tables or evaluating observations that might tie or break a statewide climate record. This paper describes the evaluation and revision of the statewide climate-extremes tables for all-time maximum and minimum temperature, greatest 24-h precipitation and snowfall, and greatest snow depth (the five basic climate elements observed on a daily basis by the NOAA Cooperative Weather Network). The process resulted in the revision of 40% of the values listed in those tables and underscored both the necessity of manual quality-assurance methods and the importance of continued climate-monitoring and data-rescue activities to ensure that potential record values are not overlooked. [ABSTRACT FROM AUTHOR]

This paper uses climate normals to assess historic changes in temperature and precipitation in Alabama. Changes in temperature and precipitation are calculated between climate normals periods at 18 weather stations across the state and for the state as a whole. The earliest climate normals period for which data are available is 1931-60 and the most recent is 1981-2010. Results show that Alabama has gotten cooler and wetter over the whole period of record, particularly in the fall and winter. However, changes between climate normals periods show these trends are reversing. [ABSTRACT FROM AUTHOR]

Global Circulation Models (GCMs) contributed to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) and are widely used in global change research. This paper assesses the performance of the AR4 GCMs in simulating precipitation and temperature in China from 1960 to 1999 by comparison with observed data, using system bias (B), root-mean-square error (RMSE), Pearson correlation coefficient (R) and Nash-Sutcliffe model efficiency (E) metrics. Probability density functions (PDFs) are also fitted to the outputs of each model. It is shown that the performance of each GCM varies to different degrees across China. Based on the skill score derived from the four metrics, it is suggested that GCM 15 (ipsl_cm4) and GCM 3 (cccma&lowbar;cgcm&lowbar;t63) provide the best representations of temperature and precipitation, respectively, in terms of spatial distribution and trend over 10 years. The results also indicate that users should apply carefully the results of annual precipitation and annual temperature generated by AR4 GCMs in China due to poor performance. At a finer scale, the four metrics are also used to obtain best fit scores for ten river basins covering mainland China. Further research is proposed to improve the simulation accuracy of the AR4 GCMs regarding China. [ABSTRACT FROM AUTHOR]

Regime-dependent evaluation is a relatively new approach to assess model performance. It consists of classifying the model biases according to a discrete number of regimes and evaluating model output within each regime. In this paper, the regimes are firstly defined by the large-scale atmospheric circulation, based on the objective Jenkinson-Collison classification technique which distinguishes synoptic patterns by strength, direction and vorticity of the geostrophic flow. Eight directional and two vorticity circulation regimes (circulation types) are specified. In this way, it is possible to quantify the model performance for cases with for example westerly winds only, or with cyclonic circulation only. A second regime classification is based on temperature, which allows for detection of temperature-dependent model performance. Modelled accumulated precipitation (mm/6 h) is evaluated with rain gauges for the years 2007 and 2008. Two variants of the COSMO model are evaluated: a fine-resolution version (2.8 km, COSMO-DE) and a coarse-resolution version (7 km, COSMO-EU). In COSMO-EU, a windward/leeward effect becomes visible since circulation is related to dominant wind direction, hence to windward and lee side of orography. In COSMO-DE, no circulation dependent but a height-related bias is identified and further explored, making use of temperature-dependent evaluation which unveils a positive model bias related to solid precipitation. [ABSTRACT FROM AUTHOR]

This paper applies a new field significance test to establish the existence and consistency of ENSO teleconnection patterns across models and observations. An ENSO teleconnection pattern is defined as a field of regression coefficients between an index of the tropical Pacific sea surface temperature and a field of variables such as surface air temperature or precipitation. The test is applied to boreal winter and summer in six continents using observations and hindcasts from the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) and the ENSEMBLE-based predictions of climate changes and their impacts (ENSEMBLES) projects. This comparison represents one of the most comprehensive and up-to-date assessments of the extent to which ENSO teleconnection patterns exist and can be reproduced by coupled models. Statistically significant ENSO teleconnection patterns are detected in both observations and models and in all continents and in both winter and summer seasons, except in two cases: 1) Europe (both seasons and variables), and 2) North America (both variables in boreal summer). Despite many ENSO teleconnection patterns being significant, however, the patterns do not necessarily agree between observations and models. The degree of agreement between models and observations is characterized as 'robust,' 'moderate,' or 'low.' Only Australia and South America are found to have robust agreement between ENSO teleconnection patterns, and then only for limited seasons and variables. Although many of our conclusions regarding teleconnection patterns conform to previous studies, there are exceptions, including the fact that the teleconnection for boreal winter precipitation is generally accepted to exist in Africa but in fact has only low agreement with model simulations, while that in Asia is not widely recognized to exist but is found to be significant and in moderate agreement with model teleconnections. [ABSTRACT FROM AUTHOR]

The Athabasca oil sands development in northeast Alberta, Canada, has disturbed more than 500 km2 of boreal forest through surface mining and tailings ponds development. In this paper, the authors compare the time series of temperatures and precipitation measured over oil sands and non-oil sands locations from 1994 to 2010. In addition, they analyzed the distribution of lightning strikes from 1999 to 2010. The oil sands development has not affected the number of lightning strikes or precipitation amounts but has affected the temperature regime. Over the past 17 years, the summer overnight minimum temperatures near the oil sands have increased by about 1.2°C compared to the regional average. The authors speculate that this is caused by a combination of the industrial addition of waste heat to the atmosphere above the oil sands and changing the surface type from boreal forest to open pit mines with tailings ponds. [ABSTRACT FROM AUTHOR]

This paper evaluates the quality of real-time seasonal probabilistic forecasts of the extreme 15%% tails of the climatological distribution of temperature and precipitation issued by the International Research Institute for Climate and Society (IRI) from 1998 through 2009. IRI's forecasts have been based largely on a two-tiered multimodel dynamical prediction system. Forecasts of the 15%% extremes have been consistent with the corresponding probabilistic forecasts for the standard tercile-based categories; however, nonclimatological forecasts for the extremes have been issued sparingly. Results indicate positive skill in terms of resolution and discrimination for the extremes forecasts, particularly in the tropics. Additionally, with the exception of some overconfidence for extreme above-normal precipitation and a strong cool bias for temperature, reliability analyses suggest generally good calibration. Skills for temperature are generally higher than those for precipitation, due both to correct forecasts of increased probabilities of extremely high (above the upper 15th percentile) temperatures associated with warming trends, and to better discrimination of interannual variability. However, above-normal temperature extremes were substantially underforecast, as noted also for the IRI's tercile forecasts. [ABSTRACT FROM AUTHOR]

This paper deals with the most recent trends in meteorological and hydrological variables, which include air temperature and precipitation ( P), potential and actual (ET) evapotranspiration, surface runoff (RO), water recharge into the soil ( R) and water loss from the soil ( L). Most hydrological variables were calculated via Palmer's algorithm. For this purpose, two rank-based statistical tests (the Mann-Kendall (MK) and a change-point analysis (CPA) approach) and the basic linear regression-based model were applied on the weekly precipitation and temperature from 17 stations all over Greece, during 1961-2006. Only in winter, all variables except for R, which showed no clear signal, presented downward trends. The declining trends of P and L in spring and summer were counterbalanced by reductions in RO (and R in the case of summer) as opposed to increases in ET. In autumn, the declining tendencies of P and L were offset by RO reductions and R increases. Annually, the trends in water cycle components were analogous to that of spring, summer and autumn. The number of stations with statistically significant (at 95%) trends greatly varied with season and meteorological/hydrological variable. [ABSTRACT FROM AUTHOR]

In northwestern North America, which is a large area with complex physiography, Climatic Research Unit (CRU) Time Series, version 2.1, (TS 2.1) gridded monthly mean 2-m temperatures are systematically lower than interpolated monthly averaged North American Regional Reanalysis (NARR) pressure-level temperatures----in particular, in the winter. Quantification of these differences based on CRU gridded observations can be used to estimate pressure-level temperatures from CRU 2-m temperatures (1901--2002) that predate the NARR period (since 1979). Such twentieth-century pressure-level temperature fields can be used in glacier mass-balance modeling and as an alternative to calibrating general circulation model control runs, avoiding the need for accurate boundary layer parameterization. In this paper, an approach is presented that is transferable to moisture, wind, and other 3D fields with potential applications in wind power generation, ecology, and air quality. At each CRU grid point, the difference between CRU and NARR is regressed against seven predictors in CRU (mean temperature, daily temperature range, precipitation, vapor pressure, cloud cover, and number of wet and frost days) for the period of overlap between CRU and NARR (1979--2002). Bayesian model averaging (BMA) is used to avoid overfitting the CRU--NARR differences and underestimating uncertainties. In cross validations, BMA provides reliable posterior predictions of the CRU--NARR differences and outperforms predictions from three alternative models: the constant model (24-yr mean), the regression model of highest Bayesian model probability, and the full model retaining all seven predictors in CRU. [ABSTRACT FROM AUTHOR]

In 2002, a 100 year flood at the Austrian Danube and some of its tributaries has caused significant damage. As a consequence and to fulfill future flood management strategies flood forecasting systems were developed for several Danube tributaries in Upper Austria and Lower Austria. The forecasting model shown includes all Austrian Danube tributaries and has been in operational use since 2006. The paper gives a general overview of the hydrologic flood forecasting model for the Danube tributaries. Runoff is estimated for all tributaries to the Austrian Danube with a total size of more than 90.000 km2. The model is based on a semi conceptual water balance model. The catchments are divided into sub-basins with sizes ranging from 25 km2 to 25.000 km2 according to on-line available gauging stations. Hourly data from 90 discharge gauges from 2003 to 2009 were used to calibrate the runoff model in the catchments. In the operational forecasting mode these data are used for the updating procedure. Precipitation and temperature data were provided by the Austrian Meteorological Service as a real mean values for the same period. MODIS-Data are used to verify the output of the snow routine. Simulation results from different calibration periods are shown. Hydrologic forecasts are based on meteorological forecasts, also provided on an hourly basis by the Austrian Meteorological Service. Both deterministic and ensemble forecasts cover a time span of 48 hours. A real time updating procedure based on ensemble Kalman filtering is implemented to have the best state variables of the model at the beginning of an event. The results of the hydrologic forecasting model provide the basis for a hydraulic 1D-model of the Danube river (Reichel, 2006). [ABSTRACT FROM AUTHOR]

This paper describes a comprehensive set of fully automated quality assurance (QA) procedures for observations of daily surface temperature, precipitation, snowfall, and snow depth. The QA procedures are being applied operationally to the Global Historical Climatology Network (GHCN)-Daily dataset. Since these data are used for analyzing and monitoring variations in extremes, the QA system is designed to detect as many errors as possible while maintaining a low probability of falsely identifying true meteorological events as erroneous. The system consists of 19 carefully evaluated tests that detect duplicate data, climatological outliers, and various inconsistencies (internal, temporal, and spatial). Manual review of random samples of the values flagged as errors is used to set the threshold for each procedure such that its false-positive rate, or fraction of valid values identified as errors, is minimized. In addition, the tests are arranged in a deliberate sequence in which the performance of the later checks is enhanced by the error detection capabilities of the earlier tests. Based on an assessment of each individual check and a final evaluation for each element, the system identifies 3.6 million (0.24%) of the more than 1.5 billion maximum/minimum temperature, precipitation, snowfall, and snow depth values in GHCN-Daily as errors, has a false-positive rate of 1%−2%, and is effective at detecting both the grossest errors as well as more subtle inconsistencies among elements. [ABSTRACT FROM AUTHOR]

Vegetation around the Daihai Lake, northern China, is very sensitive to climate changes. In this paper, pollen-based quantitative climate reconstructions using three methods [weighted averaging partial least squares method (WAPLS), modern analog technique (MAT), and pollen response surface method (PRS)] were conducted to obtain robust reconstructions of Holocene climate changes in the Daihai Lake area. The result obtained by the three methods all consistently show the annual precipitation to have been 50–100 mm lower in the early Holocene, 100–200 mm higher in the Mid-Holocene, and 50–100 mm lower again in the late Holocene than at present. The WAPLS and the MAT methods also show quasi-synchronous oscillations of the mean annual temperature (Ta); 1°–2°C lower in the Early Holocene and 1°–3°C higher in the Mid-Holocene than today. The time period from 6200 to 5100 cal yr BP was the wettest and the warmest interval, with an annual precipitation (Pa) greater than 550 mm and mean annual temperature Ta higher than 6.5°C. Several cold and dry events can be identified to occur about 8200, 6000, and 4400 cal yr BP, with an annual precipitation less than 400 mm and a mean annual temperature colder than 4.5°C, respectively. The mean temperature of the warmest month (Tw) as reconstructed using both WAPLS and MAT methods was relatively stable during the Holocene, fluctuating about ±2°C relative to the present level, but the PRS method suggests more varied Tw values in both amplitude and frequency. After 1500 cal yr BP, no consistent pattern can be observed from these three different analyses, probably because of the impact of intensified human disturbances on the natural vegetation. The fluctuations of annual precipitation (Pa) correspond to that observed in Dongge Cave in southern China. The differences might be linked to Indian monsoon and East Asia monsoon climates or caused by the different degree of dating precision, different temporal resolution, and different sensitive response of climate proxies to the climate variations. [ABSTRACT FROM AUTHOR]

The current paper presents investigation of the response of silver firs growing near Kartuzy in the Kaszubskie Lakeland (northern Poland) to climate conditions. Tree-ring width series covering the period of 1914-2006 were built and correlated with mean monthly temperature and precipitation. Dependence of the growth of analysed firs on winter, early spring and summer temperature was observed. Significant relation to moisture availability was detected only for January. Analysis of pointer years revealed similar driving forces that were obtained by correlation and response function investigation. Reaction of firs from the Kaszubskie Lakeland to the extreme climate conditions is analogous to the exhibited at other sites of this species localised outside distribution range. Investigated silver firs seem to have found favourable growth conditions in the studied area and further cultivation of that species in northern Poland may turn to be successful. [ABSTRACT FROM AUTHOR]

Precipitation and air temperature data, only, are often recorded at meteorological stations, with radiation being measured at very few weather stations, especially in developing countries. Therefore there arises a need for suitable models to estimate solar radiation for a completion of data sets. -This paper is about an evaluation of eight models for an estimation of daily solar radiation (Q) from commonly measured variables in six synoptic stations of Iran, namely: Mashhad, Kerman, Tabriz, Esfehan, Hamedan and Zanjan using daily rainfall and temperature data for a duration of three years of 2000, 2001 and 2002. These stations represent several arid and semiarid sub-climates of Iran as based on extended-Dc Martonne climatic classification (semiarid-cold: Mashhad and Tabriz, arid-cold: Esfehan, Kerman, semiarid-extracold: Hamedan and Zanjan). The STATISTICA (ver. 6.0) software was employed for non-linear multivariate regression. The results indicated that most of the models overestimated in lower values of solar radiation while underestimating in the higher ranges, indicating a systematic error. Performance of the models was evaluated based on the Root Mean Square Errors (RMSE) as well as R2. RMSE ranged from 1.14 to 7.76 Cal -cm-2min-1 for the whole data range and in all the six stations. Among the eight models, the Richardson model rendered the best agreement with the measured data in Kerman and Zanjan stations. In case of Hamedan station, Bristow and Campbell model was the most suitable. As for Tabriz station; De Jong and Stewart model using rainfall and range of daily temperature data led to the best performance. In Mashhad station, McCaskill equation can be recommended. Analysis of the data in Esfehan station showed no significant difference among the models. Due to variation in equations' performances, to come to valid conclusions and to choose the most suitable radiation model, further study would be required from other climatic regions the country. [ABSTRACT FROM AUTHOR]

The historical climate record and seasonal temperature and precipitation records provide useful datasets for making short-term drought predictions. A variety of methods have exploited these resources, but few have quantitatively measured uncertainties associated with predictions of drought index values commonly used in management plans. In this paper, stochastic approaches for estimating uncertainty are applied to drought index predictions. National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) seasonal forecasts and resampling of nearest-neighbor residuals are incorporated to measure uncertainty in monthly forecasts of Palmer drought severity index (PDSI) and standardized precipitation index (SPI) in central South Carolina. Kuiper skill scores of PDSI indicate good forecast performance with up to 3-month lead time and improvements for 1-month-lead SPI forecasts. NOAA CPC climate outlook improved the forecast skill by as much as 40%, and the degree of improvement varies by season and forecast lead time. [ABSTRACT FROM AUTHOR]

This paper addresses some of the conceptual issues involved in the analysis of the age and origin of mediterranean-climate plant taxa, paying particular attention to three topics: (1) the importance of an explicit time frame in the definition of biogeographical origins, (2) the distinction between the age of traits and the age of taxa, and (3) the idea of mediterranean-type ecosystems as environmental islands. (1) In California, recent analyses demonstrate that the diversity of species derived from different biogeographical origins is significantly correlated with temperature and precipitation gradients. These patterns support the hypothesis that niche conservatism is an important factor structuring modern diversity gradients. However, depending on how far back in time one looks, a species may be assigned to different origins; future discussions of biogeographical origins need to address the appropriate time frame for analysis. (2) Past research has demonstrated distinctive trait syndromes among woody plants of the Mediterranean, Chile, California and Mexico, and proposed that the syndromes are associated with lineages of different age in these floras. Reanalysis of individual traits demonstrates greater variability among regions than previously reported. The classification of plants into ‘old’ and ‘new’ genera is re-evaluated, and it is suggested that greater attention be paid to the age of traits, rather than to the age of taxa, especially at an arbitrary rank such as genus. (3) The idea of mediterranean-climate regions as ‘climatic islands’ is examined. Space–time diagrams of climate enable one to view the emergence of distinctive climatic regions in a continental context. The terms ‘synclimatic’ and ‘anticlimatic’ are proposed, referring to migration routes that parallel climate contours in space and time versus those that cross contours (including the case of geographic stasis in the face of climate change), respectively. Mediterranean-climate regions have served as important case studies in plant ecology and evolution, and merit continued close examination in the light of continued advances in phylogenetics and palaeoecology. [ABSTRACT FROM AUTHOR]

This paper presents a method for grouping weather types that occur over an area, which combines meteorological parameters, reflecting air mass characteristics at the surface, with synoptic conditions prevailing over an area. Five quantitative meteorological parameters are used in the procedure: temperature, precipitation, relative humidity, wind velocity and sunshine duration. In addition, two qualitative variables related to the prevailing circulation type and whether it is cyclonic or anticyclonic are also included. The study period is 43 years (1958–2000) and is restricted to the cold and wet sub-period of the year, December–March. Weather types are defined using a relatively new method of cluster analysis, two-step cluster analysis, which allows the simultaneous use of both quantitative and qualitative variables. The aim of the present study is to distinguish primary weather patterns so that the investigation into the relationship between weather patterns and circulation types will be more effective. For Athens, six weather types are created, whereas for Thessaloniki five are produced. For both stations, only two weather types are related to anticyclonic situations. The majority of the identified weather types correspond to a distinctive and well-defined synoptic situation. Each weather type differs from the others, not only in terms of the circulation conditions referring to it, but also with reference to meteorological variables such as temperature and precipitation. The results of the evaluation of the aforementioned procedure are considered to be highly satisfactory. [ABSTRACT FROM AUTHOR]

A new bulk microphysical parameterization (BMP) has been developed for use with the Weather Research and Forecasting (WRF) Model or other mesoscale models. As compared with earlier single-moment BMPs, the new scheme incorporates a large number of improvements to both physical processes and computer coding, and it employs many techniques found in far more sophisticated spectral/bin schemes using lookup tables. Unlike any other BMP, the assumed snow size distribution depends on both ice water content and temperature and is represented as a sum of exponential and gamma distributions. Furthermore, snow assumes a nonspherical shape with a bulk density that varies inversely with diameter as found in observations and in contrast to nearly all other BMPs that assume spherical snow with constant density. The new scheme’s snow category was readily modified to match previous research in sensitivity experiments designed to test the sphericity and distribution shape characteristics. From analysis of four idealized sensitivity experiments, it was determined that the sphericity and constant density assumptions play a major role in producing supercooled liquid water whereas the assumed distribution shape plays a lesser, but nonnegligible, role. Further testing using numerous case studies and comparing model results with in situ and other observations confirmed the results of the idealized experiments and are briefly mentioned herein, but more detailed, microphysical comparisons with observations are found in a companion paper in this series (Part III, forthcoming). [ABSTRACT FROM AUTHOR]

In this paper a simplified UHF-band backscattering parameterization for individual melting snowflakes is proposed. This parameterization is a function of the density, shape, and melted fraction, and is used here in a brightband bulk modeling study. A 1D bulk model is developed where aggregation and breakup are neglected. Model results are in good agreement with detailed bin-model results and simulate the radar brightband observations well. It is shown the model can be seen as an observation operator that could be introduced into a data assimilation scheme to extract information contained in the radar data measurements. [ABSTRACT FROM AUTHOR]

Motivated by the intensity and severity of winds and temperature falls that frequently accompany rapidly developing cold fronts in northern Utah, this paper presents a 25-yr climatology of strong cold frontal passages over the Intermountain West and adjoining western United States. Using conventional surface observations and the North American Regional Reanalysis, strong cold frontal passages are identified based on a temperature fall of 7°C or greater in a 2–3-h period, a concurrent pressure rise of 3 hPa or greater, and the presence of a large-scale 700-hPa temperature gradient of at least 6°C (500 km)-1. The number of strong cold frontal passages exhibits a strong continental signature with very few events (<10) along the Pacific coast and more than 200 events east of the Continental Divide. The number of events increases dramatically from the Cascade Mountains and Sierra Nevada to northern Utah, indicating that the Intermountain West is a frequent cold front breeding ground. A composite of the 25 strongest events at Salt Lake City (based on the magnitude of the temperature fall) reveals that confluent deformation acting on a broad baroclinic zone over central Nevada commonly initiates Intermountain frontogenesis. The confluent deformation develops in southwesterly large-scale flow and appears to be enhanced by flow deflection around the Sierra Nevada. Quasi-stationary development and intensification of the southwest–northeast-oriented cold front then occurs as a mobile upper-level trough approaches from the west. The front becomes mobile as cold advection and ascent associated with the upper-level trough overtake the low-level front. Cloud and precipitation observations suggest that differential diabatic heating contributes to the rapid frontal intensification in many events. [ABSTRACT FROM AUTHOR]

High-quality, daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decision making. This paper describes the development, application, and assessment of methods to construct daily high-resolution (∼50-m cell size) meteorological grids for the 2003 calendar year in the Upper South Santiam Watershed (USSW), a 500-km2 mountainous catchment draining the western slope of the Oregon Cascade Mountains. Elevations within the USSW ranged from 194 to 1650 m. Meteorological elements modeled were minimum and maximum temperature; total precipitation, rainfall, and snowfall; and solar radiation and radiation-adjusted maximum temperature. The Parameter–Elevation Regressions on Independent Slopes Model (PRISM) was used to interpolate minimum and maximum temperature and precipitation. The separation of precipitation into rainfall and snowfall components used a temperature-based regression function. Solar radiation was simulated with the Image-Processing Workbench. Radiation-based adjustments to maximum temperature employed equations developed from data in the nearby H. J. Andrews Experimental Forest. The restrictive terrain of the USSW promoted cold-air drainage and temperature inversions by reducing large-scale airflow. Inversions were prominent nearly all year for minimum temperature and were noticeable even for maximum temperature during the autumn and winter. Precipitation generally increased with elevation over the USSW. In 2003, precipitation was nearly always in the form of rain at the lowest elevations but was about 50% snow at the highest elevations. Solar radiation followed a complex pattern related to terrain slope, aspect, and position relative to other terrain features. Clear, sunny days with a large proportion of direct radiation exhibited the greatest contrast in radiation totals, whereas cloudy days with primarily diffuse radiation showed little contrast. Radiation-adjusted maximum temperatures showed similar patterns. The lack of a high-quality observed dataset was a major issue in the interpolation of precipitation and solar radiation. However, observed data available for the USSW were superior to those available for most mountainous regions in the western United States. In this sense, the methods and results presented here can inform others performing similar studies in other mountainous regions. [ABSTRACT FROM AUTHOR]

The Western Arctic Linkage Experiment (WALE) is aimed at understanding the role of high-latitude terrestrial ecosystems in the response of the Arctic system to global change through collection and comparison of climate datasets and model results. In this paper, a spatiotemporal approach is taken to compare and validate model results from the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) with commonly used analysis and reanalysis datasets for monthly averages of temperature and precipitation in 1992–2000 and for a study area at 55°–65°N, 160°–110°W in northwestern Canada and Alaska. Objectives include a quantitative assessment of similarity between datasets and climate model fields, and identification of geographic areas and seasons that are problematic in modeling, with potential causes that may aid in model improvement. These are achieved by application of algebraic similarity mapping, a simple yet effective method for synoptic analysis of many (here, 45) different spatial datasets, maps, and models. Results indicate a dependence of model–data similarity on seasonality, on climate variable, and on geographic location. In summary, 1) similarity of data and models is better for temperature than for precipitation; and 2) modeling of summer precipitation fields, and to a lesser extent, temperature fields, appears more problematic than that of winter fields. The geographic distribution of areas with best and worst agreement shifts throughout the year, with generally better agreement between maps and models in the northeastern and northern inland areas than in topographically complex and near-coastal areas. The study contributes to an understanding of the geographic complexity of the Arctic system and modeling its diverse climate. [ABSTRACT FROM AUTHOR]