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For short lived climate forcers (SLCFs), the impact of emissions depends on where and when the emissions take place. Comprehensive new calculations of various emission metrics for SLCFs are presented based on radiative forcing (RF) values calculated in four different (chemistry-transport or coupled-chemistry climate) models. We distinguish between emissions during summer (May-October) and winter season (November-April) for emissions from Europe, East Asia, as well as the global shipping sector. The species included in this study are aerosols and aerosols precursors (BC, OC, SO2, NH3), and ozone precursors (NOx, CO, VOC), which also influence aerosols, to a lesser degree. Emission metrics for global climate responses of these emissions, as well as for CH4, have been calculated relative to CO2, using Global Warming Potential (GWP) and Global Temperature change Potential (GTP), based on dedicated RF simulations by four global models. The emission metrics include indirect cloud effects of aerosols and the semi-direct forcing for BC. In addition to the standard emission metrics for pulse and sustained emissions, we have also calculated a new emission metric designed for an emission profile consisting of a ramp up period of 15 years followed by sustained emissions, which is more appropriate for a gradual implementation of mitigation policies. For the aerosols, the emission metric values are larger in magnitude for Europe than East Asia and for summer than winter. A variation is also observed for the ozone precursors, with largest values in East Asia and winter for CO and in Europe and summer for VOC. In general, the variations between the emission metrics derived from different models are larger than the variations between regions and seasons, but the regional and seasonal variations for the best estimate also hold for most of the models individually. Further, the estimated climate impact of a mitigation policy package is robust even when accounting for correlations. For the ramp up emission metrics, the values are generally larger than for pulse or sustained emissions, which holds for all SLCFs. For a potential SLCFs mitigation policy, the dependency of metric values on the region and season of emission should be considered. [ABSTRACT FROM AUTHOR]

The article presents a study on the application of the Energy balance Snow Cover Integrated Model (ESCIMO), a spreadsheet-based point snow surface energy balance model to assess snow water equivalent (SWE), snow melt rates, and climate change. The study had recorded the temperature, precipitation, and humidity in an hourly basis with the model. Results indicate that ESCIMO.spread stimulates the impact of the climate change through the parameters which changes the temperature and precipitation.

Summary: Long‐term historical daily temperatures are used in electricity forecasting to simulate the probability distribution of future demand but can be affected by changes in recording site and climate. This paper presents a method of adjusting for the effect of these changes on daily maximum and minimum temperatures. The adjustment technique accommodates the autocorrelated and bivariate nature of the temperature data which has not previously been taken into account. The data are from Perth, Western Australia, the main electricity demand centre for the South‐West of Western Australia. The statistical modelling involves a multivariate extension of the univariate time series ‘interleaving method’, which allows fully efficient simultaneous estimation of the parameters of replicated Vector Autoregressive Moving Average processes. Temperatures at the most recent weather recording location in Perth are shown to be significantly lower compared to previous sites. There is also evidence of long‐term heating due to climate change especially for minimum temperatures. [ABSTRACT FROM AUTHOR]

This paper aims to study wet-cold compound events (WCCEs) over Greece for the wet and cold season November-April. WCCEs are divided in two different compound events (TX-RR) and (TN10 RR) and two different approaches using fixed (RR over 20 mm/day and Temperature under 0 oC) and percentile (RR over 95th and Temperature under 5th) thresholds. Observational data from the Hellenic National Meteorology Service (HNMS) and simulation data from reanalysis and EUROCORDEX models were used in the study for the historical period 1980-2004. Simulation datasets from projection models were employed for the near future period (2025-2049) to study the impact of climate change on the occurrence of WCCEs under RCP 4.5 and 8.5 scenarios. Following data processing and validation of the models, the potential changes in the distribution of WCCEs in the future were investigated based on the projected and historical simulations. WCCEs determined by fixed thresholds were mostly found over high altitudes with a future tendency to reduce particularly under RCP 8.5. On the other hand, WCCEs obtained with percentile thresholds, were distributed mostly in Eastern Greece and Crete while their changes differed significantly among models. [ABSTRACT FROM AUTHOR]

This paper describes the Coastal Ice Ocean Prediction System for the East Coast of Canada (CIOPS-E) running operationally at Environment and Climate Change Canada (ECCC). CIOPS-E uses a one-way downscaling technique on a 1/36° horizontal grid (~2 km) to simulate high-resolution ice and ocean conditions over the northwest Atlantic Ocean and the Gulf of St. Lawrence (GSL). CIOPS-E is forced at its lateral boundaries with ECCC's Regional Ice-Ocean Prediction System (RIOPS) and tidal conditions from the Oregon State University TPXO model. The three-dimensional temperature and salinity fields are spectrally nudged towards the RIOPS solution offshore of the 1500 m isobath to, effectively constrain mesoscale features in the Gulf Stream area. Over the continental shelf and the GSL, the CIOPS-E solution is free to develop fully according to model dynamics. CIOPS-E is evaluated over one year from March 2019 to February 2020. Overall, the CIOPS-E improves the representation of tides compared to ECCC's lower resolution systems: RIOPS (1/12°) and the Regional Marine Prediction System – Gulf of St. Lawrence (RMPS-GSL, 5 km). The accuracy of the tides are comparable to the TPXO at most coastal tide gauges. Sub-tidal water levels from CIOPS-E agree well with the observed seasonal variability and show improved errors statistics at all stations compared to RIOPS and RMPS-GSL. Improvements are especially noted for the GSL. Sea surface temperatures (SSTs) from CIOPS-E are lower (higher) in spring (fall) over most of the GSL compared to satellite-derived analyses and RIOPS. Comparison with in-situ observations of SST show significant improvement in CIOPS-E with respect to the RMPS-GSL. Lastly, sea ice conditions in the GSL are compared with the Canadian Ice Service (CIS) charts and the RMPS-GSL model. The sea ice cover and thickness from the pseudo-analysis component (without data assimilation) shows an overestimation compared to the CIS estimates, which is subsequently corrected in the forecast phase through the direct insertion of a Radarsat image analysis product. [ABSTRACT FROM AUTHOR]

We address the hypothetical question of whether an increasing total solar irradiance (TSI) trend, without anthropogenic contributions, could be sufficient to explain the ongoing global warming. To this end, the intermediate-complexity climate model PlaSim is used. To consider the total internal variability, we present a set of ensemble simulations, with different forcing histories in TSI and CO2 concentration, that have converged sufficiently tightly to the relevant probability distributions to provide a satisfactory bound on any spurious trend possibly arising from a sampling bias; similar bounds on any other unforced contributions to ensemble mean trends are also estimated. A key point is the consideration, among the forcing histories, the steepest increasing trend in TSI that is still consistent with observations according to a recent study; thereby, we essentially revisit corresponding TSI reconstructions, more than 20 years after their last modeling-based evaluation, by improving the analysis through taking care of all possible sources of error or uncertainty and incorporating data that have become available since then. Without any change in CO2 concentration, our TSI trend (i.e., and upper bound on actual TSI trends) is found to be insufficient to produce outcomes compatible with the observational record in global mean surface temperature (GMST) with a nonnegligible probability. We formalize our statement for quantifiers of GMST trends through evaluating their distributions over the ensemble, and we speculate that the hypothesis about the exclusive role of an increasing TSI remains implausible even beyond our particular model setup. At the same time, if we consider a constant TSI, and the observational record in CO2 concentration is applied as forcing, the simulation results and the recorded GMST match well. While we currently need to leave the question of a precise attribution open, we conclude by pointing out that an attribution of the ongoing global warming to an increasing TSI alone could be made plausible only if a bias in the set of land-based instrumental temperature measurements were increasing more rapidly than commonly estimated; an assessment of the latter possibility is out of the scope of our study, as well as addressing solar forcing mechanisms beyond the effect of TSI. [ABSTRACT FROM AUTHOR]

Climate change effects are most often presented with ongoing and expected temperature increase and sea level rise, but also stressed is the shift in rainfall patterns, often difficult to distinguish because there is much natural variability in precipitation. Statistical process control presents application of statistical methods and procedures for monitoring and control of the selected process. It aims to evaluate two potential sources of a process variation: natural (common) and assignable (special) causes. Statistical process control was recently used to evaluate climate change/variation, using previous referential period as a benchmark for addressing the present variations (e. g. in temperature or precipitation) as being triggered by natural or special causes. This means that either variation statistically should have been expected or the natural processes "capability" changed and variations are higher than one could expect. This paper analytically compares specific precipitation pattern changes in the three cities of Bosnia and Herzegovina with different annual participation. The comparison is based on the assessment of statistical behaviour of the precipitation data during the periods of 1961-1990 and after 1990. Such comparison allows preliminary conclusions on the studied geographical distribution of specific climate change/variation impacts. The presented results show that climate variations effect the precipitation patterns change, but do not confirm that they are as high as they could not be statistically expected, based on previous precipitation data. [ABSTRACT FROM AUTHOR]

Accurate measurements of temperature and water vapor in the upper-air are of great interest in relation to weather prediction and climate change. Those measurements are mostly conducted using radiosondes equipped with a variety of sensors that are flown by a balloon up to lower stratosphere. Reference Upper Air Network (GRUAN) has identified water vapor pressure as one of the most important measurands and has set an accuracy requirement of 2 % in terms of the mixing ratio. In order to achieve the requirement, many errors in the humidity measurement such as a temperature dependency in sensing characteristics including measurement values and response time need to be corrected because humidity sensors of radiosondes pass through low-pressure (1 kPa) and low-temperature (- 80 ∘ C) environments in the upper-air. In this paper, the humidity sensing characteristics of Jinyang radiosonde sensors in relation to temperature dependencies were evaluated at low temperature using a newly developed ultralow-temperature humidity chamber. The sensitivity characteristic curve of the radiosonde sensors was evaluated down to - 80 ∘ C, and the calibration curves of the humidity sensor and the temperature sensor were obtained. The response time of humidity sensor slowly increased from 52 to 116 s at the temperature from 20 to - 40 ∘ C, respectively, and then rapidly increased to almost one hour at - 80 ∘ C. Those results will help to improve the reliability of the upper-air observation data. [ABSTRACT FROM AUTHOR]

The urban heat island (UHI) phenomenon has become a concern in many major cities worldwide, as high summer temperatures and poor wind flow can have negative impacts on city dwellers, particularly increasing energy demand for artificial cooling. This paper showcases how an Integrated Multi-scale Environmental Urban Model (IMEUM) can be employed to support planners, architects and engineers to assess the combined impacts of the UHI phenomenon and rising global temperatures due to climate change. IMEUM concept derives from downscaling environmental models from global scale (25 km) to mesoscale (1 km) and city scale (100 m). Hence, this paper showcases a computationally efficient method which couples multi-scale atmospheric models with statistical model to estimate weather parameters. Developed under Singapore context, IMEUM can be utilized to incorporate appropriate UHI mitigation measures upfront in design process, consecutively bridging the gap between global and building scale. This paper also includes calibration of the IMEUM output using observations from ground sensors. Furthermore, by using case study of a hypothetical office building, this paper showcases how the IMEUM output can be fully converted into a localized weather data file for cooling load simulation. IMEUM is currently being developed further into integrated quantitative urban environment simulation tool (QUEST), which can be used to test the immediate microclimatic impact of development plans and assess their long term impacts under future climate change scenarios. [ABSTRACT FROM AUTHOR]

Satellite-based temperature measurements are an important indicator for global climate change studies over large areas. Records from Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Very High Resolution Radiometer (AVHRR) and (Advanced) Along Track Scanning Radiometer ((A)ATSR) are providing long-term time series information. Assessing the quality of remote sensing-based temperature measurements provides feedback to the climate modeling community and other users by identifying agreements and discrepancies when compared to temperature records from meteorological stations. This paper presents a comparison of state-of-the-art remote sensing-based land surface temperature data with air temperature measurements from meteorological stations on a pan-arctic scale (north of 60° latitude). Within this study, we compared land surface temperature products from (A)ATSR, MODIS and AVHRR with an in situ air temperature (Tair) database provided by the National Climate Data Center (NCDC). Despite analyzing the whole acquisition time period of each land surface temperature product, we focused on the inter-annual variability comparing land surface temperature (LST) and air temperature for the overlapping time period of the remote sensing data (2000-2005). In addition, land cover information was included in the evaluation approach by using GLC2000. MODIS has been identified as having the highest agreement in comparison to air temperature records. The time series of (A)ATSR is highly variable, whereas inconsistencies in land surface temperature data from AVHRR have been found. [ABSTRACT FROM AUTHOR]

Domestic heating in the ‘Hot Summer–Cold Winter’ climatic region of China attracts research attention for it is predicted to dramatically increase building energy consumption and associated greenhouse gas emissions. Determining the optimum heating temperature set point is an essential prerequisite for research, technology and policy development in this topic. This paper reviews instrumental and subjective research about occupants' thermal comfort and behavior in this climatic region, and advances a hypothesis as to why residents in the ‘Hot Summer–Cold Winter’ region are able to accept a lower temperature (16.5 °C) in winter than are predicted by the heat balance model (PMV/PPD) and ASHRAE's adaptive comfort model. The paper concludes by recommending heating temperature set point (17–18 °C) based on a lumped-parameter four-node steady-state model and a prediction about the heating mode that will be utilized in this region. [ABSTRACT FROM AUTHOR]

CO2 conversion to mitigate CO2 emissions is of great importance to reduce the negative impact of CO2 on climate change. Different technologies have been developed for CO2 conversion, including chemical, photocatalytic, electrochemical, and biological transformation. Among them, biological conversion by using Carbonic anhydrase (CA) to efficiently convert CO2 to HCO3- is a promising one, owing to its high specificity and selectivity under the mild condition and presenting environmentally friendly nature. The production of CO2 hydrates requires relatively high pressures and low temperatures, to make these applications feasible. However, free CA unable to withstand with too extreme temperature and pressure. Thus, the present work was conducted with the aim to determine the optimum parameter in the CO2 hydration using immobilized CA. In this research, CO2 hydrate were formed using CaCl biomimetic solution with an immobilized CA into PDVF membrane. Temperature variation from 30 to 85 °C and CO2 flowrate from 100 - 800 mL/min were evaluated for the CO2 hydration process. Time taken to reach pH 7 and the amount of CaCO3 precipitate formed during the process were used to elucidate the performance of the CO2 hydration process. The finding indicated that temperature plays an important role in reducing time taken for pH 7 to be reached. At 30 °C, 16 min was required for the CO2 hydration process and reaction time was decreased with the increasing of the temperature. At higher temperature of 85 °C, 3.4 min was recorded as an optimum time for the pH to turn to 7. Similar trend was observed with increasing of CO2 flowrate. Higher CO2 flowrate has shorter the time for the reaction to occur and 3 to 4 min was recorded as an optimum time for CO2 hydration process in the CO2 membrane reactor. This work might help comprehend CO2 hydrate storage technology, in separation of CO2 from methane gas and could give theoretical basis for subsequent applications in the sector. [ABSTRACT FROM AUTHOR]

Meteorological observations over the last four decades are of paramount importance to investigating ongoing climate change. An important issue is the quality and reliability of the climatic series, which are fundamental prerequisites to drawing the correct conclusions. Homogeneity tests are used to detect discontinuities whose interpretation is facilitated by metadata availability. In this work, daily minimum and maximum temperature measurements collected in Padua, Italy, between 1980 and 2022 are examined. During this period, the weather station of Padua center underwent many changes in location or instruments; therefore, some tests have been used to identify and remove their effects and obtain homogeneous series. Some well-known absolute tests have been applied to investigate the shift in the mean value: Standard Normal Homogeneity test (SNH), Buishand U and range tests, Pettitt test, F-test, and STARS. Relative tests have been applied too, using several stations nearby Padua and two reanalysis datasets (ERA5 and MERIDA) as reference series to enhance the picture of the local situation and provide more robust conclusions. The applied tests identify change-points in the years in which a change in instrument or the location of the station has occurred, confirming that these changes have compromised the homogeneity of the series. The sub-series obtained, splitting the observations in correspondence with these change-points, have been homogenized with respect to a selected period. The corrected series of the minimum and maximum temperatures are more coherent with the modern warming trend. The transfer functions to be applied to future measurements of minimum temperature have been calculated, while the series of maximum temperature measurements can be directly extended. [ABSTRACT FROM AUTHOR]

This paper studies the climatic conditions of warm and cold dry months in the humid and semi-humid Argentine region and some aspects of the regional circulation related to these cases. The climatic analysis of warm (temperatures above percentile 80) and cold (temperatures below percentile 20) dry months is based on precipitation and temperature data registered at reference stations over a period of at least 70 years, while the associated circulation is derived from daily data of geopotential height at 500 hPa from NCEP-DOE Reanalysis 2 database. The reference station for the center of the country registered a greater number of warm dry months during both the warm season (October-March) and the cold season (April-September), whereas the reference stations in the north-east and center-east showed differences depending on the time of the year, with more cold dry months during the April-September season and more warm dry months in the October-March season. A classification of daily fields of geopotential height anomalies at 500 hPa was used to analyze the atmospheric circulation related to warm and cold dry months. The circulation patterns were obtained by applying principal component analysis and cluster analysis. Findings show that some mid-level circulation patterns occur with a significant different frequency during the warm dry months or the cold dry months studied. Finally, cases of spatially extended precipitation-deficit conditions (hereinafter generalized droughts) were studied, noting dominant patterns that are coherent with the previous results. [ABSTRACT FROM AUTHOR]

Data from temperature measurements in boreholes are indicators of the temperature variations associated with past climate change. This paper is a contribution to reconstruct the ground surface temperature history (GSTH) from geothermal data in the eastern part of Morocco. From a set of several temperature logs, measured in the study area, only two were found suitable for estimating the ground surface temperature history (GSTH). In order to reconstruct the surface temperature past changes the functional space inversion method (FSI) was used. The inversion reveals a recent warming in the last century with respective amplitude of 0.1 °C and 1 °C for the boreholes 2952 in Oujda and 1624 in Berkane. These results can be confirmed by the air temperature record of the meteorical station in Oujda despite the scarceness of data beyond 1959. [ABSTRACT FROM AUTHOR]

Large-scale environmental, social, and economic impacts of recent weather and climate extremes are raising questions about whether the frequency and intensity of these extremes have been increasing. Here, the authors evaluate trends in climate extremes during the past half century using the U.S. High Plains as a case study. A total of eight different extreme indices and the standardized precipitation index (SPI) were evaluated using daily maximum and minimum temperature and precipitation data from 207 stations and 0.258 gridded data. The 1958-2010 time period was selected to exclude the 1950s and 2011 droughts. Results show general consistency between the station data and gridded data. The annual extreme temperature range (ETR) decreased significantly (p , 0.05) in ;54% of the High Plains, with a spatial mean rate of 20.78C decade21. Decreases in ETR result primarily from increases in annual lowest temperature in ;63% of the stations at a mean rate of ~0.9°C decade21, whereas increases in annual highest temperature were much less. Approximately 43% of the stations showed increasing warm nights (Tmin90) with a spatial mean rate of 0.5% decade21. Precipitation intensity generally did not vary significantly in most grid cells and stations. Significant decreasing trends in consecutive dry days (CDD) were restricted to 21% of the stations in the northern High Plains with a spatial mean of 20.8 days decade21. Areas experiencing severe dry periods (1-month SPI , 21.5) decreased over time from 8% to 4%. The number of dry months (SPI , 0) in each year also decreased. In summary, the ETR is decreasing and low temperatures are increasing. Precipitation extremes are generally not changing in the High Plains; however, high natural climatic variability in this semiarid region makes it difficult to assess climate extremes. [ABSTRACT FROM AUTHOR]

This paper assesses the extent to which temperature variability has increased in Austria since the late 19th century using a novel objective approach. The approach focuses on multi-day temperature episodes and isolates variability from changes in the long-term mean and seasonal variation. We define and compute three different indices of temperature variability, and find-based on 140 years of data-that temperature variability has evolved independently of mean temperature but with no long-term trend. Early 21st century's relatively raised temperature variability level is known from late 19th century's pre-greenhouse climate state. [ABSTRACT FROM AUTHOR]

Previous studies have indicated a widespread decline in snowpack over Utah accompanied by a decline in the snow-precipitation ratio while anecdotal evidence claims have been put forward that measured changes in Utah's snowpack are spurious and do not reflect actual change. Using two distinct lines of investigation, this paper further analyzes the winter precipitation regime in the state of Utah. First, by means of observation-based, gridded daily temperature, precipitation, and remotely sensed data, as well as utilizing a climatological rain-snow threshold (RST) temperature method, the precipitation regime of Utah was scrutinized. Second, a comprehensive synoptic analysis was conducted as an alternate means that is independent from surface observations. It was found that the proportion of winter (January-March) precipitation falling as snow has decreased by 9% during the last half century, a combined result from a significant increase in rainfall and a minor decrease in snowfall. Meanwhile, observed snow depth across Utah has decreased and is accompanied by consistent decreases in snow cover and surface albedo. Weather systems with the potential to produce precipitation in Utah have decreased in number with those producing snowfall decreasing at a considerably greater rate. Further circulation analysis showed that an anomalous anticyclone has developed over western North America, which acts to reduce the frequency of cyclone waves impacting Utah. Combined with the increased precipitation, this feature suggests that the average precipitation per event has intensified with more of it falling as rain than as snow. Trends in the hydroclimate such as these have implications for present and future regional water policy in the state of Utah. [ABSTRACT FROM AUTHOR]

Many areas of society are susceptible to the effects of extreme temperatures. Without an adequate definition of what constitutes heat and cold waves, it is impossible to assess either their changes in the past or their possible consequences for the future. The Intergovernmental Panel on Climate Change recommended criteria for heat wave duration indexes based on two arbitrarily defined constants. The principal weakness of this approach is that it does not yield comparable results for different geographical locations. This paper remedies the current lack of a meteorologically based definition of heat and cold waves and offers a preliminary test of its performance. Having previously shown that maximum daily temperature values follow normal frequency distribution, we derive statistical thresholds (e.g., below and above normal) from that distribution. These thresholds are thus climate specific and their change can be compared across geographical locations. These criteria are then tested on the homogeneous time series of maximum daily temperature observed for the period 1961-2008 with respect to three different geographical locations. The results obtained show an increase in the frequency of heat waves for the period 1991-2008 in comparison with the normal climatological period 1961-1990. [ABSTRACT FROM AUTHOR]

The U.S. Climate Reference Network (USCRN) was deployed between 2001 and 2008 for the purpose of yielding high-quality and temporally stable in situ climate observations in pristine environments over the twenty-first century. Given this mission, USCRN stations are engineered to operate largely autonomously with great reliability and accuracy. A triplicate approach is used to provide redundant measurements of temperature and precipitation at each location, allowing for observations at a specific time to be compared for quality control. This approach has proven to be robust in the most extreme environments, from extreme cold (−49°C) to extreme heat (++52°C), in areas of heavy precipitation (4700 mm yr−1), and in locations impacted by strong winds, freezing rain, and other hazards. In addition to a number of stations enduring extreme winter environments in Alaska and the northern United States, seven of the USCRN stations are located at elevations over 2000 m, including stations on Mauna Loa, Hawaii (3407 m) and on Niwot Ridge above Boulder, Colorado (2996 m). The USCRN temperature instruments and radiation shield have also been installed and run successfully at a station on the Quelccaya Ice Cap in Peru (5670 m). This paper reviews the performance of the USCRN station network during its brief lifetime and the potential utility of its triplicate temperature instrument configuration for measuring climate change at elevation. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of climate change on drought by addressing two questions: (1) How reliable is the assessment of climate change impact on drought based on state-of-the-art climate change projections and downscaling techniques? and (2) Will the impact be at the same level from meteorological, agricultural, and hydrologic perspectives? Regional climate change projections based on dynamical downscaling through regional climate models (RCMs) are used to assess drought frequency, intensity, and duration, and the impact propagation from meteorological to agricultural to hydrological systems. The impact on a meteorological drought index (standardized precipitation index, SPI) is first assessed on the basis of daily climate inputs from RCMs driven by three general circulation models (GCMs). Two periods and two emission scenarios, i.e., 1991-2000 and 2091-2100 under B1 and A1Fi for Parallel Climate Model (PCM), 1990-1999 and 2090-2099 under A1B and A1Fi for Community Climate System Model, version 3.0 (CCSM3), 1980-1989 and 2090-2099 under B2 and A2 for Hadley Centre CGCM (HadCM3), are undertaken and dynamically downscaled through the RCMs. The climate projections are fed to a calibrated hydro-agronomic model at the watershed scale in Central Illinois, and agricultural drought indexed by the standardized soil water index (SSWI) and hydrological drought by the standardized runoff index (SRI) and crop yield impacts are assessed. SSWI, in particular with extreme droughts, is more sensitive to climate change than either SPI or SRI. The climate change impact on drought in terms of intensity, frequency, and duration grows from meteorological to agricultural to hydrological drought, especially for CCSM3-RCM. Significant changes of SSWI and SRI are found because of the temperature increase and precipitation decrease during the crop season, as well as the nonlinear hydrological response to precipitation and temperature change. [ABSTRACT FROM AUTHOR]

A key issue of climate change is to identify the forcings and their relative contributions. The solar-climate relationship is currently the matter of a fierce debate. We address here the need for high quality observations and an adequate statistical approach. A recent work by Le Mouël et al. (2010) and its companion paper by Kossobokov et al. (2010) show spectacular correlations between solar activity and temperature series from three European weather stations over the last two centuries. We question both the data and the method used in these works. We stress (1) that correlation with solar forcing alone is meaningless unless other forcings are properly accounted for and that sunspot counting is a poor indicator of solar irradiance, (2) that long temperature series require homogenization to remove historical artefacts that affect long term variability, (3) that incorrect application of statistical tests leads to interpret as significant a signal which arises from pure random fluctuations. As a consequence, we reject the results and the conclusions of Le Mouël et al. (2010) and Kossobokov et al. (2010). We believe that our contribution bears some general interest in removing confusion from the scientific debate. [ABSTRACT FROM AUTHOR]

The climate change context has raised new problems in the computation of temperature return levels (RLs) in using the statistical extreme value theory. This arises since it is not yet possible to accept the hypothesis that the series of maxima or of high level values are stationary, without at least verifying the assumption. Thus, in this paper, different approaches are tested and compared to derive high order RLs in the nonstationary context. These RLs are computed by extrapolating identified trends, and a bootstrap method is used to estimate confidence intervals. The identification of trends can be made either in the parameters of the extreme value distributions or in the mean and variance of the whole series. Then, a methodology is proposed to test if the trends in extremes can be explained by the trends in mean and variance of the whole dataset. If this is the case, the future extremes can be derived from the stationary extremes of the centered and normalized variable and the changes in mean and variance of the whole dataset. The RL can then be estimated as nonstationary or as stationary for fixed future periods. The work is done for both extreme value methods: block maxima and peak over threshold, and will be illustrated with the example of a long observation time series for daily maximum temperature in France. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Drastic changes were detected in glacial systems of the Antarctic Peninsula in the last decades. The observed phenomena comprise the disintegration of ice shelves, acceleration and thinning of glaciers, and retreat of glacier fronts. However, due to the lack of consistent systematic observations in particular of the higher parts of the glacial systems, it is difficult to predict further responses of the Antarctic Peninsula glaciers to climatic change. The present paper analyses spatial and temporal variations of changes in the dry-snow line altitude on the Antarctic Peninsula as extracted from a time series (1992–2005) of ERS-1/2 SAR and Envisat ASAR data. Upward changes in dry-snow line altitude were observed in general, and are attributed to extreme high-temperature events impacting the central plateaus of the Antarctic Peninsula and the increasing duration of warming periods. A mean decrease in dry-snow line altitude was detected on the west side of the peninsula and is identified as a response to recorded increase in precipitation and accumulation. These results validate the capability of SAR data for deriving superficial parameters of glaciers to be used as indicators of climatic changes in high-latitude regions where operational restrictions limit conventional meteorological observations. [ABSTRACT FROM AUTHOR]

This paper explores changes in the principal components of observed energy budgets across the tropical Pacific in response to the strong 1998 El Niño event. Multisensor observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Visible and Infrared Scanner (VIRS), and precipitation radar (PR) instruments aboard TRMM are used to quantify changes in radiative and latent heating in the east and west Pacific in response to the different phases of the El Niño–Southern Oscillation. In periods of normal east–west SST gradients there is substantial heating in the west Pacific and cooling in the east, implying strong eastward atmospheric energy transport. During the active phase of the El Niño, both the east and west Pacific tend toward local radiative–convective equilibrium resulting in their temporary energetic decoupling. It is further demonstrated that the response of these regions to ENSO-induced SST variability is directly related to changes in the characteristics of clouds and precipitation in each region. Through quantitative analysis of the radiative and latent heating properties of shallow, midlevel, and deep precipitation events and an equivalent set of nonprecipitating cloud systems, times of reduced atmospheric heating are found to be associated with a shift toward shallow and midlevel precipitation systems and associated low-level cloudiness. The precipitation from such systems is typically less intense, and they do not trap outgoing longwave radiation as efficiently as their deeper counterparts, resulting in reduced radiative and latent heating of the atmosphere. The results also suggest that the net effect of precipitating systems on top-of-the-atmosphere (TOA) fluxes and the efficiency with which they heat the atmosphere and cool the surface exhibit strong dependence on their surroundings. The sensitivity of cloud radiative impacts to the atmospheric and surface properties they act to modify implies the existence of strong feedbacks whose representation may pose a significant challenge to the climate modeling community. [ABSTRACT FROM AUTHOR]

In 2004 a new aspirated surface air temperature system was officially deployed nationally in the U.S. Climate Reference Network (USCRN) commissioned by the National Oceanic and Atmospheric Administration. The primary goal of the USCRN is to provide future long-term and high-quality homogeneous observations of surface air temperature and precipitation that can be coupled to past long-term observations for the detection and attribution of present and future climate change. In this paper two precision air temperature systems are included for evaluating the new USCRN air temperature system based on a 1-yr side-by-side field comparison. The measurement errors of the USCRN temperature sensor are systematically analyzed, and the components of error attributable to the datalogger, lead wires, fixed resistors, and the temperature coefficient of the resistors are presented. Although the current configuration is adequate, a more desirable configuration of USCRN temperature sensor coupled with the datalogger is proposed as a means of further reducing the uncertainty for the USCRN temperature measurement. [ABSTRACT FROM AUTHOR]

The U.S. Historical Climate Network is a subset of surface weather observation stations selected from the National Weather Service cooperative station network. The criteria used to select these stations do not sufficiently address station exposure characteristics. In addition, the current metadata available for cooperative network stations generally do not describe site exposure characteristics in sufficient detail. This paper focuses on site exposures with respect to air temperature measurements. A total of 57 stations were photographically surveyed in eastern Colorado, comparing existing exposures to the standards endorsed by the World Meteorological Organization. The exposures of most sites surveyed, including U.S. Historical Climate Network sites, were observed to fall short of these standards. This raises a critical question about the use of many Historical Climate Network sites in the development of long-term climate records and the detection of climate trends. Some of these sites clearly have poor exposures and therefore should be considered for removal from the Historical Climate Network. Candidate replacement sites do exist and should be considered for addition into the network to replace the removed sites. Documentation as performed for this study should be conducted worldwide in order to determine the extent of spatially nonrepresentative exposures and possible temperature biases. [ABSTRACT FROM AUTHOR]

The objective of this paper is to focus on the influence of clouds and wind on air and road surface temperature variations between different types of local climate environments. The study area covers 160×130 km2 and includes 35 field stations in the Swedish Road Weather Information System (RWIS) and two synoptic weather stations. By combining data from the two sources, the spatial and temporal variations in air and road surface temperature have been analysed. In the first part of this paper the theoretical influence of different weather parameters is determined. In the empirical part of the study, a validation of the theoretical result is assessed using temperature and weather data from the study area. The results show that it is possible to calculate the temperature variations in relation to topographical siting and different weather factors. During day-time conditions, the effect of screening from the sun has a significant influence on the road surface temperature, even with cloudiness amounting to 4–6 octas, provided that the solar elevation is high. During night-time, the potential for pooling of cold air is determined by cloud cover and wind speed. When cloudy situations prevail during night-time, neutral stability is dominant resulting in a decrease with increasing altitude for both air and surface temperatures. Road surface temperatures, however, have a lower correlation with altitude than air temperature. The variation in surface temperature decreases with altitude is also larger and has a more even distribution than the air temperature decrease with altitude. Wind speed was not an important factor for the variation in surface temperature decrease with altitude, but insolation from the sun during day-time is one parameter to consider. Copyright © 2000 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Highlights • Identify homogeneous regions in China based on the maximum daily air temperature. • Reveal the intra-annual changing patterns of regionalization and trends. • Explore linkages of changing patterns of regionalization to climatic conditions. • Propose an objective hybrid clustering analysis for a better regionalization. Abstract Regionalization plays an important role in climatology and hydrology research, as it can be used to understand the changing pattern of a hydroclimate variable better and explore its underlying drivers effectively by identifying homogeneous regions which are determined by topography and climatic conditions. However, as climatic drivers change over time, homogeneous regions should vary when the intra-annual patterns are of interest. In this paper we investigate the regionalization and changing patterns of maximum daily temperature in China based on the maximum air temperature (Tmax) derived from the CN05.1 daily surface air temperature gridded data from 1981 to 2010. We also propose an objective variable-based regionalization approach by combining the rotated empirical orthogonal function (REOF) method and K-means clustering analysis, to determine homogeneous regions effectively for such a large volume of daily grid data. The REOF approach is not able to identify discrete regional boundaries easily, but it is efficient at determining the number of regions and their rough spatial location. Furthermore, while clustering analysis suffers from convergence when the number of observations is large, it is able to provide clean boundaries between regions. The hybrid method tends to overcome their individual disadvantages while maintaining their individual advantages. The results show that the patterns of homogeneous regions have distinct features in both summer and winter seasons. The reasonableness of regionalization is then examined by the first principal component within regions, which shows the homogeneity within regions, and the scatterplots of Tmax time series between regions, which show the heterogeneity between regions. Furthermore, the boxplots of normalized Tmax within regions for both summer and winter seasons also clearly show the different characteristics of inter-annual variability in each region. In order to reveal detailed process of the change in the number and pattern of regions, we further conducted the regionalization for individual months and explored the potential linkages between regionalization and climatic conditions over time. This research is noteworthy in promoting research on regionalization with consideration of seasonal and intra-annual variation as well as extreme temperature events. The proposed hybrid regionalization method is broadly applicable to other regionalization studies. [ABSTRACT FROM AUTHOR]

As major tourism economies in the Southern Mediterranean, Greece, Spain, and Turkey are particularly vulnerable to climate change. With mounting evidence of climate change, we study if the negative impact of climate change on Greece, Spain, and Turkey is particularly large. Empirically, we use a unique data set that makes temperature measurement more meaningful, and adopt the model in Ng and Zhao (Ecological Economics 70:963-970, 2011) to estimate the economic impacts of climate change on different types of economies. Our main finding is that climate change’s adverse impact on Greece, Spain, and Turkey is larger than its impacts on other types of economies, suggesting that Greece, Spain, and Turkey should engage in strong international cooperation to mitigate the adverse impact of climate change. [ABSTRACT FROM AUTHOR]

Changes in climate will exert increasing pressure on heritage, so standard climate metrics need to be tuned to heritage threats. Historical meteorological records are commonly available as monthly summaries, with few offering daily observations as daily readings may not have been taken or yet digitised. As data averaged over longer intervals misses short weather events, we investigate the extent to which temporal resolution is important for assessing climate pressures on façades. The Radcliffe Meteorological Station, Oxford, UK, provides the longest continual record of daily temperature and precipitation measurements in the UK. We use this record to assess the role of temporal scale in heritage climate parameters relating to (i) sunshine and warmth, (ii) rainy days and (iii) freezing events. Where there is a linear relationship between daily and monthly scale data, monthly observations can be interpolated as heritage climate parameters. However, for the majority of parameters, daily data was required to capture the variability in the datasets. We argue for the increased availability of daily observations to help assess the threat of climate to heritage. [ABSTRACT FROM AUTHOR]

Changes to the environment surrounding a temperature measuring station can cause local changes to the recorded temperature that deviate from regional temperature behavior. This phenomenon—often caused by construction or urbanization—occurs at a local level. If these local changes are assumed to represent regional or global processes it can have significant impacts on historical data analyses. These changes or deviations are generally gradual, but can be abrupt, and arise as construction or other environmental changes occur near a recording station. We propose a methodology to examine if changes in temperature behavior at a point in time exist at a local level at various locations in a region assuming that regional or global processes are correlated among nearby stations. Specifically, we propose a Bayesian change point model for spatio‐temporally dependent data where we select the number of change points at each location using a "forward" selection process using deviance information criterion. We then fit the selected version of the model and examine the linear slopes across time to quantify the local changes in long‐term temperature behavior. We show the utility of this model and method using both synthetic data and observed temperature measurements from eight stations in Utah consisting of daily temperature data for 60 years. [ABSTRACT FROM AUTHOR]

Bangladesh is very vulnerable to the impacts of climate change, and adaptation is emerging as a key policy response. Place based programs that build adaptive capacity are needed. This paper explores the effectiveness of formal institutions in climate change adaptation for agriculture from the perspectives of farmers and institutional communities of practice within two drought-prone areas in Bangladesh. Our findings show that formal institutions via their communities of practice play an important role in building place based capacity for mitigation and adaptation strategies in agriculture. Over-emphasis on technology, lack of acknowledgement of cultural factors and a failure of institutional communities of practice to mediate and create linkages with informal institutional communities of practice remain barriers. We argue that in order for formal institutions to play an ongoing and crucial role in building adaptive agriculture in Bangladesh, they must incorporate cultural mechanisms and build partnerships with more community based informal institutions. [ABSTRACT FROM AUTHOR]

As one of the most important geographical units affected by global climate change, lakes are sensitive to climatic changes and are considered "indicators" of climate and the environment. In this study, changes in the spatial-temporal characteristics of the water levels of 204 global major lakes are systematically analyzed using satellite altimetry data (Hydroweb product) from 2002 to 2010. Additionally, the responses of the major global lake levels to climatic fluctuations are analyzed using Global Land Surface Assimilation System (GLDAS) data (temperature and precipitation). The results show that the change rates of most global lakes exceed 0, which means that the lake levels of these lakes are rising. The change rates of the lake levels are between -0.3~0.3 m/a, which indicates that the rate of change in the water-level of most lakes is not obvious. A few lakes have a particularly sharp change rate, between -5.84~-2 m/a or 0.7~1.87 m/a. Lakes with increasing levels are mainly located in the mountain and plateau regions, and the change rates in the coastal highlands are more evident. The global temperatures rise by a change rate of 0.0058 °C/a, while the global precipitation decreases by a change rate of -0.6697 mm/a. However, there are significant regional differences in both temperature and precipitation. In addition, the impact of precipitation on the water level of lakes is significant and straightforward, while the impact of temperature is more complex. A study of lake levels on a global scale would be quite useful for a better understanding of the impact which climate change has on surface water resources. [ABSTRACT FROM AUTHOR]

The literature on metrics to measure contributions to climate change from emissions of different greenhouse gases divides into studies that highlight physical aspects and studies that show the importance of economic factors. This paper distinguishes the physical aspects and implications of economic factors by asking what is demanded from physically based metrics if used for a specific policy objective. We study the aim of maximizing the welfare of emissions generated by consumption when there is a limit to the increase in global mean temperature. In that case, metrics ought to change over time, with increasing weight on short-living gases before the temperature limit is met. Metrics for short-living gases increase also with increasing uncertainty. Adjustments to new information spur higher metrics for short-living gases if it reduces the expected allowable emissions before the target is met, and lower metrics in the opposite case. Under a binding target, metrics refer to the instantaneous impact on radiative forcing multiplied by the lifetime of the respective gases, and adjusted by the attitude to risk. [ABSTRACT FROM AUTHOR]

Although the global climate is changing at an unprecedented rate, links between weather and infectious disease have received little attention in high income countries. The "El Niño Southern Oscillation" (ENSO) occurs irregularly and is associated with changing temperature and precipitation patterns. We studied the impact of ENSO on infectious diseases in four census regions in the United States. We evaluated infectious diseases requiring hospitalization using the US National Hospital Discharge Survey (1970-2010) and five disease groupings that may undergo epidemiological shifts with changing climate: (i) vector-borne diseases, (ii) pneumonia and influenza, (iii) enteric disease, (iv) zoonotic bacterial disease, and (v) fungal disease. ENSO exposure was based on the Multivariate ENSO Index. Distributed lag models, with adjustment for seasonal oscillation and long-term trends, were used to evaluate the impact of ENSO on disease incidence over lags of up to 12 mo. ENSO was associated more with vector-borne disease [relative risk (RR) 2.96, 95% confidence interval (CI) 1.03-8.48] and less with enteric disease (0.73, 95% CI 0.62-0.87) in the Western region; the increase in vector-borne disease was attributable to increased risk of rickettsioses and tick-borne infectious diseases. By contrast, ENSO was associated with more enteric disease in non-Western regions (RR 1.12, 95% CI 1.02-1.15). The periodic nature of ENSO may make it a useful natural experiment for evaluation of the impact of climatic shifts on infectious disease risk. The impact of ENSO suggests that warmer temperatures and extreme variation in precipitation events influence risks of vector-borne and enteric disease in the United States. [ABSTRACT FROM AUTHOR]

The study of climate trends taking into consideration possible structural changes is important for understanding climate development characterized by a stochastic trend or by a determined one. In the paper global and hemisphere temperature anomalies are modeled by piecewise linear regression and break points in the temperature evolution are found. It was demonstrated that the used method allowed finding of breaks characterized by long time trends (low frequency processes) as well as abrupt changes (fast frequency processes). The obtained break points for slow temperature change are close to the ones found by other authors however additional conditions (as segment length, gradient and others) are not used here. The results for higher break point numbers are like the ones of step slope models. It was demonstrated that the successive phases of warming and cooling and most of the break points subdividing these periods in the Northern Hemisphere are introduced by the Atlantic multidecadal oscillation. Because the strong quasi periodicity of the Atlantic multidecadal oscillation the authors recommend the removal of its influence on the temperature from the temperature series before studies of trends or structural changes. The Northern Hemisphere temperature data after the removal of the Atlantic multidecadal oscillation influence show structures like the Southern Hemisphere temperatures. Model selection by the Schwarz–Bayesian Information Criterion developed by Liu, Wu and Zidek (LWZ criterion) shows that models with only one break point are to be preferred. [ABSTRACT FROM AUTHOR]

The El Nino-Southern Oscillation (ENSO) phenomenon is the most important form of tropical climate change. By modifying the distribution of rainfall and temperatures, it sometimes engenders devastating effects in many tropical regions and even in high latitudes. The aim of this study was to choose the El Nino event as a potential predictor for long-term precipitation forecast in Iraq in the presence of opposite patterns in Iraq's precipitation distribution at different phases of the El Nino event. The results indicate that calculating the frequency of occurrence of precipitation gradations in Iraq during the warm and cold phases of ENSO are presented in Tables 2 and 3. [ABSTRACT FROM AUTHOR]

The early Pleistocene site of Barranco León (Guadix-Baza Basin, SE Spain), dated to 1.4 Ma (millions of years ago), records the oldest hominin occurrence in Western Europe, as evidenced by the discovery of one tooth and thousands of Mode 1 stone tools. In this paper a detailed analysis of the microvertebrate content of the D1 and D2 units from this site is presented. The early Pleistocene in the Guadix-Baza Basin is characterized by a sharp climatic deterioration, which possibly impeded the settlement of this region by the early hominin population from the southern Caucasus. Shortly afterwards, when the climatic conditions were again favorable, a hominin presence is suddenly evidenced at the units D1 and D2 of Barranco León. According to the microvertebrate analysis of these units, the mean annual temperature at the time of deposition was significantly higher than 13 °C, with prevalent humid conditions. However, although most of the species were inhabitants of water edges, an open landscape was present in the vicinity of the lake. The data reported here clearly support the idea that the early hominin occupation of Europe was strongly constrained by climatic and environmental conditions, rather than by physiography or cultural factors. [ABSTRACT FROM AUTHOR]

Urban heat island and global warming increase ambient temperature and modify the energy budget of buildings. The magnitude of the modification has been evaluated in a large number of articles, under different climatic and building boundary conditions. This paper collects, analyzes and classifies existing knowledge regarding the energy impact of urban heating to buildings and calculates preliminary indicators and impact figures. Based on the analysis of the impact studies, it is found that in average the cooling load of typical urban buildings is by 13% higher compared to similar buildings in rural areas. Four specific energy impact indicators, the global energy penalty per m 2 , the global energy penalty per m 2 and degree of UHI, the global energy penalty per person and the global energy penalty per person and per degree of the UHI are defined and calculated. The variability of the heating and cooling loads of typical buildings is evaluated for the period 1970–2010. The average increase of the cooling demand is 23% while the corresponding average reduction of the heating is 19%. In total, the average energy consumption of typical buildings for heating and cooling purposes increased by 11% for the same period. [ABSTRACT FROM AUTHOR]

Solar radiation is an important climatic variable and widely used in building performance monitoring and analysis. However, due to sensor malfunction, data transmission problems, and quality assurance issues, there are often short-term or long-term missing data on solar radiation. These gaps are challenging for engineers involved in building performance monitoring and control. This paper examines and compares three different approaches, namely, singular spectrum analysis (SSA), statistically adjusted solar radiation (SASR), and the temperature-based approach (TBA), for restoring missing solar data. The TBA, SASR, and SSA are applied to fill artificial gaps which are generated continuously as representative of up to 25 days missing data in actual hourly solar radiation data of Oklahoma City North (OKCN) for 2012 and Albuquerque for 2005. Results show that SSA outperforms the other methods for filling solar radiation gaps of up to 5 days. For gaps up to 20 days, the SSA and TBA have similar performance. For gaps larger than 20 days, the TBA is more suitable. The SASR performs similarly to the TBA for dry and sunny Alburquerque climates, but worse in OKCN. Accuracy of the SSA decreases with increasing gap lengths. The study concludes by recommending appropriate methods for different gap lengths. [ABSTRACT FROM AUTHOR]