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1.
This paper compares precipitation, maximum and minimum air temperature and solar radiation estimates from the Hadley Centre’s HadRM3 regional climate model (RCM), (50 × 50 km grid cells), with observed data from 15 meteorological station in the UK, for the period 1960–90. The aim was to investigate how well the HadRM3 is able to represent weather characteristics for a historical period (hindcast) for which validation data exist. The rationale was to determine if the HadRM3 data contain systematic errors and to investigate how suitable the data are for use in climate change impact studies at particular locations. Comparing modelled and observed data helps assess and quantify the uncertainty introduced to climate impact studies. The results show that the model performs very well for some locations and weather variable combinations, but poorly for others. Maximum temperature estimations are generally good, but minimum temperature is overestimated and extreme cold events are not represented well. For precipitation, the model produces too many small events leading to a serious under estimation of the number of dry days (zero precipitation), whilst also over- or underestimating the mean annual total. Estimates represent well the temporal distribution of precipitation events. The model systematically over-estimates solar radiation, but does produce good quality estimates at some locations. It is concluded that the HadRM3 data are unsuitable for detailed (i.e. daily time step simulation model based) site-specific impacts studies in their current form. However, the close similarity between modelled and observed data for the historical case raises the potential for using simple adjustment methods and applying these to future projection data.  相似文献   
2.
We present multiwavelength observations (from optical to submillimetre, including Spitzer and Submillimetre Common-User Bolometer Array) of H2XMMJ 003357.2−120038 (also GD 158_19), an X-ray selected, luminous narrow-line (type 2) quasar at   z = 1.957  selected from the HELLAS2XMM survey. Its broad-band properties can be reasonably well modelled assuming three components: a stellar component to account for the optical and near-infrared (IR) emission; an active galactic nucleus (AGN) component (i.e. dust heated by an accreting active nucleus), dominant in the mid-IR, with an optical depth at 9.7      along the line of sight (close to the equatorial plane of the obscuring matter) of  τ(9.7) = 1  and a full covering angle of the reprocessing matter (torus) of 140° and a far-IR starburst component (i.e. dust heated by star formation) to reproduce the wide bump observed longward of 70      .
The derived star formation rate is  ≈1500 M⊙ yr−1  . The overall modelling indicates that GD 158_19 is a high-redshift X-ray luminous, obscured quasar with coeval powerful AGN activity and intense star formation. It is probably caught before the process of expelling the obscuring gas has started, thus quenching the star formation.  相似文献   
3.
This paper has exploited, for Central and Southern Italy (Mediterranean Sub-regional Area), an unprecedented historical dataset as an attempt to model seasonal (winter and summer) air temperatures in pre-instrumental time (back to 1500). Combining information derived from proxy–documentary data and large-scale simulation, a statistical downscaling approach in the form of mixed regression model was developed to adapt larger-scale estimations (regional component) to the sub-regional temperature pattern (local component). It interprets local temperature anomalies by means of monthly based Temperature Anomaly Scaled Index in the range ?5 (very cold conditions in June) to 2 (very warm conditions). The modelled response agrees well with the independent data from the validation sample (Nash–Sutcliffe efficiency coefficient, >0.60). The advantage of the approach is not merely increased accuracy in estimation. Rather, it relies on the ability to extract (and exploit) the right information to replicate coherent temperature series in historical times.  相似文献   
4.
This study reveals the changes and evolution of rainstorm-driven intermediate floods occurring and driving multiple damaging hydrological events in the Rhone River Basin (RRB), since 1500 until 2010. A parsimonious approach was developed to simulate the major hydroclimatological flood-producing forcing, the Multiscale Rainstorm Climate Model (STORMCLIMM). We collected the frequency of intermediate floods—a type of particularly hazardous floods commonly taking place between June and beginning of November—from the RCB to be compared to STORMCLIMM estimates. The latter, smoothed by a moving window of 21 years, results in a high-pass filter in the time domain, which magnifies the signal of forcing variations causing intermediate floods. The RRB showed large temporal variations in both extreme rainstorms and associated multidecadal intermediate-floods (MUDIF) frequency at different climatic periods and land-use systems through historical times. An important peak was observed in the Maunder Minimum (1645–1715 AD). The model allowed detecting MUDIF occurred in the historical times. The situation becomes interesting with respect to recent times, because the Rhone landscape looks more vulnerable in the last decades as a consequence of land-use changes and climate shift towards more erratic and intensive storms. This evidence suggests that the interactions of land-use and climatic changes may turn into considerable vulnerability to fluvial flooding and agro-ecosystem connected to them for upcoming years. The Rhone, for example, provides basis for use of hydrological indicators (such as the one represented by STORMCLIMM) for one site or region and which, through minor modifications, can be made relevant to specific needs.  相似文献   
5.
An understanding of the weather drivers of soil erosion necessitates an extended instrumental meteorological series and knowledge of the processes linking climate and hydrology. The nature of such linkages remains poorly understood for the Mediterranean region. This gap is addressed through a composite analysis of long‐term climatic controls on rain erosivity in the Calore River Basin (southern Italy) for the period 1869–2006. Based on a parsimonious interpretation of rainstorm processes, a model (comparable with the Revised Universal Soil Loss Equation) was adapted to generate erosivity values on different time‐aggregation scales (yearly and seasonal). The evolution of the generated series of cumulated and extreme erosivity events was assessed by two return period (T) quantiles via a 22‐year moving window analysis (low return period, T = 2 years; high return period, T = 50 years). Erosivity extremes are shown to be characterized by increasing yearly trends (at a 100‐year rate of ～150 MJ mm ha–1 h–1 for T = 2 years and ～800 MJ mm ha–1 h–1 for T = 50 years), especially during the spring and autumn seasons. Quantile patterns on the extremes are also shown to be decoupled from trends in the cumulated values. The Buishand test was applied to detect the presence of temporal change points, and a wavelet spectrum analysis used for time‐frequency localization of climate signals. A change‐point in the evolution of climate is revealed over the 1970s in the spring series, which correlates to a distinct rain erosivity increase. The results indicate that soil erosion risk tends to rise as a consequence of an escalation of the climate erosive hazard, predominantly between April and November (associated with cultivation and tillage practices). Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   
6.
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7.
A crop simulation model must first be capable of representing the actual performance of crops grown in any region before it can be applied to the prediction of climate variability and change impacts. A cropping systems model (CropSyst) simulations of crop productivity in the sub-Saharan Central African (using Cameroon as the case study) region, under the current climate were compared with observed yields of maize, sorghum, groundnut, bambara groundnut and soybean from eight sites. The model produced both over-and-under estimates, but with a mean percentage difference of only –2.8%, ranging from –0.6% to –4.5%. Based on these results, we judged the CropSyst simulations sufficiently reliable to justify use of the model in assessing crop growth vulnerability to climatic changes in Cameroon and else where.  相似文献   
8.
The advent of instrumental and digital weather observatories has not eliminated the substantial gaps within surface meteorological time series. In particular, the lack of long-term homogeneous snowfall records may be a major impediment for hydrologic studies. We tested the hypothesis that reliable estimates of snowy days per year (SDY) can be produced for peninsular Italy, based on weather and site measurements from a limited set of stations centrally located in the Central Mediterranean Area. The core weather data are those from three observatories: Naples (40° 51′ N, 14° 15′ E, 150 m a.s.l.), Rome (41° 53′ N, 12° 28′ E, 100 m a.s.l.) and Montevergine (40° 56′ N, 14° 43′ E, 1280 m a.s.l.). A linear multivariate regression model (LMRM) was developed with candidate predictors (elevation, snowfall days and winter temperatures) for SDY reconstructions in the Benevento Valley (calibration site), whose homogenised SDY time series covers the period 1869–2018 (the longest in Southern Italy, extending back to 1832 thanks to documentary proxies but with missing values from 1911 to 1949). Three validation sites across peninsular Italy were considered: Vesuvius (40° 49′ N, 14° 24′ E, 605 m a.s.l.), Perugia (43° 05′ N, 12° 30′ E, 205 m a.s.l.) and Padua (45° 23′ N, 11° 51′ E, 15 m a.s.l.). The percent relative mean absolute error (%RMAE) for Benevento Valley was 20.2%, and though higher model errors were encountered at validation sites, they were in an acceptable range (32.6, 39.3 and 39.5% at Vesuvius, Perugia and Padua, respectively). Our SDY reconstruction in the Benevento Valley parallels, the pattern of water discharge occurred in the region during the same period, whose fluctuations result in changes of the pattern of snowfall days (i.e. decreasing snowfall days in recent times was accompanied by decreasing groundwater levels). This corroborates that the approach used to reconstruct SDY data takes dominant climate controlling factors of hydrological changes. We conclude that the LMRM, a statistically developed model, is physically meaningful and may be reasonably used for estimating SDY in peninsular Italy roughly down from the sub-Alpine range.  相似文献   
9.
Groundwater extraction is used to alleviate drought in many habitats. However, widespread drought decreases spring discharge and there is a need to integrate climate change research into resource management and action. Accurate estimates of groundwater discharge may be valuable in improving decision support systems of hydrogeological resource exploitation. The present study performs a forecast for groundwater discharge in Aquifer?s Cervialto Mountains(southern Italy). A time series starting in 1883 was the basis for longterm predictions. An Ensemble Discharge Prediction(EDis P) was applied, and the progress of the discharge ensemble forecast was inferred with the aid of an Exponential Smoothing(ES) model initialized at different annual times. EDisP-ES hindcast model experiments were tested, and discharge plume-patterns forecast was assessed with horizon placed in the year 2044. A 46-year cycle pattern was identified by comparing simulations and observations, which is essential for the forecasting purpose. ED is P-ES performed an ensemble mean path for the coming decades that indicates a discharge regime within ± 1 standard deviation around the mean value of 4.1 m~3 s~(-1). These fluctuations are comparable with those observed in the period 1961-1980 and further back, with changepoints detectable around the years 2025 and 2035. Temporary drought conditions are expected after the year 2030.  相似文献   
10.
Complexity‐reduction modelling can be useful for increasing the understanding of how the climate affects basin soil moisture response upon historical times not covered by detailed hydrological data. For this purpose, here is presented and assessed an empirical regression‐based model, the European Soil Moisture Empirical Downscaling (ESMED), in which different climatic variables, easily available on the web, are addressed for simplifying the inherent complexity in the long‐time studies. To accommodate this simplification, the Palmer Drought Severity Index, the precipitation, the elevation and the geographical location were used as input data in the ESMED model for predicting annual soil moisture budget. The test area was a large region including central Europe and Mediterranean countries, and the spatial resolution was initially set at 50 km. ESMED model calibration was made according to the soil moisture values retrieved from the Terrestrial Water Budget Data archive by selecting randomly 285 grid points (out of 2606). Once parameterized, ESMED model was performed at validation stage both spatially and temporally. The spatial validation was made for the grid points not selected in the calibration stage while the comparison with the soil moisture outputs of the Global Land Data Assimilation System–NOAH10 simulations upon the period 1950–2010 was carried out for the temporal validation. Moreover, ESMED results were found to be in good agreement with a root‐zone soil moisture product obtained from active and passive microwave sensors from various satellite missions. ESMED model was thus found to be reliable for both the temporal and spatial validations and, hence, it might represent a useful tool to characterize the long‐term dynamics of soil moisture–weather interaction. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   
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