Daily Meteorological Observations Research Articles

Adaptive Kalman Filtering for Postprocessing Ensemble Numerical Weather Predictions

Forecasts from numerical weather prediction models suffer from systematic and nonsystematic errors, which originate from various sources such as subgrid-scale variability affecting large scales. Statistical postprocessing techniques can partly remove such errors. Adaptive MOS techniques based on Kalman filters (here called AMOS), are used to sequentially postprocess the forecasts, by continuously updating the correction parameters as new ground observations become available. These techniques, originally proposed for deterministic forecasts, are valuable when long training datasets do not exist. Here, a new adaptive postprocessing technique for ensemble predictions (called AEMOS) is introduced. The proposed method implements a Kalman filtering approach that fully exploits the information content of the ensemble for updating the parameters of the postprocessing equation. A verification study for the region of Campania in southern Italy is performed. Two years (2014–15) of daily meteorological observations of 10-m wind speed and 2-m temperature from 18 ground-based automatic weather stations are used, comparing them with the corresponding COSMO-LEPS ensemble forecasts. It is shown that the proposed adaptive method outperforms the AMOS method, while it shows comparable results to the member-by-member batch postprocessing approach.

Impact of climate change on quantity and area of forest fires in the northern part of the Black Sea Region of Ukraine

The aim of this study consists in assessment of impact of change of thermal regime, air moisture and weather phenomena on quantity and area of forest fires in the northern part of the Black Sea Region of Ukraine, their possible changes and consequences by the middle of XXI century with regard to modern climatic period for SRESA1B scenario and setting of some proportion of uncertainty of these changes.
 The study of regional peculiarities of climate change was performed on the basis of daily meteorological observations over the period of 1961-2013 in the context of Kherson region. To assess impact of weather conditions on fire safety data on number of forest fires and their area in the region over 1996-2013 (about 4 000 cases of fire) were used. The study was carried out using regression and correlation analysis. Calculation projections of climate characteristics’ change resulting in forest fires was performed for the period of 2021-2050 with relation to modern climatic period (1981-2010) using the data of regional climate model REMO with resolution of 25 km initiated by ECHAM5 global model calculation.
 It was found that number and area of forest fires in the northern part of the Black Sea Region of Ukraine is largely dependent on thermal regime, moisture and wind regime. Influence of temperature appears to be decisive and affects area of fires rather than their number. For example, increase of annual / summer average air temperature by 1°C can lead to increase of average area of fire almost by 110% and 90% respectively and increase of number of days with atmospheric drought and heat (maximum temperature above 30°C) by 10 days can cause increase of average area of fires by 130% and 80%. At the same time air temperature in September and October has a significant impact on number of fires: increase of monthly average air temperature by 1°C can lead to increase of number of fires by 20%.
 Climate change analysis conducted in Kherson oblast resulted in finding that over the recent decades the region faced a significant change of thermal regime, moisture and wind regime, recurrence of weather phenomena affecting number and area of forest fires. These changes led to increase of fire risks in the region. Evaluation of possible changes of these characteristics by the middle of the XXI century showed that the under SRES A1B scenario the region might expect further increase of temperature throughout the year, growth of number of hot days and duration of sultry period. Since these processes are accompanied by increase of duration of dry period these changes will significantly affect fire risk increase – number of forest fires and their area by the middle of the XXI century in Kherson region may significantly grow.
 Obtained results can be used to develop plans for adaptation to climate change.

Spatio-temporal trends in fire weather in the French Alps

The Alpine area is particularly sensitive to climatic and environmental changes that might impact socio-ecosystems and modify the regime of natural hazards. Among them, wildfire is of major importance as it threatens both ecosystems and human lives and infrastructures. Wildfires result from complex interactions between available vegetation fuels, climate and weather, and humans who decide of the land use and are the main source of fire ignitions.The changes in fire weather during the past decades are rather unknown in the French Alps especially due to their complex topography. Moreover, local institutions and managers wonder if the ongoing climate changes might increase fire risk and affect the environmental quality and the different ecosystem services provided by the mountain forests.In this context, we used the national forest fires database together with daily meteorological observations from 1959 to 2015 to investigate the changes in wildfire danger in the French Alps. We analysed the spatial and temporal variations in terms of intensity, frequency, seasonality and window of opportunity of two fire weather indices: the fine fuel moisture code (FFMC) and the fire weather index (FWI) that measure the daily water content of vegetation and the potential intensity of fires, respectively.Our results showed a major contrast between Southern Alps with a high fire weather danger on average and a significant increase in the past decades, and Northern Alps with low to moderate danger on average that increased only at low elevations. This study contributes to the understanding of the consequences of ongoings climate changes on wildfires in the French Alps. It produced high resolution results that account for the topographic and climatic variability of the area. Finally, the maps of the different fire weather components have practical implications for fire management and modelling and for preventing indirect effects of fires on ecosystems and human assets.

CPLFD-GDPT5: High-resolution gridded daily precipitation and temperature data set for two largest Polish river basins

Abstract. The CHASE-PL (Climate change impact assessment for selected sectors in Poland) Forcing Data–Gridded Daily Precipitation & Temperature Dataset–5 km (CPLFD-GDPT5) consists of 1951–2013 daily minimum and maximum air temperatures and precipitation totals interpolated onto a 5 km grid based on daily meteorological observations from the Institute of Meteorology and Water Management (IMGW-PIB; Polish stations), Deutscher Wetterdienst (DWD, German and Czech stations), and European Climate Assessment and Dataset (ECAD) and National Oceanic and Atmosphere Administration–National Climatic Data Center (NOAA-NCDC) (Slovak, Ukrainian, and Belarusian stations). The main purpose for constructing this product was the need for long-term aerial precipitation and temperature data for earth-system modelling, especially hydrological modelling. The spatial coverage is the union of the Vistula and Oder basins and Polish territory. The number of available meteorological stations for precipitation and temperature varies in time from about 100 for temperature and 300 for precipitation in the 1950s up to about 180 for temperature and 700 for precipitation in the 1990s. The precipitation data set was corrected for snowfall and rainfall under-catch with the Richter method. The interpolation methods were kriging with elevation as external drift for temperatures and indicator kriging combined with universal kriging for precipitation. The kriging cross validation revealed low root-mean-squared errors expressed as a fraction of standard deviation (SD): 0.54 and 0.47 for minimum and maximum temperature, respectively, and 0.79 for precipitation. The correlation scores were 0.84 for minimum temperatures, 0.88 for maximum temperatures, and 0.65 for precipitation. The CPLFD-GDPT5 product is consistent with 1971–2000 climatic data published by IMGW-PIB. We also confirm good skill of the product for hydrological modelling by performing an application using the Soil and Water Assessment Tool (SWAT) in the Vistula and Oder basins. Link to the data set: doi:10.4121/uuid:e939aec0-bdd1-440f-bd1e-c49ff10d0a07.

Ensemble seasonal forecast of extreme water inflow into a large reservoir

Abstract. An approach to seasonal ensemble forecast of unregulated water inflow into a large reservoir was developed. The approach is founded on a physically-based semi-distributed hydrological model ECOMAG driven by Monte-Carlo generated ensembles of weather scenarios for a specified lead-time of the forecast (3 months ahead in this study). Case study was carried out for the Cheboksary reservoir (catchment area is 374 000 km2) located on the middle Volga River. Initial watershed conditions on the forecast date (1 March for spring freshet and 1 June for summer low-water period) were simulated by the hydrological model forced by daily meteorological observations several months prior to the forecast date. A spatially distributed stochastic weather generator was used to produce time-series of daily weather scenarios for the forecast lead-time. Ensemble of daily water inflow into the reservoir was obtained by driving the ECOMAG model with the generated weather time-series. The proposed ensemble forecast technique was verified on the basis of the hindcast simulations for 29 spring and summer seasons beginning from 1982 (the year of the reservoir filling to capacity) to 2010. The verification criteria were used in order to evaluate an ability of the proposed technique to forecast freshet/low-water events of the pre-assigned severity categories.

110 years of temperature observations at Orcadas Antarctic Station: multidecadal variability

ABSTRACTThere is growing evidence of significant changes in components of the Antarctic climate system, an important issue given the influence Antarctica has on global climate. It is important to infer to what extent these regional changes could be attributed to human‐induced processes and to what extent to natural variability. Standard methods such as linear trend estimates or piecewise linear trends can be inadequate because they may result in erratic, non‐systematic results, particularly if different scales of variability are present in each record and various records are to be compared. The Orcadas Antarctic Station (Argentina), with daily surface meteorological observations since April 1903, provides Antarctica's longest observational record. This study analyses the Orcadas seasonal surface temperature variability. Multidecadal variability and short‐term trends are studied to provide an improved assessment of climate evolution and necessary information for the determination of mechanisms driving regional/local change. A combined method using wavelet transform (WT), non‐linear statistical model approaches and derivative of fits is developed. This methodology is also applied for validation and comparison to the Gomez ice core oxygen isotope record for the 1857–2006 and 1903–2006 time intervals. Significant quasi 50‐year and quasi 20‐year variability bands were obtained, both for the quarterly and seasonal Orcadas temperature records, with warming (cooling) periods detected between 1903–1912, 1927–1961 and 1972–2004 (1912–1927 and 1962–1972). If seasons are considered, the only one with a fairly sustained warming is summer, where actual cooling is observed only at the beginning, prior to the early 1930s. Quasi 50‐year variability was also detected in the Gomez record. Long periods are obtained in the model fits, longer than the time series, which varied with window length. Although not representing variability cycles, they could represent the best fit of the non‐linear, non oscillating asymptotic stationary component of the series, i.e. a non‐linear trend.

Моделирование экстремального наводнения в дельте Дона на многопроцессорных вычислительных системах

According to the materials of daily meteorological observations in the period from March 20 to March 26, 2013 the restoration of abnormal flooding Don delta were carried out. For calculations of water level and volume of incoming water into the delta of the Don the two-layer mathematical model were carried out. The calculations were carried on multiprocessor computer systems installed in the Southern Federal University.

Estimating uncertainty in daily weather interpolations: a Bayesian framework for developing climate surfaces

Conservation of biodiversity demands comprehension of evolutionary and ecological patterns and processes that occur over vast spatial and temporal scales. A central goal of ecology is to understand the climatic factors that control ecological processes and this has become even more important in the face of climate change. Especially at global scales, there can be enormous uncertainty in underlying environmental data used to explain ecological processes, but that uncertainty is rarely quantified or incorporated into ecological models. In this study, a climate-aided Bayesian kriging approach is used to interpolate 20 years of daily meteorological observations (maximum and minimum temperatures and precipitation) to a 1 arc-min grid for the Cape Floristic Region of South Africa. Independent validation data revealed overall predictive performance of the interpolation to have R2 values of 0.90, 0.85, and 0.59 for maximum temperature, minimum temperature, and precipitation, respectively. A suite of ecologically relevant climate metrics that include the uncertainty introduced by the interpolation were then generated. By providing the high-resolution climate metric surfaces and uncertainties, this work facilitates richer and more robust predictive modelling in ecology and biogeography. These data can be incorporated into ecological models to propagate the uncertainties through to the final predictions.

Severe dust storms in Central Asia

The study of the spatial distribution of the severe and very severe dust storms over the Central Asian area has been carried out. The dust storm event can be considered as severe if it lasts 3–12 h, storms with wind speed 10–14 m/s and meteorological visibility in the range of 500–1000 m. The extremely severe dust storms last more than 12 h, with the wind speed exceeding 15 m/s; the dust storms with meteorological visibility less than 50 m are considered as very severe regardless to duration and wind speed. The data of daily meteorological observations from 144 meteorological stations of Kazakhstan and 29 meteorological stations in Uzbekistan and Turkmenistan for the period 1936–1972 had been analyzed, and number of days with severe and very severe dust storms had been calculated using above criteria. Relation between the number of days with dust events and number of severe and very severe storms was calculated, and map of spatial distribution of severe events in Central Asia was compiled using this relation. The analysis of extremely severe dust storms, which developed under the exits of southern cyclones, was done.

Recent climate change: Long-term trends in meteorological forest fire danger in the Alps

Climate change is one of the key issues in current scientific research. In this paper we investigate the impacts of rising temperatures and changing precipitation patterns on meteorological forest fire danger in the Alps. Our analysis is based on daily meteorological observations from 25 long-term stations in six Alpine countries. The selected stations are distributed more or less uniformly over the whole Alpine area and represent the different climate regions in this complex terrain. Stations with similar climatological conditions were grouped into regions. These were: Western Alps, Northern Alps, inner Alpine area and Southern Alps. The meteorological forest fire danger in the time period 1951–2010 was assessed on the basis of different forest fire danger indices (FWI, Nesterov, Baumgartner, etc.) calculated on a daily basis. A statistical percentile analysis revealed different impacts of recent climate change in the four regions. A significant increase in forest fire danger occurred at the stations in the Western Alps and even more strongly in the Southern Alps. Here, the yearly averaged fire danger increased during the past six decades. Additionally, in recent years the number of days with elevated forest fire danger (indices above a pre-defined threshold) has also increased. A comparatively weak increase was observed in the Northern Alps and no clear signal was evident at the stations in the inner Alpine valleys. In order to analyze extreme events (highest index value per year and region) extreme values statistics was applied. It was shown that the return period of extraordinarily high index values has decreased significantly over the past decades, especially in the Western and Southern Alps.For three pilot areas (Valais in the Western Alps, Bavaria in the Northern Alpine region and Ticino in the Southern Alps) a comparison with observed historical fire data is shown. In Valais, a region in the Western Alps with a generally low fire hazard, a weak trend toward more forest fires and more area burned could be found. The correlation between calculated indices and observed fires was quite low in this region. In Bavaria (Northern Alps) this correlation was higher, but while the trend of forest fires in Bavaria was decreasing in terms of number and burned area, the meteorological fire danger in contrast increased. Reasons for this contrasting trend may be related to altered anthropogenic factors such as less military activities, technical progress, and higher awareness. The correlation between indices and forest fires south of the Alps (Ticino) was considerably lower because here most forest fires occurred in winter when the meteorological fire danger is usually lower than in summer. In this region a positive trend in meteorological fire danger over recent decades was also counterbalanced by decreasing anthropogenic ignitions.

Verification of a Synthesized Method for the Calculation of Low-Level Climatological Wind Fields Using a Mesoscale Boundary-Layer Model

Low-level climatological wind fields over the La Plata River region of South America are synthesized with a dry, hydrostatic mesoscale boundary-layer numerical model. The model is forced at the upper boundary with the 1200 UTC local radiosonde observations and at the lower boundary with a land-river differential heating function defined from the daily meteorological observations of the region. The climatological wind field is defined as the mean value of a series of individual daily forecasts, employing two methods. The simplified method considers a 192-member ensemble (16 wind directions and 12 wind-speed classes at the upper boundary). Each member has a probability of occurrence that is determined from the 1959–1984 observations; the daily method uses a total of 3,248 days with available data during the same period. In both methods each realization is a daily forecast from which the mean wind distributions at 0300, 0900, 1500 and 2100 local standard time are calculated and compared to the observations of five meteorological stations in the region. The validation of the climatological wind fields for both methods is evaluated by means of the root-mean-square error of the wind-direction frequency distribution and mean wind speed by wind sector. The results obtained with the two methods are similar, and the errors in wind speed are always smaller than those in wind direction. The combined errors of wind direction and wind speed show that the ensemble method is outperformed by the daily method, on average by meteorological station in only one out of five of them, and on average by the time of the day in only one out of 4 h. The conclusion of the study is that the ensemble method is an appropriate methodology for determining high resolution, low-level climatological wind fields, with the boundary-layer model applied to a region with a strong diurnal cycle of surface thermal contrast. The proposed methodology is of particular utility for synthesizing wind fields over regions with limited meteorological observations, since the 192-member matrix can be easily defined with few observing points, as well as in the case of relatively incomplete records.

Spatial coherency of extreme weather events in Germany and Switzerland

AbstractWith a simple statistical approach, the spatial representativeness of extreme events in daily meteorological surface observations from Germany and Switzerland is analysed. A percentile‐based definition of extremes is employed, and the frequency of simultaneously occurring extreme events at different stations is used as a measure for their spatial coherency. The largest representativeness is diagnosed for daily temperature extremes, i.e. hot and cold days, which very often occur simultaneously at many stations. On the contrary, precipitation extremes usually are restricted to local or regional scales. The spatial coherency of wind gust maxima is intermediate between the other extremes and depends on station location and terrain complexity. For cold extremes, station altitude has a strong influence on the spatial coherency of the events. It is argued that the spatial representativeness of extreme weather events directly relates to the importance of a coherent large‐scale atmospheric forcing, compared to more local factors, for triggering these events. In particular, large‐scale advection is the most important driver of temperature extremes. Strong wind gusts are often caused by mid‐latitude cyclones over the North Sea. The results from this study can also be used to assess the spatial representativeness of extreme weather reconstructions from proxy data in paleoclimate studies. Copyright © 2011 Royal Meteorological Society

Climatic conditions and their impact on viticulture in the Upper Moselle region

Climate parameters, especially temperature, sunlight, and precipitation, play a decisive role in growing and maturing processes. The aim of this study is to investigate the relationship between climate variability and variations in phenological events in viticulture. Long time series of daily meteorological observations are used to quantify these relations. The primary aim is to predict the date of phenological events by relationships between plant morphology and environmental conditions. Causal relationships between environment and internal activities of the vine (phytochemistry, cellular interactions, molecular and cell biology) are not our focus. The dates of the phenological events are important for planning treatments in the vineyards like pest management, for predicting the duration of the ripening phase and estimating the quality of the grapes and the vintage. The focus is layed on the region of the Upper Moselle, especially the Luxembourgian viticulture. First the regional climate and the phenological states of different vine varieties during the time period 1951–2005 are analysed. Significant trends are detected in annual, spring and summer temperatures. Vine phenology is also found to have changed significantly; budburst date and flowering events occur earlier by about two weeks. In a second step, relationships between phenological events and climate parameters are used to develop a prediction model. The parameterisation used in this study is based on a linear multiple regression method with forward and backward steps. The predictors tested are mainly temperature means for different time periods or temperature derived indices. In addition precipitation and sunshine duration for different time periods are evaluated, but only the temperature based predictors showed sufficient skill. For the budburst event, the significant predictors are the accumulated degree days in March, the mean daily maximum temperature in April and the accumulated frost days from January to March. The flowering event is best predicted by the accumulated degree days in May and April, the mean daily maximum temperature in June, and the date of the budburst event. Depending on the vine variety and the phenological event, the model explains 80–89% of the variance and has a correlation coefficient above 0.90 with the observations.

Evaluation of 13 Empirical Reference Potential Evapotranspiration Equations on the Island of Crete in Southern Greece

Knowledge of reference potential evapotranspiration (PETref) conditions is important for a number of vegetation- and hydro- logical-related applications. Direct estimations of PETref are difficult and require sophisticated instrumentation. The Food and Agriculture Organization (FAO), therefore, proposed a method for the estimation of PETref using only meteorological data. This equation has been widely accepted as the standard method for the estimation of PETref because of its good fit with measured values. Nevertheless, it requires several meteorological variables (e.g., wind speed), which are rarely available. Where such data are not available, its application is hampered. To overcome this problem, a number of simpler, empirical equations requiring only a fraction of the meteorological input variables required by the FAO PETref have been developed. Before using these equations, it is important to evaluate their performance and choose the equation that will have the lowest possible bias in the estimation of PETref. Using daily meteorological observations obtained from seven meteorological stations on the island of Crete (southern Greece), the performance of 13 empirical equations (radiation- and temperature-based) for the estimation of PETref has been evaluated against the estimations of PETref using the FAO equation. Performance was evaluated on a daily and a monthly basis, and five different measures of goodness offit were used. The results showed that when the use of the FAO equation is not possible because of the unavailability of data, some empirical methods can serve as appropriate alternatives. The radiation-based equations generally performed better than those that included only temperature-related input variables. The equations proposed by Hansen and Turc were the most useful because they had an average monthly absolute error ranging from 5.7 to 17.7 mm and 5.5 to 19.2 mm, respectively. DOI: 10.1061/(ASCE)IR.1943-4774.0000283. © 2011 American Society of Civil Engineers. CE Database subject headings: Evapotranspiration; Evaluation; Performance characteristics; Validation; Greece. Author keywords: Evapotranspiration; Evaluation; Performance characteristics; Validation.

The effect of thermal stress on superovulatory response and embryo production in Bharat Merino ewes

This experiment was conducted to observe the effect of thermal stress during estrous cycle on superovulatory response and subsequent embryo production in Bharat Merino ewes (fine wool crossbred developed for the tropical environment). Fourteen cycling, multiparous ewes were randomly allocated to two groups ( n=7/group). The animals in Group-I were maintained in a shed from 10.00 to 16.00 h while animals in Group-II were exposed to the elevated temperature for a period of 6 h (10.00–16.00 h) for 4 weeks. Animals grazed on natural pasture of Cenchrus ciliaris during the morning (7.00–10.00 h) and evening hours (16.30–19.30 h), and drinking water was offered once daily at 16.30 h. Daily meteorological observations were recorded during the trial. Superovulation was induced in all the ewes using FSH (ovagen 5.4 mg in eight injections) and PMSG (200 IU). Estrus in the ewes was synchronized with 2 doses of PGF2α (10 mg) 10 days apart. Ewes demonstrating estrus were hand mated with the aid of Bharat Merino rams. Ovarian examination and embryo/ova recovery were performed using laparoscopy on days 3–5 following mating. All the ewes exhibited estrus within 48 h after the second PGF2α injection. Ewes in Group-I exhibited estrus earlier (25.5±1.1 h) and the estrus period was longer (37.7±1.6 h) than ewes exposed to thermal stress, i.e. 30.6±1.2 and 31.7±3.6 h, respectively. No significant difference were observed for the two groups with respect to the superovulatory response and embryo/ova recovery rate. The ewes exposed to thermal stress yielded relatively poor quality embryos. The results indicate that thermal stress could adversely affected the quality of the embryos in Bharat Merino sheep during the preovulatory period.

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using a production efficiency approach. In this study, the 2001 MODIS GPP product was compared with scaled GPP estimates (25 km 2) based on ground measurements at two forested sites. The ground-based GPP scaling approach relied on a carbon cycle process model run in a spatially distributed mode. Land cover classification and maximum annual leaf area index, as derived from Landsat ETM+ imagery, were used in model initiation. The model was driven by daily meteorological observations from an eddy covariance flux tower situated at the center of each site. Model simulated GPPs were corroborated with daily GPP estimates from the flux tower. At the hardwood forest site, the MODIS GPP phenology started earlier than was indicated by the scaled GPP, and the summertime GPP from MODIS was generally lower than the scaled GPP values. The fall-off in production at the end of the growing season was similar to the validation data. At the boreal forest site, the GPP phenologies generally agreed because both responded to the strong signal associated with minimum temperature. The midsummer MODIS GPP there was generally higher than the ground-based GPP. The differences between the MODIS GPP products and the ground-based GPPs were driven by differences in the timing of FPAR and the magnitude of light use efficiency as well as by differences in other inputs to the MODIS GPP algorithm—daily incident PAR, minimum temperature, and vapor pressure deficit. Ground-based scaling of GPP has the potential to improve the parameterization of light use efficiency in satellite-based GPP monitoring algorithms.

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using a production efficiency approach. In this study, the 2001 MODIS GPP product was compared with scaled GPP estimates (25 km2) based on ground measurements at two forested sites. The ground-based GPP scaling approach relied on a carbon cycle process model run in a spatially distributed mode. Land cover classification and maximum annual leaf area index, as derived from Landsat ETM+ imagery, were used in model initiation. The model was driven by daily meteorological observations from an eddy covariance flux tower situated at the center of each site. Model simulated GPPs were corroborated with daily GPP estimates from the flux tower. At the hardwood forest site, the MODIS GPP phenology started earlier than was indicated by the scaled GPP, and the summertime GPP from MODIS was generally lower than the scaled GPP values. The fall-off in production at the end of the growing season was similar to the validation data. At the boreal forest site, the GPP phenologies generally agreed because both responded to the strong signal associated with minimum temperature. The midsummer MODIS GPP there was generally higher than the ground-based GPP. The differences between the MODIS GPP products and the ground-based GPPs were driven by differences in the timing of FPAR and the magnitude of light use efficiency as well as by differences in other inputs to the MODIS GPP algorithm—daily incident PAR, minimum temperature, and vapor pressure deficit. Ground-based scaling of GPP has the potential to improve the parameterization of light use efficiency in satellite-based GPP monitoring algorithms.

Climate in the Czech Lands during the 1780s in light of the daily weather records of parson Karel Bernard Hein of Hodonice (southwestern Moravia): Comparison of documentary and instrumental data

Visual daily meteorological observations are analysed according to the diary of parson Karel Bernard Hein of Hodonice near Znojmo (south-western Moravia), carried out from 1 February 1780 to 5 October 1789. Records written in Latin are a complement of the description of events of everyday life. They allow characterisation of temperature and precipitation patterns of the individual months and frequencies of occurrence of selected weather phenomena (thunderstorm, fog). On the basis of monthly temperature and precipitation indices derived from the interpretation of Hein's reports, a quantitative interpretation of temperatures and precipitation is performed for the meteorological station Kuchařovice in the 1780s with respectto the reference period 1961–2000. Hein's records are further compared withregular meteorological observations of the station Prague-Klementinum and in the broader European context with data from Austria, Germany and Switzerland. From the comparison, a good agreement is evident according to documentary evidence and instrumental measurements. Hein's records are, together with further written sources and meteorological measurements, utilised for describing extreme periods during the 1780s in the Czech Lands (from the view of measurements of the station Prague-Klementinum): the warm summer of 1783, the hard winter of 1783/84, the hitherto coldest March and spring of 1785, the hitherto coldest autumn of 1786, and the hard winter of 1788/89 with so far the coldest December.

Estimating daily recharge to the Chalk aquifer of southern England – a simple methodology

Abstract. A simple, practical model for estimating daily recharge - as hydrologically effective rainfall (HER) - to the Chalk outcrop of southern England is presented. Daily meteorological observations are the only data requirements. The model was calibrated for a Chalk river, the Wey, in south Dorset. Six different root constant thresholds were used to estimate daily actual evapotranspiration (AET) rates for the river. The model was then used to calculate HER using the six estimates of AET. Daily mean flow was simulated using three different models: CAPTAIN, IHACRES and INCA. The six HER estimates provided independent model inputs. HER calculated using a root constant of 200mm proved suitable not only for the Wey, but also (via a validation exercise) for other rivers on the Chalk of southern England for riverflow simulations as well as the timing and magnitude of groundwater recharge. The results suggest that a root constant of 200mm is optimal for the Chalk outcrop of southern England. The model is particularly useful for studies where the application of more complex methods of recharge estimation is impractical. Keywords: Chalk aquifer, root constant, recharge, Hydrologically Effective Rainfall, model, riverflow, CAPTAIN, IHACRES, INCA, River Wey

The climate attractor over short timescales

Recent work has highlighted the possibilities of using certain ideas from the theory of dynamical systems for the study of global climate. These ideas include the geometrical notion of correlation or scaling dimension, first used to analyse attractors arising in mathematical and laboratory systems1–4 and later applied in a geophysical context5,6. The conclusion of the original geophysical work5 has been criticized in the light of a reanalysis7 which questions the existence of a low-dimensional climate attractor. Here results of a similar analysis conducted on daily meteorological observations from 1946 to 1982, are announced. This new work overcomes limitations of previous analyses, and supports the existence of such an attractor.