A simple method for generating daily rainfall data

Geng, Shaoqing; Vries, F.W.T. Penning de; Supit, Iwan

doi:10.1016/0168-1923(86)90014-6

Cited by 185 publications

(146 citation statements)

References 16 publications

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“…With this, temperature and cloudiness were downscaled with a cubic-spline-function between the monthly averages, which were assigned to the middle of each month. Precipitation was distributed equally over the number of wet days per month which were distributed within the month using a two-state, firstorder Markov Chain, applying the parameterization according to Geng et al (1986).…”

Section: Baselinementioning

confidence: 99%

Effect of modelling scale on the assessment of climate change impact on river runoff

Piniewski

Voß

Bärlund

et al. 2013

Hydrological Sciences Journal

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The effect of using two distributed hydrological models with different degrees of spatial aggregation on the assessment of climate change impact on river runoff was investigated. Analyses were conducted in the Narew River basin situated in northeast Poland using a global hydrological model (WaterGAP) and a catchment-scale hydrological model (SWAT). Climate change was represented in both models by projected changes in monthly temperature and precipitation between the period 2040-2069 and the baseline period, resulting from two general circulation models: IPSL-CM4 and MIROC3.2, both coupled with the SRES A2 emissions scenario. The degree of consistency between the global and the catchment model was very high for mean annual runoff, and medium for indicators of high and low runoff. It was observed that SWAT generally suggests changes of larger magnitude than WaterGAP for both climate models, but SWAT and WaterGAP were consistent as regards the direction of change in monthly runoff. The results indicate that a global model can be used in Central and Eastern European lowlands to identify hot-spots where a catchment-scale model should be applied to evaluate, e.g. the effectiveness of management options.

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Section: Baselinementioning

confidence: 99%

Effect of modelling scale on the assessment of climate change impact on river runoff

Piniewski

Voß

Bärlund

et al. 2013

Hydrological Sciences Journal

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“…Transient simulations, beginning in 1901 and ending in 2005, included CO 2 concentrations from CDIAC (Keeling and Whorf, 2005) and soil texture characteristics from FAO (Zobler, 1986). Monthly temperature and precipitation were interpolated to quasi-daily values, while monthly precipitation was randomly distributed to quasi-daily values using a weather generator dependent on number of wet days per month (Geng et al, 1986), or daily climate data were used when available (Table 1). Cloud cover was converted to photosynthetic active radiation (PAR) following Prentice et al (1993) and transmissivity coefficients of Linacre (1968).…”

Section: Forcing Datamentioning

confidence: 99%

Impacts of land cover and climate data selection on understanding terrestrial carbon dynamics and the CO<sub>2</sub> airborne fraction

et al. 2011

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Abstract. Terrestrial and oceanic carbon cycle processes remove ∼55 % of global carbon emissions, with the remaining 45 %, known as the "airborne fraction", accumulating in the atmosphere. The long-term dynamics of the component fluxes contributing to the airborne fraction are challenging to interpret, but important for informing fossil-fuel emission targets and for monitoring the trends of biospheric carbon fluxes. Climate and land-cover forcing data for terrestrial ecosystem models are a largely unexplored source of uncertainty in terms of their contribution to understanding airborne fraction dynamics. Here we present results using a single dynamic global vegetation model forced by an ensemble experiment of climate (CRU, ERA-Interim, NCEP-DOE II), and diagnostic land-cover datasets (GLC2000, GlobCover, MODIS). For the averaging period 1996-2005, forcing uncertainties resulted in a large range of simulated global carbon fluxes, up to 13 % for net primary production (52.4 to 60.2 Pg C a −1 ) and 19 % for soil respiration (44.2 to 54.8 Pg C a −1 ). The sensitivity of contemporary global terrestrial carbon fluxes to climate strongly depends on forcing data (1.2-5.9 Pg C K −1 or 0.5 to 2.7 ppmv CO 2 K −1 ), but weakening carbon sinks in sub-tropical regions and strengthening carbon sinks in northern latitudes are found to be robust. The climate and land-cover combination that best correlate to the inferred carbon sink, and with the lowest residuals, is from observational data (CRU) rather than reanalysis climate data and with land-cover categories that have more stringent criteria for forest cover (MODIS). Since 1998, an increasing positive trend in residual error from bottom-up accounting of global sinks and sources (from 0.03 (1989-2005) to 0.23 Pg C a −1 (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)) suggests that either modeled drought sensitivity of carbon fluxes is too high, or that carbon emissions from net land-cover change is too large.

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“…Three types of weather data may be used as an input: (1) daily weather, (2) monthly weather data (WOFOST format; Hijmans et al, 1994) and (3) long-term average weather data with monthly values averaged over a long period. Monthly or long-term average weather data were transformed to daily values using the approach of Geng et al (1986).…”

Section: Weather and Soil Datamentioning

confidence: 99%

A physiological production model for cocoa (Theobroma cacao): model presentation, validation and application

Zuidema

Leffelaar

Gerritsma

et al. 2005

Agricultural Systems

185

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In spite of the economic importance and extensive agronomic literature on cocoa, no physiological production model has been developed for cocoa so far. Such a model would be very useful to compare yields in different climates and cropping systems, and to set the agenda for future agronomic research. Here, we present and apply such a physiological growth and production model for cocoa (SUCROS-Cocoa), based on the SUCROS-family of physiological crop growth models. Our model calculates light interception, photosynthesis, maintenance respiration, evapotranspiration, biomass production and bean yield for cocoa trees grown under shade trees. It can cope with both potential and water-limited situations, and is parameterised using existing information on cocoa physiology and morphology. A validation study showed that the model produces realistic output for bean yield, standing biomass, leaf area and The model was applied to answer four questions that are currently relevant to cocoa production. (1) Which are the most important yield-determining parameters? Sensitivity analyses revealed that these parameters were chiefly related to the morphology of fruits, photosynthesis and maintenance respiration. (2) To what extent can cocoa yield be predicted by rainfall and irradiance data? Regression analyses showed that over 70% of the variation in simulated bean yield could be explained by a combination of annual radiation and rainfall during the two driest months. (3) How large is the cocoa yield gap due to water limitation? Yield gaps were large -up to 50% -for locations with a strong dry season combined with an unfavourable (clayey or sandy) soil. The calculated yield gaps decreased exponentially with the amount of rain during the two driest months. (4) What are the consequences of shading on cocoa yield? Our simulations showed that moderate shade levels hardly affected bean yield, whereas heavy shading (>60%) reduced yields by more than one-third.

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A simple method for generating daily rainfall data

Cited by 185 publications

References 16 publications

Effect of modelling scale on the assessment of climate change impact on river runoff

Effect of modelling scale on the assessment of climate change impact on river runoff

Impacts of land cover and climate data selection on understanding terrestrial carbon dynamics and the CO<sub>2</sub> airborne fraction

A physiological production model for cocoa (Theobroma cacao): model presentation, validation and application

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A simple method for generating daily rainfall data

Cited by 185 publications

References 16 publications

Effect of modelling scale on the assessment of climate change impact on river runoff

Effect of modelling scale on the assessment of climate change impact on river runoff

Impacts of land cover and climate data selection on understanding terrestrial carbon dynamics and the CO&lt;sub&gt;2&lt;/sub&gt; airborne fraction

A physiological production model for cocoa (Theobroma cacao): model presentation, validation and application

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Impacts of land cover and climate data selection on understanding terrestrial carbon dynamics and the CO<sub>2</sub> airborne fraction