Climate Model HadCM3 Research Articles

Reconstructing the Antarctic ice-sheet shape at the Last Glacial Maximum using ice-core data

Abstract The Antarctic ice sheet (AIS) is the Earth’s largest store of frozen water; understanding how it changed in the past allows us to improve projections of how it, and sea levels, may change. Here, we use previous AIS reconstructions, water isotope ratios from ice cores, and simulator predictions of the relationship between the ice-sheet shape and isotope ratios to create a model of the AIS at the Last Glacial Maximum. We develop a prior distribution that captures expert opinion about the AIS, generate a designed ensemble of potential shapes, run these through the climate model HadCM3, and train a Gaussian process emulator of the link between ice-sheet shape and isotope ratios. To make the analysis computationally tractable, we develop a preferential principal component method that allows us to reduce the dimension of the problem in a way that accounts for the differing importance we place in reconstructions, allowing us to create a basis that reflects prior uncertainty. We use Markov chain Monte Carlo to sample from the posterior distribution, finding shapes for which HadCM3 predicts isotope ratios closely matching observations from ice cores. The posterior distribution allows us to quantify the uncertainty in the reconstructed shape, a feature missing in other analyses.

Browning of Scottish surface water sources exposed to climate change

Levels of dissolved natural organic matter (DNOM) are increasing in our boreal watercourses. This is manifested by an apparent increase in its yellow to brown colour of the water, i.e., browning. Sound predictions of future changes in colour of our freshwaters is a prerequisite for predicting effects on aquatic fauna and a sustainable operation of drinking water facilities using surface waters as raw water sources. A model for the effect of climate on colour (mg Pt L-1) has been developed for two surface raw water sources in Scotland, i.e., at Bracadale and Port Charlotte. Both sites are situated far out on the Scottish west coast, without major impact of acid rain, with limited amounts of frost, and with limited recent land-use changes. The model was fitted to 15 years long data-series on colour measurements, provided by Scottish Water, at the two sites. Meteorological data were provided by UK Met. The models perform well for both sites in simulating the variation in monthly measured colour, explaining 89 and 90% of the variation at Bracadale and Port Charlotte, respectively. These well fitted models were used to predict future changes in colour due to changes in temperature and precipitation based on median climate data from a high emission climate RCP8.5 scenario from the HadCM3 climate model (UKCP18). The model predicted an increase in monthly average colour during growing season at both sites from about 150 mg Pt L-1 to about 200 mg Pt L-1 in 2050–2079. Temperature is found to be the most important positively driver for colour development at both sites.

Identifying the Sources of Continental Summertime Temperature Variance Using a Diagnostic Model of Land–Atmosphere Interactions

AbstractClimate models show that soil moisture and its subseasonal fluctuations have important impacts on the surface latent heat flux, thus regulating surface temperature variations. Using correlations between monthly anomalies in net absorbed radiative fluxes, precipitation, 2-m air temperature, and soil moisture in the ERA-Interim reanalysis and the HadCM3 climate model, we develop a linear diagnostic model to quantify the major effects of land–atmosphere interactions on summertime surface temperature variability. The spatial patterns in 2-m air temperature and soil moisture variance from the diagnostic model are consistent with those from the products from which it was derived, although the diagnostic model generally underpredicts soil moisture variance. We use the diagnostic model to quantify the impact of soil moisture, shortwave radiation, and precipitation anomalies on temperature variance in wet and dry regions. Consistent with other studies, we find that fluctuations in soil moisture amplify temperature variance in dry regions through their impact on latent heat flux, whereas in wet regions temperature variability is muted because of high mean evapotranspiration rates afforded by plentiful surface soil moisture. We demonstrate how the diagnostic model can be used to identify sources of temperature variance bias in climate models.

Impacts of long term climate change during the collapse of the Akkadian Empire

Four thousand years ago what is often considered to be the world's first empire, the Akkadian Empire, collapsed. Proxy data has suggested a regional aridification event coincided with this collapse, but there is a lack of records collected from within the Mesopotamian region, where the Akkadian Empire was based. Here we analyse a suite of simulations from the HadCM3 climate model covering the last 6000 years. The results show that long-term drivers produced a shift to a more arid climate, showing minima in both precipitation and river flow at 2000 BCE, whilst temperatures were colder at 2250 BCE. These changes were sufficient to have a negative impact on the natural vegetation in Mesopotamia, suggesting that this climate change would have also impacted the agriculture sustaining local communities. We suggest that the combined effects of climate change and land mismanagement would lead to shortages of water and food, which may have contributed to social disruption and the collapse of the Akkadian Empire. We also find examples of resilience through the surviving cities such as Tell Brak and Tell Mozan. These could provide lessons for adapting to climate change in the future, as modern-day climate change threatens food and water security.

Holocene temperature trends in the extratropical Northern Hemisphere based on inter‐model comparisons

ABSTRACTLarge uncertainties exist in Holocene climate estimates, especially for the early Holocene when large‐scale reorganization occurred in the climate system. To improve our understanding of these uncertainties, we compare four Holocene simulations performed with the LOVECLIM, CCSM3, HadCM3 and FAMOUS climate models. The simulations are generally consistent for the large‐scale Northern Hemisphere extratropics, while the multi‐simulation consistencies are heterogeneous on the sub‐continental scale. Consistently simulated temperature trends are found in Greenland, northern Canada, north‐eastern and north‐western Europe, and central‐west Siberia. These Holocene temperatures show a pattern of an early Holocene warming, mid‐Holocene warmth and gradual decrease towards the pre‐industrial in winter, and the extent of early Holocene warming varies spatially, with 9 °C warming in northern Canada compared with 3 °C warming in central‐west Siberia. In contrast, mismatched temperatures are detected: in Alaska, the warm early Holocene winter in LOVECLIM primarily results from strongly enhanced southerly winds induced by the ice sheets; in eastern Siberia, the intense early‐Holocene summer warmth anomaly in CCSM3 is caused by large negative albedo anomalies due to overestimated snow cover at 0 ka; in the Arctic, cool winter conditons in FAMOUS can be attributed to extensive sea ice coverage probably due to simplified sea ice representations. Thus, the Holocene temperature trends in these regions remain inconclusive.

The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0

Abstract. Understanding natural and anthropogenic climate change processes involves using computational models that represent the main components of the Earth system: the atmosphere, ocean, sea ice, and land surface. These models have become increasingly computationally expensive as resolution is increased and more complex process representations are included. However, to gain robust insight into how climate may respond to a given forcing, and to meaningfully quantify the associated uncertainty, it is often required to use either or both ensemble approaches and very long integrations. For this reason, more computationally efficient models can be very valuable tools. Here we provide a comprehensive overview of the suite of climate models based around the HadCM3 coupled general circulation model. This model was developed at the UK Met Office and has been heavily used during the last 15 years for a range of future (and past) climate change studies, but has now been largely superseded for many scientific studies by more recently developed models. However, it continues to be extensively used by various institutions, including the BRIDGE (Bristol Research Initiative for the Dynamic Global Environment) research group at the University of Bristol, who have made modest adaptations to the base HadCM3 model over time. These adaptations mean that the original documentation is not entirely representative, and several other relatively undocumented configurations are in use. We therefore describe the key features of a number of configurations of the HadCM3 climate model family, which together make up HadCM3@Bristol version 1.0. In order to differentiate variants that have undergone development at BRIDGE, we have introduced the letter B into the model nomenclature. We include descriptions of the atmosphere-only model (HadAM3B), the coupled model with a low-resolution ocean (HadCM3BL), the high-resolution atmosphere-only model (HadAM3BH), and the regional model (HadRM3B). These also include three versions of the land surface scheme. By comparing with observational datasets, we show that these models produce a good representation of many aspects of the climate system, including the land and sea surface temperatures, precipitation, ocean circulation, and vegetation. This evaluation, combined with the relatively fast computational speed (up to 1000 times faster than some CMIP6 models), motivates continued development and scientific use of the HadCM3B family of coupled climate models, predominantly for quantifying uncertainty and for long multi-millennial-scale simulations.

METEOROLOGICAL DROUGHT ASSESSMENT IN WONOGIRI DISTRICT

Drought is one of natural disaster occurrences that affect many life aspects such as agricultural and economy. Drought is one ofhazard that affected by extreme condition due to climate change. Wonogiri is one of districts in Indonesia that has a high risk ofmeteorological drought. This area tends to have less rainfall than other areas that make the condition drier. This study is aimedto provide some information required in determining the drought disaster mitigation through analysis of the droughtcharacteristics, for both historical and future condition. For the historical condition analysis, the input is 12 years of daily rainfallrecorded data from 1990 to 2001 in 15 rain gauges. In case of the future assessment, the meteorological drought was analyzedby using Effective Drought Index (EDI) and Standardized Precipitation Index (SPI) methods. Input data for the future assessmentis 90 years of daily rainfall which was generated by using climate model HadCM3 scenario A2 and B2. The future data predictionwas done by using Automated Statistical Downscaling software. Statistical criteria i.e. Root Mean Square Error (RMSE),regression coefficient and standard deviation were used for testing the model accuracy. The drought coefficient obtained fromthe analysis using EDI and SPI then was applied to draw drought risk map using GIS software in Wonogiri District for historicaland future condition. The results show that for the historical condition, the most severe drought occurred in 1997-1998. Thisextreme condition related to ENSO phenomenon that happened in this area. Compared with the historical condition, the numberof future drought event in 2080 period is less than the historical one. This result agree with the rainfall prediction. The generatedrainfall for both scenarios are increase from existing period to 2080’s.

Common dolphins in the Alboran Sea: Facing a reduction in their suitable habitat due to an increase in Sea surface temperature

The short-beaked common dolphin Mediterranean subpopulation appears to have suffered a steep decline over recent decades and was listed in 2003 as ‘Endangered’ in the IUCN Red List of Threatened Species. The Alboran Sea is the last region in the Mediterranean where it is still abundant. In this study, we relate features of this species’ ecology to climate change, focusing on distribution and density. This work used a two decades-long dataset on the common dolphin in the Alboran Sea and a time series of environmental changes. Once established, these relationships were used in conjunction with some simulated scenarios of environmental change to predict the potential effects of further change on these species over the next 100 years. Two approaches were used: 1) projection from a regression line from local variation, and 2) a HadCM3 climate model with time-varying anthropogenic effects. Generalized Additive Models were used to model the relationship between density of the animals with SST and other environmental covariates. Results from both approaches were very similar. The predictions of density from the regression line fell within the ranges from the HadCM3 climate model, the first being based on local and locally, point to point, differentiated information, which lead us to consider the first approach as the best for this area. At the small spatial scale of the Alboran Sea and Gulf of Vera, an increase in SST will potentially yield a reduction in suitable habitat for common dolphins, with a progressive reduction in density from east to west.

Development of Adaptive Strategies for Irrigation Water Demand Management under Climate Change

AbstractThe HadCM3 climate model is applied with greenhouse gas emission scenario A2 to predict climatic variables in the Aidoghmoush Basin (East Azerbaijan, Iran) over the period 2026–2039. The impacts of the predicted climate variables on reservoir inflow and irrigation water use are calculated with the IHACRES model and the Food and Agricultural Organization’s (FAO) evapotranspiration method, respectively. The presented results show that reservoir inflow and irrigation water use in the prediction period relative to the baseline period (1987–2000) would be decreased by 0.7% and increased by 6%, respectively. Therefore, the Aidoghmoush Basin is likely to face increasing water shortage under a changing climate. As a result, irrigation water use should be reduced by applying the following three adaptive strategies to climate change: delaying the planting date, applying irrigation deficit stress, and increasing the irrigation efficiency. Simulations are performed to evaluate the yield of the agricultural cr...

Assessment of Impacts of Climate Change and Adaptation Measures for Maize Production in East Sikkim, India

An investigation was carried out to assess the impacts of climate change on rainfed maize yield using a yield response to water stress model (AquaCrop) and to identify suitable adaptation options to minimize the negative impacts on maize yield in East Sikkim, North East India. Crop management and yield data was collected from the field experimental plots for calibration and validation of the model for the study area. The future climate data was developed for two IPCC emission scenarios A2 and B2 based on the global climate model HadCM3 with downscaling of climate to finer spatial resolution using the statistical downscaling model, SDSM. The impact study revealed that there is an expected reduction in maize yield of 12.8, 28.3 and 33.9% for the A2 scenario and 7.5, 19.9 and 29.9% for the B2 scenario during 2012-40, 2041-70 and 2071-99 respectively compared to the average yield simulated during the period of 1961-1990 with observed climate data. The maize yield of same variety under future climate can be maintained or improved from current level by changing planting dates, providing supplement irrigation and managing optimum nutrient.Journal of Hydrology and Meteorology, Vol. 9(1) 2015, p.15-27

Towards Dependence of Tropical Cyclone Intensity on Sea Surface Temperature and Its Response in a Warming World

Tropical Cyclone (TC) systems affect global ocean heat transport due to mixing of the upper ocean and impact climate dynamics. A higher Sea Surface Temperature (SST), other influencing factors remaining supportive, fuels TC genesis and intensification. The atmospheric thermodynamic profile, especially the sea-air temperature contrast (SAT), also contributes due to heat transfer and affects TC’s maximum surface wind speed (Vmax) explained by enthalpy exchange processes. Studies have shown that SST can approximately be used as a proxy for SAT. As a part of an ongoing effort in this work, we simplistically explored the connection between SST and Vmax from a climatological perspective. Subsequently, estimated Vmax is applied to compute Power Dissipation Index (an upper limit on TC’s destructive potential). The model is developed using long-term observational SST reconstructions employed on three independent SST datasets and validated against an established model. This simple approach excluded physical parameters, such as mixing ratio and atmospheric profile, however, renders it generally suitable to compute potential intensity associated with TCs spatially and weakly temporally and performs well for stronger storms. A futuristic prediction by the HadCM3 climate model under doubled CO2 indicates stronger storm surface wind speeds and rising SST, especially in the Northern Hemisphere.

Terrestrial biosphere changes over the last 120 kyr

Abstract. A new global synthesis and biomization of long (> 40 kyr) pollen-data records is presented and used with simulations from the HadCM3 and FAMOUS climate models and the BIOME4 vegetation model to analyse the dynamics of the global terrestrial biosphere and carbon storage over the last glacial–interglacial cycle. Simulated biome distributions using BIOME4 driven by HadCM3 and FAMOUS at the global scale over time generally agree well with those inferred from pollen data. Global average areas of grassland and dry shrubland, desert, and tundra biomes show large-scale increases during the Last Glacial Maximum, between ca. 64 and 74 ka BP and cool substages of Marine Isotope Stage 5, at the expense of the tropical forest, warm-temperate forest, and temperate forest biomes. These changes are reflected in BIOME4 simulations of global net primary productivity, showing good agreement between the two models. Such changes are likely to affect terrestrial carbon storage, which in turn influences the stable carbon isotopic composition of seawater as terrestrial carbon is depleted in 13C.

Influence of Projected Climate on Rice Yield Over Tamilnadu

A study was carried out at Agro Climate Research Centre, Tamil Nadu Agricultural University using PRECIS and RegCM4 Regional Climate Models (RCMs) by downscaling HadCM3 (Q0) and ECHAM5 global climate model outputs at 25 km resolution. The downscaled data obtained from the RCMs were verified with CRU observed climatology and found to have good agreement. Four weather variables viz., maximum temperature, minimum temperature, solar radiation and rainfall were extracted and employed in DSSAT crop simulation model for rice yield simulation for agricultural grids of Tamilnadu State India from 1971-2100. Two treatments were fixed as control and CO2 enriched conditions. The maximum temperature and minimum temperature showed increase in temperature at the end of the century with high rate of increase for minimum temperature. Rainfall exhibited high variability. The rice yield simulations showed decline in yield in the study period for both control and CO2 enriched conditions, with later consistently showing higher yields than the former till the end of 21st century.

Assessment of climate change impacts on soil water balance and aquifer recharge in a semiarid region in south east Spain

Summary Climate change forecasts in a semiarid region are of much interest to academics, managers and governments. A significant decrease in annual precipitation and an increase in mean annual air temperature are expected; consequently, changes in the soil water balance and groundwater recharge to aquifers are expected as a response to climate change forecasts. In this context, our study aimed to assess the impact of climate changes on the soil water balance and natural groundwater recharge in a semiarid area (Ventos-Castellar aquifer, SE, Spain). To this end, we selected Global Climate Model HadCM3 after comparing it with two other models (ECHAM4 and CGCM2). The HadCM3 model climate data (air temperature and precipitation in two emission scenarios: A2-high and B2-low; 2011–2099) were coupled to a HYDROBAL hydrological model to determine the soil water balance. The HYDROBAL model results showed that climate change will have a significant impact on the soil water balance in the study area, especially on groundwater recharge during the latter period. In both the A2-high and B2-low scenarios, the selected years to run the HYDROBAL model showed a decrease in water balance components (precipitation, actual evapotranspiration, aquifer recharge and runoff) in relation to the baseline period (1961–1990). Over the projected period (2011–2099), we expect fewer rainfall events (>15 mm), which promote aquifer recharge, longer dry summer seasons and, consequently, reduced average annual recharge that ranged from 3% to 17%; 10–49 mm, if compared to the baseline period. The methodology developed in the present study can be beneficial for assessing the impact of predicted climate change on groundwater recharge, and can help managers and planners to devise strategies for the efficient use and conservation of freshwater resources.

Global sensitivity analysis of the Indian monsoon during the Pleistocene

Abstract. The sensitivity of the Indian monsoon to the full spectrum of climatic conditions experienced during the Pleistocene is estimated using the climate model HadCM3. The methodology follows a global sensitivity analysis based on the emulator approach of Oakley and O'Hagan (2004) implemented following a three-step strategy: (1) development of an experiment plan, designed to efficiently sample a five-dimensional input space spanning Pleistocene astronomical configurations (three parameters), CO2 concentration and a Northern Hemisphere glaciation index; (2) development, calibration and validation of an emulator of HadCM3 in order to estimate the response of the Indian monsoon over the full input space spanned by the experiment design; and (3) estimation and interpreting of sensitivity diagnostics, including sensitivity measures, in order to synthesise the relative importance of input factors on monsoon dynamics, estimate the phase of the monsoon intensity response with respect to that of insolation, and detect potential non-linear phenomena. By focusing on surface temperature, precipitation, mixed-layer depth and sea-surface temperature over the monsoon region during the summer season (June-July-August-September), we show that precession controls the response of four variables: continental temperature in phase with June to July insolation, high glaciation favouring a late-phase response, sea-surface temperature in phase with May insolation, continental precipitation in phase with July insolation, and mixed-layer depth in antiphase with the latter. CO2 variations control temperature variance with an amplitude similar to that of precession. The effect of glaciation is dominated by the albedo forcing, and its effect on precipitation competes with that of precession. Obliquity is a secondary effect, negligible on most variables except sea-surface temperature. It is also shown that orography forcing reduces the glacial cooling, and even has a positive effect on precipitation. As regards the general methodology, it is shown that the emulator provides a powerful approach, not only to express model sensitivity but also to estimate internal variability and detect anomalous simulations.

Projected changes in tropical cyclones over Vietnam and the South China Sea using a 25 km regional climate model perturbed physics ensemble

The regional climate modelling system PRECIS, was run at 25 km horizontal resolution for 150 years (1949–2099) using global driving data from a five member perturbed physics ensemble (based on the coupled global climate model HadCM3). Output from these simulations was used to investigate projected changes in tropical cyclones (TCs) over Vietnam and the South China Sea due to global warming (under SRES scenario A1B). Thirty year climatological mean periods were used to look at projected changes in future (2069–2098) TCs compared to a 1961–1990 baseline. Present day results were compared qualitatively with IBTrACS observations and found to be reasonably realistic. Future projections show a 20–44 % decrease in TC frequency, although the spatial patterns of change differ between the ensemble members, and an increase of 27–53 % in the amount of TC associated precipitation. No statistically significant changes in TC intensity were found, however, the occurrence of more intense TCs (defined as those with a maximum 10 m wind speed >35 m/s) was found to increase by 3–9 %. Projected increases in TC associated precipitation are likely caused by increased evaporation and availability of atmospheric water vapour, due to increased sea surface and atmospheric temperature. The mechanisms behind the projected changes in TC frequency are difficult to link explicitly; changes are most likely due to the combination of increased static stability, increased vertical wind shear and decreased upward motion, which suggest a decrease in the tropical overturning circulation.

Adaptive Reservoir Operation Rules Under Climatic Change

Increases in greenhouse gases caused by human activities have raised global temperature. Global warming affects water resources systems and the hydrologic cycle and may impact the performance of water resource systems. Water resources managers face challenges balancing conflicting goals in reservoir operation given the uncertainties introduced by climatic change. The HadCM3 climate model is used in this paper to estimate temperature and precipitation for early (2025–2039), middle (2055–2069) and late (2085–2099) periods of the 21st century under the A2 greenhouse gases emission scenario. The estimated temperature and precipitation from the climate model are input to a calibrated hydrologic model (IHACRES) to simulate inflow in a river basin draining to the Karoon-4 reservoir in Iran. A meta-heuristic multi-objective optimization algorithm (NSGA-II) is used in conjunction to predicted hydrologic variables to optimize dynamic operation rules in the Karoon-4 reservoir. The Karoon4 reservoir is operated non-adaptively and adaptively under climatic change. Our results show that adaptive reservoir management increases the reliability and reduces the vulnerability associated with hydropower generation in early, middle, and late simulation periods of the 21st century. These findings establish the importance of factoring in climatic change and considering adaptive strategies in future reservoir operations.

Climate change impact on legumes' water production function in the northeast of Iran

Enhanced understanding of the climate impact on crops' production is necessary to cope with expected climate variability and change. This study was conducted to find any robust association between crop yield and evapotranspiration using historical data (1986–2005) and subsequently employ the acquired relationship to project crop yield under future climate conditions for two agricultural centers in northeast Iran. Three legume crops of chickpea, lentil, and bean were selected in this study. The future precipitation and temperature data were projected by downscaling outputs of global climate model HadCM3 (A2 scenario) by LARS-WG stochastic weather generator. The data were downscaled for the baseline (1961–1990) and two time periods (2011–2030 and 2080–2099) as near and far future conditions. Projected temperature under A2 scenario showed increasing trend changed from 4 to 26% during the legumes' growth period compared to baseline. In addition, projected annual precipitation change was between −14 and 10% range under different time periods in contrast to baseline. There was a nonlinear relationship between crop yields and the seasonal values of crop evapotranspiration for all crops. The results showed that seasonal evapotranspiration would increase under climate change conditions across study locations. Crop yield would also increase for chickpea but not for lentil and bean for the far future in Sabzevar location compared to baseline. In conclusion, increasing the temperature and decreasing the precipitation may have a negative effect on legumes' yield in northeast Iran, especially for far future conditions. Therefore, planning effective adaptation and mitigation strategies would be necessary for northeast Iran.

Hydropower Reservoir Management Under Climate Change: The Karoon Reservoir System

This study assesses the performance of hydropower production by reservoirs with and without climate change impacts on river discharge. The case study of this research includes the Khersan 1, Karoon 4, and Karoon 3 reservoirs in Iran. The HADCM3 climate model with A2 greenhouse gas emission scenario is coupled with proportional downscaling to assess the impact of climate change on river discharge and reservoir hydropower production. The IHACRES rainfall- runoff model is implemented for calculating river discharge under climate-change conditions. Reservoir simulation and optimization models are implemented to calculate hydropower production in the base period (1986–2000), future period 1 (2025–2039), future period 2 (2055–2069), and future period 3 (2085–2099). The power production and performance criteria of the reservoirs are calculated using simulation (standard operating policy) and optimization models in the considered periods. Our results show that the largest reductions of reservoir discharge correspond, in decreasing order, to the future periods 3, 1, and 2, respectively. Moreover, the hydropower production obtained with the optimization model is found to be larger than that obtained with the simulation model. The calculated increase in power production in the base period and future periods 1, 2, and 3 is equal to 6, 19, 10, and 22 %, respectively. These results demonstrate the benefit of applying optimization modeling for hydropower production in the Khersan -Karoon reservoir system to mitigate and adapt to climate-change impacts on river discharge.

Sensitivity of a coupled climate model to canopy interception capacity

The canopy interception capacity is a small but key part of the surface hydrology, which affects the amount of water intercepted by vegetation and therefore the partitioning of evaporation and transpiration. However, little research with climate models has been done to understand the effects of a range of possible canopy interception capacity parameter values. This is in part due to the assumption that it does not significantly affect climate. Near global evapotranspiration products now make evaluation of canopy interception capacity parameterisations possible. We use a range of canopy water interception capacity values from the literature to investigate the effect on climate within the climate model HadCM3. We find that the global mean temperature is affected by up to −0.64 K globally and −1.9 K regionally. These temperature impacts are predominantly due to changes in the evaporative fraction and top of atmosphere albedo. In the tropics, the variations in evapotranspiration affect precipitation, significantly enhancing rainfall. Comparing the model output to measurements, we find that the default canopy interception capacity parameterisation overestimates canopy interception loss (i.e. canopy evaporation) and underestimates transpiration. Overall, decreasing canopy interception capacity improves the evapotranspiration partitioning in HadCM3, though the measurement literature more strongly supports an increase. The high sensitivity of climate to the parameterisation of canopy interception capacity is partially due to the high number of light rain-days in the climate model that means that interception is overestimated. This work highlights the hitherto underestimated importance of canopy interception capacity in climate model hydroclimatology and the need to acknowledge the role of precipitation representation limitations in determining parameterisations.