ALBERT

Description: In a warming climate, the water budget of the land is subject to varying forces such as increasing evaporative demand, mainly through the increased temperature, and changes to the precipitation, which might go up or down. Using a verified, physically based model with 55 years of observation-based meteorological forcing, an analysis of the water budget demonstrates that Great Britain is getting warmer and wetter. Increases in precipitation (2.96.0 ± 2.03 mm yr–1 yr–1) and air temperature (0.20 ± 0.13 K decade–1) are driving increases in runoff (2.18 ± 1.84 mm yr–1 yr–1) and evapotranspiration (0.87 ± 0.55 mm yr–1 yr–1), with no significant trend in the soil moisture. The change in evapotranspiration is roughly constant across the regions, whereas runoff varies greatly between regions: the biggest change is seen in Scotland (4.56 ± 2.82 mm yr–1 yr–1), where precipitation increases were also the greatest (5.4 ± 3.0 mm yr–1 yr–1), and the smallest trend (0.33 ± 1.50 mm yr–1 yr–1, not statistically significant) is seen in the English Lowlands (East Anglia and Midlands), where the increase in rainfall is not statistically significant (1.07 ± 1.76 mm yr–1 yr–1). Relative to its contribution to the evapotranspiration budget, the increase in interception is higher than the other components. This is due to the fact that it correlates strongly with precipitation, which is seeing a greater increase than the potential evapotranspiration. This leads to a higher increase in actual evapotranspiration than the potential evapotranspiration, and a negligible increase in soil moisture or groundwater store.

Description: Knowledge of how uncertainty propagates through a hydrological land surface modelling sequence is of crucial importance in the identification and characterisation of system weaknesses in the prediction of droughts and floods at global scale. We evaluated the performance of five state-of-the-art global hydrological and land surface models in the context of modelling extreme conditions (drought and flood). Uncertainty was apportioned between the model used (model skill) and also the satellite-based precipitation products used to drive the simulations (forcing data variability) for extreme values of precipitation, surface runoff and evaporation. We found in general that model simulations acted to augment uncertainty rather than reduce it. In percentage terms, the increase in uncertainty was most often less than the magnitude of the input data uncertainty, but of comparable magnitude in many environments. Uncertainty in predictions of evapotranspiration lows (drought) in dry environments was especially high, indicating that these circumstances are a weak point in current modelling system approaches. We also found that high data and model uncertainty points for both ET lows and runoff lows were disproportionately concentrated in the equatorial and southern tropics. Our results are important for highlighting the relative robustness of satellite products in the context of land surface simulations of extreme events and identifying areas where improvements may be made in the consistency of simulation models.

Description: Knowledge of how uncertainty propagates through a hydrological land surface modelling sequence is of crucial importance in the identification and characterisation of system weaknesses in the prediction of droughts and floods at global scale. We evaluated the performance of five state-of-the-art global hydrological and land surface models in the context of modelling extreme conditions (drought and flood). Uncertainty was apportioned between model used (model skill) and also the satellite-based precipitation products used to drive the simulations (forcing data variability) for extreme values of precipitation, surface runoff and evaporation. We found in general that model simulations acted to augment uncertainty rather than reduce it. In percentage terms, the increase in uncertainty was most often less than the magnitude of the input data uncertainty, but of comparable magnitude in many environments. Uncertainty in predictions of evapotranspiration lows (drought) in dry environments was especially high, indicating that these circumstances are a weak point in current modelling system approaches. We also found that high data and model uncertainty points for both ET lows and runoff lows were disproportionately concentrated in the equatorial and southern tropics. Our results are important for highlighting the relative robustness of satellite products in the context of land surface simulations and identifying areas where improvements may be made in the consistency of simulation models.

Description: Land surface models (LSMs) represent terrestrial hydrology in weather and climate modelling operational systems and research studies. We aim to improve hydrological performance in the Joint UK Land Environment Simulator (JULES) LSM that is suitable for distributed hydrological modelling within the new land-atmosphere-ocean coupled prediction system UKC2 (UK regional Coupled environmental prediction system 2). Using river flow observations from gauge stations, we study the capability of JULES to simulate river flow over 13 catchments in Great Britain, each representing different climatic and topographic characteristics at 1km2 spatial resolution. A series of tests, carried out to identify where the model results are sensitive to the scheme and parameters chosen for runoff production, suggests that different catchments require different parameters and even different runoff schemes to produce the best results. From these results, we introduce a new topographical parametrization that produces the best daily river flow results (in terms of Nash-Sutcliffe efficiency and mean bias) for all 13 catchments. The new parametrization introduces a dependency on terrain slope, constraining surface runoff production to wet soil conditions over flatter regions (like the Thames catchment; Nash-Sutcliffe efficiency above 0.8), whereas over steeper regions the model produces surface runoff for every rainfall event regardless of the soil wetness state. This new parametrization improves the model capability in regional (Great Britain wide) assessments. The new choice of parameters is reinforced by examining the amplitude and phase of the modelled versus observed river flows, via cross-spectral analysis for time scales longer than daily.

Description: In a warming climate, the water budget of the land is subject to varying forces such as increasing evaporative demand, mainly through the increased temperature, and changes to the precipitation, which might go up or down. Using a verified, physically based model with 55 years of observation-based meteorological forcing, an analysis of the water budget demonstrates that Great Britain is getting warmer and wetter. Increases in precipitation (3.0±2.0mmyr−1yr−1) and air temperature (0.20±0.13Kdecade−1) are driving increases in river flow (2.16mmyr−1yr−1) and evapotranspiration (0.87mmyr−1yr−1), with no significant trend in the soil moisture. The change in evapotranspiration is roughly constant across the regions whereas runoff varies greatly between regions: the biggest change is seen in Scotland (4.56mmyr−1yr−1), where precipitation increases were also the greatest (5.4±3.0mmyr−1yr−1) and smallest trend (0.29mmyr−1yr−1) is seen in the English Lowlands (East Anglia and Midlands), where the increase in rainfall is not statistically significant (1.1±0.7mmyr−1yr−1). Relative to their contribution to the evapotranspiration budget, the increase in interception is higher than the other components. This is due to the fact that it correlates strongly with precipitation which is seeing a greater increase than the potential evapotranspiration. This leads to a higher increase in actual evapotranspiration that the potential evapotranspiration, and a negligible increase in soil moisture or groundwater store.

Description: Land surface models (LSMs) represent terrestrial hydrology in weather and climate modelling operational systems and research studies. We aim to improve hydrological performance in the Joint UK Land Environment Simulator (JULES) LSM that is used for distributed hydrological modelling within the new land–atmosphere–ocean coupled prediction system UKC2 (UK regional Coupled environmental prediction system 2). Using river flow observations from gauge stations, we study the capability of JULES to simulate river flow at 1 km2 spatial resolution within 13 catchments in Great Britain that exhibit a variety of climatic and topographic characteristics. Tests designed to identify where the model results are sensitive to the scheme and parameters chosen for runoff production indicate that different catchments require different parameters and even different runoff schemes for optimal results. We introduce a new parameterisation of topographic variation that produces the best daily river flow results (in terms of Nash–Sutcliffe efficiency and mean bias) for all 13 catchments. The new parameterisation introduces a dependency on terrain slope, constraining surface runoff production to wet soil conditions over flatter regions, whereas over steeper regions the model produces surface runoff for every rainfall event regardless of the soil wetness state. This new parameterisation improves the model performance across Great Britain. As an example, in the Thames catchment, which has extensive areas of flat terrain, the Nash–Sutcliffe efficiency exceeds 0.8 using the new parameterisation. We use cross-spectral analysis to evaluate the amplitude and phase of the modelled versus observed river flows over timescales of 2 days to 10 years. This demonstrates that the model performance is modified by changing the parameterisation by different amounts over annual, weekly-to-monthly and multi-day timescales in different catchments, providing insights into model deficiencies on particular timescales, but it reinforces the newly developed parameterisation.

Description: Observations of climate are often available on very different spatial scales from observations of the natural environments and resources that are affected by climate change. In order to help bridge the gap between these scales using modelling, a new dataset of daily meteorological variables was created at 1 km resolution over Great Britain for the years 1961–2012, by interpolating coarser resolution climate data and including the effects of local topography. These variables were used to calculate atmospheric evaporative demand (AED) at the same spatial and temporal resolution. Two functions that represent AED were chosen: one is a standard form of potential evapotranspiration (PET) and the other is a derived PET measure used by hydrologists that includes the effect of water intercepted by the canopy (PETI). Temporal trends in these functions were calculated, with PET found to be increasing in all regions, and at an overall rate of 0.021 ± 0.021 mm day−1 decade−1 in Great Britain. PETI was found to be increasing at a rate of 0.019 ± 0.020 mm day−1 decade−1 in Great Britain, but this was not statistically significant. However, there was a trend in PETI in England of 0.023 ± 0.023 mm day−1 decade−1. The trends were found to vary by season, with spring PET increasing by 0.043 ± 0.019 mm day−1 decade−1 (0.038 ± 0.018 mm day−1 decade−1 when the interception correction is included) in Great Britain, while there is no statistically significant trend in other seasons. The trends were attributed analytically to trends in the climate variables; the overall positive trend was predominantly driven by rising air temperature, although rising specific humidity had a negative effect on the trend. Recasting the analysis in terms of relative humidity revealed that the overall effect is that falling relative humidity causes the PET to rise. Increasing downward short- and longwave radiation made an overall positive contribution to the PET trend, while decreasing wind speed made a negative contribution to the trend in PET. The trend in spring PET was particularly strong due to a strong decrease in relative humidity and increase in downward shortwave radiation in the spring.

Description: Land surface models (LSMs) represent terrestrial hydrology in weather and climate modelling operational systems and research studies. Using river flow observations from gauge stations, we study the capability of the Joint UK Land Environment Simulator (JULES) LSM to simulate river flow over 13 catchments in Great Britain, each representing different climatic and topographic characteristics at the 1 km2 spatial resolution. A series of tests, carried out to identify where the model results are sensitive to the scheme and parameters chosen for runoff production, suggests that different catchments require different parameters and even different runoff schemes to produce the best results. From these results, we introduce a new topographical parametrization that produces the best daily river flow results (in terms of Nash-Sutcliffe efficiency and mean bias) for all 13 catchments. The new parametrization introduces a dependency on terrain slope, constraining surface runoff production to wet soil conditions over flatter regions (like the Thames catchment; Nash-Sutcliffe efficiency above 0.8), whereas over steeper regions the model produces surface runoff for every rainfall event regardless of the soil wetness state. This new parametrization improves the model capability in regional (Great Britain wide) assessments. The new choice of parameters is reinforced by examining the amplitude and phase of the modelled versus observed river flows, via cross-spectral analysis for time scales longer than daily.