HydroPy (v1.0): a new global hydrology model written in Python

Global hydrological models (GHMs) are a useful tool in the assessment of the land surface water balance. They are used to further the understanding of interactions between water balance components and their past evolution as well as potential future development under various scenarios. While GHMs have been part of the hydrologist's toolbox for several decades, the models are continuously being developed. In our study, we present the HydroPy model, a revised version of an established GHM, the Max Planck Institute for Meteorology's Hydrology Model (MPI-HM). Being rewritten in Python, the new model requires much less effort in maintenance, and due to its flexible infrastructure, new processes can be easily implemented. Besides providing a thorough documentation of the processes currently implemented in HydroPy, we demonstrate the skill of the model in simulating the land surface water balance. We find that evapotranspiration is reproduced realistically for the majority of the land surface but is underestimated in the tropics. The simulated river discharge correlates well with observations. Biases are evident for the annual accumulated discharge; however, they can - at least to some extent - be attributed to discrepancies between the meteorological model forcing data and the observations. Finally, we show that HydroPy performs very similarly to MPI-HM and thus conclude the successful transition from MPI-HM to HydroPy

Life time of soil moisture perturbations in a coupled land-atmosphere simulation

This study evaluates the lifetime of soil moisture perturbations using an atmosphere-land GCM. We find memory of up to 9 months for root zone soil moisture. Interactions with other surface states result in significant but short-lived anomalies in surface temperature and more stable anomalies in leaf carbon content. As these anomalies can recur repeatedly, e.g. due to interactions with a deep-soil moisture reservoir, we conclude that soil moisture initialization may impact climate predictions

High resolution discharge simulations over Europe and the Baltic Sea catchment

Regional coupled system models require a high-resolution discharge component to couple their atmosphere/land components to the ocean component and to adequately resolve smaller catchments and the day-to-day variability of discharge. As the currently coupled discharge models usually do not fulfill this requirement, we improved a well-established discharge model, the Hydrological Discharge (HD) model, to be globally applicable at 5 Min. resolution. As the first coupled high-resolution discharge simulations are planned over Europe and the Baltic Sea catchment, we focus on the respective regions in the present study. As no river specific parameter adjustments were conducted and since the HD model parameters depend on globally available gridded characteristics, the model is, in principle, applicable for climate change studies and over ungauged catchments. For the validation of the 5 Min. HD (HD5) model, we force it with prescribed fields of surface and subsurface runoff. As no large-scale observations of these variables exist, they need to be calculated by a land surface scheme or hydrology model using observed or re-analyzed meteorological data. In order to pay regard to uncertainties introduced by these calculations, three different methods and datasets were used to derive the required fields of surface and subsurface runoff for the forcing of the HD5 model. However, the evaluation of the model performance itself is hampered by biases in these fields as they impose an upper limit on the accuracy of simulated discharge. 10-years simulations (2000–2009) show that for many European rivers, where daily discharge observations were available for comparison, the HD5 model captures the main discharge characteristics reasonably well. Deficiencies of the simulated discharge could often be traced back to deficits in the various forcing datasets. As direct anthropogenic impact on the discharge, such as by regulation or dams, is not regarded in the HD model, those effects can generally not be simulated. Thus, discharges for many heavily regulated rivers in Scandinavia or for the rivers Volga and Don are not well represented by the model. The comparison of the three sets of simulated discharges indicates that the HD5 model is suitable to evaluate the terrestrial hydrological cycle of climate models or land surface models, especially with regard to the separation of throughfall (rain or snow melt) into surface and subsurface runoff

Snowfall-albedo feedbacks could have led to deglaciation of Snowball Earth starting from mid-latitudes

Simple and complex climate models suggest a hard snowball – a completely ice-covered planet – is one of the steady-states of Earth’s climate. However, a seemingly insurmountable challenge to the hard-snowball hypothesis lies in the difficulty in explaining how the planet could have exited the glaciated state within a realistic range of atmospheric carbon dioxide concentrations. Here, we use simulations with the Earth system model MPI-ESM to demonstrate that terminal deglaciation could have been triggered by high dust deposition fluxes. In these simulations, deglaciation is not initiated in the tropics, where a strong hydrological cycle constantly regenerates fresh snow at the surface, which limits the dust accumulation and snow aging, resulting in a high surface albedo. Instead, comparatively low precipitation rates in the mid-latitudes in combination with high maximum temperatures facilitate lower albedos and snow dynamics that – for extreme dust fluxes – trigger deglaciation even at present-day carbon dioxide level

Drought at the global scale in the 2nd part of the 20th century (1963-2001)

The large impacts of drought on society, economy and environment urge for a thorough investigation. A good knowledge of past drought events is important for both understanding of the processes causing drought, as well as to provide reliability assessments for drought projections for the future. Preferably, the investigation of historic drought events should rely on observations. Unfortunately, for a global scale these detailed observations are often not available. Therefore, the outcome of global hydrological models (GHMs) and off-line land surface models (LSMs) is used to assess droughts. In this study we have investigated to what extent simulated gridded time series from these large-scale models capture historic hydrological drought events. Results of ten different models, both GHMs and LSMs, made available by the WATCH project, were compared. All models are run on a global 0.5 degree grid for the period 1963-2000 with the same meteorological forcing data (WATCH forcing data). To identify hydrological drought events, the monthly aggregated total runoff values were used. Different methods were developed to identify spatio-temporal drought characteristics. General drought characteristics for each grid cell, as for example the average drought duration, were compared. These characteristics show that when comparing absolute values the models give substantially different results, whereas relative values lead to more or less the same drought pattern. Next to the general drought characteristics, some documented major historical drought events (one for each continent) were selected and described in more detail. For each drought event, the simulated drought clusters (spatial events) and their characteristics are given for one month during the event. It can be concluded that most major drought events are captured by all models. However, the spatial extent of the drought events differ substantially between the models. In general the models show a fast reaction to rainfall and therefore also capture drought events caused by large rainfall anomalies. More research is still needed, since here we only looked at a few selected number of documented drought events spread over the globe. To assess more in detail if these large-scale models are able to capture drought, additional quantitative analyses are needed together with a more elaborated comparison against observed drought events

Improved seasonal prediction of European summer temperatures with new five-layer soil-hydrology scheme

We evaluate the impact of a new 5-layer soil-hydrology scheme on seasonal hindcast skill of 2-meter temperatures over Europe obtained with the Max Planck Institute Earth System Model (MPI-ESM). Assimilation experiments from 1981 to 2010 and 10-member seasonal hindcasts initialized on 1 May each year are performed with MPI-ESM in two soil configurations, one using a bucket scheme and one a new 5-layer soil-hydrology scheme. We find the seasonal hindcast skill for European summer temperatures to improve with the 5-layer scheme compared to the bucket scheme, and investigate possible causes for these improvements. First, improved indirect soil moisture assimilation allows for enhanced soil moisture-temperature feedbacks in the hindcasts. Additionally, this leads to improved prediction of anomalies in the 500 hPa geopotential height surface, reflecting more realistic atmospheric circulation patterns over Europe

Global multimodel analysis of drought in runoff for the second half of the twentieth century

During the past decades large-scale models have been developed to simulate global and continental terrestrial water cycles. It is an open question whether these models are suitable to capture hydrological drought, in terms of runoff, on global scale. A multi-model ensemble analysis was carried out to evaluate if ten of such large-scale models agree on major drought events during the second half of the 20th century. Time series of monthly precipitation, monthly total runoff from ten global hydrological models, and their ensemble median have been used to identify drought. Temporal development of area in drought for various regions across the globe was investigated. Model spread was largest in regions with low runoff and smallest in regions with high runoff. In vast regions, correlation between runoff drought derived from the models and meteorological drought was found to be low. This indicated that models add information to the signal derived from precipitation and that runoff drought cannot directly be determined from precipitation data alone in global drought analyses with a constant aggregation period. However, duration and spatial extent of major drought events differed between models. Some models showed a fast runoff response to rainfall, which led to deviations from reported drought events in slowly responding hydrological systems. By using an ensemble of models, this fast runoff response was partly overcome and delay in drought propagating from meteorological drought to drought in runoff was included. Finally, an ensemble of models also allows to consider uncertainty associated with individual model structures

Comparing projections of future changes in runoff and water resources from hydrological and ecosystem models in ISI-MIP

Projections of future changes in runoff can have important implications for water resources and flooding. In this study, runoff projections from ISI-MIP (Inter-sectoral Impact Model Intercomparison Project) simulations forced with HadGEM2-ES bias-corrected climate data under the Representative Concentration Pathway 8.5 have been analysed. Projections of change from the baseline period (1981–2010) to the future (2070–2099) from a number of different ecosystems and hydrological models were studied. The differences between projections from the two types of model were looked at globally and regionally. Typically, across different regions the ecosystem models tended to project larger increases and smaller decreases in runoff than the hydrological models. However, the differences varied both regionally and seasonally. Sensitivity experiments were also used to investigate the contributions of varying CO2 and allowing vegetation distribution to evolve on projected changes in runoff. In two out of four models which had data available from CO2 sensitivity experiments, allowing CO2 to vary was found to increase runoff more than keeping CO2 constant, while in two models runoff decreased. This suggests more uncertainty in runoff responses to elevated CO2 than previously considered. As CO2 effects on evapotranspiration via stomatal conductance and leaf-area index are more commonly included in ecosystems models than in hydrological models, this may partially explain some of the difference between model types. Keeping the vegetation distribution static in JULES runs had much less effect on runoff projections than varying CO2, but this may be more pronounced if looked at over a longer timescale as vegetation changes may take longer to reach a new state

Multimodel projections and uncertainties of irrigation water demand under climate change

Crop irrigation is responsible for 70% of humanity's water demand. Since the late 1990s, the expansion of irrigated areas has been tapering off, and this trend is expected to continue in the future. Future irrigation water demand (IWD) is, however, subject to large uncertainties due to anticipated climate change. Here, we use a set of seven global hydrological models (GHMs) to quantify the impact of projected global climate change on IWD on currently irrigated areas by the end of this century, and to assess the resulting uncertainties arising from both the GHMs and climate projections. The resulting ensemble projections generally show an increasing trend in future IWD, but the increase varies substantially depending on the degree of global warming and associated regional precipitation changes. Under the highest greenhouse gas emission scenario (RCP8.5), IWD will considerably increase during the summer in the Northern Hemisphere (>20% by 2100), and the present peak IWD is projected to shift one month or more over regions where ≥80% of the global irrigated areas exist and 4 billion people currently live. Uncertainties arising from GHMs and global climate models (GCMs) are large, with GHM uncertainty dominating throughout the century and with GCM uncertainty substantially increasing from the midcentury, indicating the choice of GHM outweighing by far the uncertainty arising from the choice of GCM and associated emission scenario. Key Points: IWD will considerably increase during the summer in the Northern Hemisphere Peak demand is projected to shift over 80% of the present irrigated areas Global hydrological models dominate the uncertainty in projected IWD. © 2013. American Geophysical Union. All Rights Reserved