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

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

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

America’s Forgotten Holiday

Though now a largely forgotten holiday in the United States, May Day was founded here in 1886 by an energized labor movement as a part of its struggle for the eight-hour day. In ensuing years, May Day took on new meaning, and by the early 1900s had become an annual rallying point for anarchists, socialists, and communists around the world. Yet American workers and radicals also used May Day to advance alternative definitions of what it meant to be an American and what America should be as a nation. Mining contemporary newspapers, party and union records, oral histories, photographs, and rare film footage, America’s Forgotten Holiday explains how May Days celebrants, through their colorful parades and mass meetings, both contributed to the construction of their own radical American identities and publicized alternative social and political models for the nation. This fascinating story of May Day in America reveals how many contours of American nationalism developed in dialogue with political radicals and workers, and uncovers the cultural history of those who considered themselves both patriotic and dissenting Americans

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

Lifetime 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

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