Rainfall and dry spell occurrence in Ghana : trends and seasonal predictions with a dynamical and a statistical model

Improved information on the distribution of seasonal rainfall is important for crop production in Ghana. The predictability of key agro-meteorological indices, namely, seasonal rainfall, maximum dry spell length (MDSL) and dry spell frequency (DSF) was investigated across Ghana (with an interest on the coastal savannah agro-ecological zone). These three variables are relevant for local agricultural water management. A dynamical model (i.e. European Centre for Medium-Range Weather Forecasts (ECMWF) System 4 seasonal forecasts) and a statistical model (i.e. response to sea surface temperatures (SSTs)) were used and analysed using correlation and other discrimination skill metrics. ECMWF-System 4 was bias-corrected and verified with 14 local stations’ observations. Results show that differences in variability and skills of the agro-meteorological indices are small between agro-ecological zones as compared to the differences between stations. The dynamic model System 4 explains up to 31% of the variability of the MDSL and seasonal rainfall indices. Coastal savannah exhibits the highest level of discrimination skills. However, these skills are generally higher for the below and above normal MDSL and seasonal rainfall categories at lead time 0. Similarity in skills for the agro-meteorological indices over the same zones and stations is found both for the dynamical and statistical models. Although System 4 performs slightly better than the statistical model, especially, for dry spell length and seasonal rainfall. For dry spell frequency and longer lead time dry spell length, the statistical model tends to perform better. These results suggest that the agro-meteorological indices derived from System 4′ updated versions, corrected with local observations, together with the response to SST information, can potentially support decision-making of local smallholder farmers in Ghana.</p

Impacts of climate change on European hydrology at 1.5, 2 and 3 degrees mean global warming above preindustrial level

Impacts of climate change at 1.5, 2 and 3 °C mean global warming above preindustrial level are investigated and compared for runoff, discharge and snowpack in Europe. Ensembles of climate projections representing each of the warming levels were assembled to describe the hydro-meteorological climate at 1.5, 2 and 3 °C. These ensembles were then used to force an ensemble of five hydrological models and changes to hydrological indicators were calculated. It is seen that there are clear changes in local impacts on evapotranspiration, mean, low and high runoff and snow water equivalent between a 1.5, 2 and 3 °C degree warmer world. In a warmer world, the hydrological impacts of climate change are more intense and spatially more extensive. Robust increases in runoff affect the Scandinavian mountains at 1.5 °C, but at 3 °C extend over most of Norway, Sweden and northern Poland. At 3 °C, Norway is affected by robust changes in all indicators. Decreases in mean annual runoff are seen only in Portugal at 1.5 °C warming, but at 3 °C warming, decreases to runoff are seen around the entire Iberian coast, the Balkan Coast and parts of the French coast. In affected parts of Europe, there is a distinct increase in the changes to mean, low and high runoff at 2 °C compared to 1.5 °C, strengthening the case for mitigation to lower levels of global warming. Between 2 and 3 °C, the changes in low and high runoff levels continue to increase, but the changes to mean runoff are less clear. Changes to discharge in Europe’s larger rivers are less distinct due to the lack of homogenous and robust changes across larger river catchments, with the exception of Scandinavia where discharges increase with warming level

Impact of model physics on estimating the surface mass balance of the Greenland ice sheet

Long-term predictions of sea level rise from increased Greenland ice sheet melting have been derived using Positive Degree Day models only. It is, however, unknown precisely what uncertainties are associated with applying this simple surface melt parameterization for future climate. We compare the behavior of a Positive Degree Day and Energy Balance/ Snowpack model for estimating the surface mass balance of the Greenland ice sheet under a warming climate. Both models were first tuned to give similar values for present-day mass balance using 10 years of ERA-40 climatology and were then run for 300 years, forced with the output of a GCM in which atmospheric CO2 increased to 4 times preindustrial levels. Results indicate that the Positive Degree Day model is more sensitive to climate warming than the Energy Balance model, generating annual runoff rates almost twice as large for a fixed ice sheet geometry. Roughly half of this difference was due to differences in the volume of melt generated and half was due to differences in refreezing rates in the snowpack. Our results indicate that the modeled snowpack properties evolve on a multidecadal timescale to changing climate, with a potentially large impact on the mass balance of the ice sheet; an evolution that was absent from the Positive Degree Day model. Copyright 2007 by the American Geophysical Union

Evaluation of a high-resolution regional climate simulation over Greenland

A simulation of the 1991 summer has been performed over south Greenland with a coupled atmosphere–snow regional climate model (RCM) forced by the ECMWF re-analysis. The simulation is evaluated with in-situ coastal and ice-sheet atmospheric and glaciological observations. Modelled air temperature, specific humidity, wind speed and radiative fluxes are in good agreement with the available observations, although uncertainties in the radiative transfer scheme need further investigation to improve the model’s performance. In the sub-surface snow-ice model, surface albedo is calculated from the simulated snow grain shape and size, snow depth, meltwater accumulation, cloudiness and ice albedo. The use of snow metamorphism processes allows a realistic modelling of the temporal variations in the surface albedo during both melting periods and accumulation events. Concerning the surface albedo, the main finding is that an accurate albedo simulation during the melting season strongly depends on a proper initialization of the surface conditions which mainly result from winter accumulation processes. Furthermore, in a sensitivity experiment with a constant 0.8 albedo over the whole ice sheet, the average amount of melt decreased by more than 60%, which highlights the importance of a correctly simulated surface albedo. The use of this coupled atmosphere–snow RCM offers new perspectives in the study of the Greenland surface mass balance due to the represented feedback between the surface climate and the surface albedo, which is the most sensitive parameter in energy-balance-based ablation calculations.Peer reviewe

Skill and sources of skill in seasonal streamflow hindcasts for South America made with ECMWF's SEAS5 and VIC

The first aim of the present paper is the determination of the magnitude, annual variation and spatial distribution of skill in seasonal hindcasts of runoff and discharge in the entire continent of South America. We evaluated 35 years of hindcasts generated with the Variable Infiltration Capacity (VIC) hydrological model forced with SEAS5 hindcasts. Initial conditions of terrestrial water and so-called pseudo-observations were computed with a reference (i.e. historic) simulation. Skill was determined with monthly temporal resolution for the entire annual cycle and mostly using the pseudo-observations for verification. The second aim of the paper is the explanation of skill in terms of its sources, namely meteorological forcing and the initial conditions. Therefore, two sets of restricted hindcasts, which isolate the sources of skill, were analysed. The SEAS5 precipitation hindcasts exhibit significant skill even at the longest lead times (7 months). Beyond the first lead month we found significant skill in 13–43 % of the grid cells, depending on target and lead month. Levels of skill are higher in the full hindcasts (significant skill in 31–89 % of the grid cells). At the continental scale more of the skill is caused by the forcing than by the initial conditions. The runoff hindcasts are skilful in large parts of the continent. In a 1000 km wide band along the north coast of the continent and in southeast South America, most of the skill is due to the forcing. A typical feature of these regions is an increase of skill with lead time during specific parts of the year, which is against the common tendency. In Argentina and north Chile most of the skill in the runoff hindcasts can be attributed to the initial conditions of soil moisture. Verification with real observations of discharge broadly confirmed the skill pattern obtained with pseudo-observations