Interactions between mass balance, atmospheric circulation, and recent climate change on the Djankuat Glacier, Caucasus Mountains, Russia

This paper reports recent changes in the mass balance record from the Djankuat Glacier, central greater Caucasus, Russia, and investigates possible relationships between the components of mass balance, local climate, and distant atmospheric forcing. The results clearly show that a strong warming signal has emerged in the central greater Caucasus, particularly since the 1993/1994 mass balance year, and this has led to a significant increase in the summer ablation of Djankuat. At the same time, there has been no compensating consistent increase in winter precipitation and accumulation leading to the strong net loss of mass and increase in glacier runoff. Interannual variability in ablation and accumulation is partly associated with certain major patterns of Northern Hemisphere climatic variability. The positive phase of the North Pacific (NP) teleconnection pattern forces negative geopotential height and temperature anomalies over the Caucasus in summer and results in reduced summer melt, such as in the early 1990s, when positive NP extremes resulted in a temporary decline in ablation rates. The positive phase of the NP is related to El Nino-Southern Oscillation, and it is possible that a teleconnection between the tropical Pacific sea surface temperatures and summer air temperatures in the Caucasus is bridged through the NP pattern. More recently, the NP pattern was predominantly negative, and this distant moderating forcing on summer ablation in the Caucasus was absent. Statistically significant correlations are observed between accumulation and the Scandinavian (SCA) teleconnection pattern. The frequent occurrence of the positive SCA phase at the beginning of accumulation season results in lower than average snowfall and reduced accumulation. The relationship between the North Atlantic Oscillation (NAO), Arctic Oscillation, and accumulation is weak, although positive precipitation anomalies in the winter months are associated with the negative phase of the NAO. A stronger positive correlation is observed between accumulation on Djankuat and geopotential height over the Bay of Biscay unrelated to the established modes of the Northern Hemisphere climatic variability. These results imply that the mass balance of Djankuat is sensitive to the natural variability in the climate system. Distant forcing, however, explains only 16% of the variance in the ablation record and cannot fully explain the recent increase in ablation and negative mass balance.

Stratospheric temperature trends: impact of ozone variability and the QBO

In most climate simulations used by the Intergovernmental Panel on Climate Change 2007 fourth assessment report, stratospheric processes are only poorly represented. For example, climatological or simple specifications of time-varying ozone concentrations are imposed and the quasi-biennial oscillation (QBO) of equatorial stratospheric zonal wind is absent. Here we investigate the impact of an improved stratospheric representation using two sets of perturbed simulations with the Hadley Centre coupled ocean atmosphere model HadGEM1 with natural and anthropogenic forcings for the 1979–2003 period. In the first set of simulations, the usual zonal mean ozone climatology with superimposed trends is replaced with a time series of observed zonal mean ozone distributions that includes interannual variability associated with the solar cycle, QBO and volcanic eruptions. In addition to this, the second set of perturbed simulations includes a scheme in which the stratospheric zonal wind in the tropics is relaxed to appropriate zonal mean values obtained from the ERA-40 re-analysis, thus forcing a QBO. Both of these changes are applied strictly to the stratosphere only. The improved ozone field results in an improved simulation of the stepwise temperature transitions observed in the lower stratosphere in the aftermath of the two major recent volcanic eruptions. The contribution of the solar cycle signal in the ozone field to this improved representation of the stepwise cooling is discussed. The improved ozone field and also the QBO result in an improved simulation of observed trends, both globally and at tropical latitudes. The Eulerian upwelling in the lower stratosphere in the equatorial region is enhanced by the improved ozone field and is affected by the QBO relaxation, yet neither induces a significant change in the upwelling trend.

The meteorology of the Western Indian Ocean, and the influence of the east African highlands

This paper reviews the meteorology of the Western Indian Ocean and uses a state–of–the–art atmospheric general circulation model to investigate the influence of the East African Highlands on the climate of the Indian Ocean and its surrounding regions. The new 44–year re–analysis produced by the European Centre for Medium range Weather Forecasts (ECMWF) has been used to construct a new climatology of the Western Indian Ocean. A brief overview of the seasonal cycle of the Western Indian Ocean is presented which emphasizes the importance of the geography of the Indian Ocean basin for controlling the meteorology of the Western Indian Ocean. The principal modes of inter–annual variability are described, associated with El Niño and the Indian Ocean Dipole or Zonal Mode, and the basic characteristics of the subseasonal weather over the Western Indian Ocean are presented, including new statistics on cyclone tracks derived from the ECMWF re–analyses. Sensitivity experiments, in which the orographic effects of East Africa are removed, have shown that the East African Highlands, although not very high, play a significant role in the climate of Africa, India and Southeast Asia, and in the heat, salinity and momentum forcing of the Western Indian Ocean. The hydrological cycle over Africa is systematically enhanced in all seasons by the presence of the East African Highlands, and during the Asian summer monsoon there is a major redistribution of the rainfall across India and Southeast Asia. The implied impact of the East African Highlands on the ocean is substantial. The East African Highlands systematically freshen the tropical Indian Ocean, and act to focus the monsoon winds along the coast, leading to greater upwelling and cooler sea–surface temperatures.

Probabilistic simulations of crop yield over western India using the DEMETER seasonal hindcast ensembles

Process-based integrated modelling of weather and crop yield over large areas is becoming an important research topic. The production of the DEMETER ensemble hindcasts of weather allows this work to be carried out in a probabilistic framework. In this study, ensembles of crop yield (groundnut, Arachis hypogaea L.) were produced for 10 2.5 degrees x 2.5 degrees grid cells in western India using the DEMETER ensembles and the general large-area model (GLAM) for annual crops. Four key issues are addressed by this study. First, crop model calibration methods for use with weather ensemble data are assessed. Calibration using yield ensembles was more successful than calibration using reanalysis data (the European Centre for Medium-Range Weather Forecasts 40-yr reanalysis, ERA40). Secondly, the potential for probabilistic forecasting of crop failure is examined. The hindcasts show skill in the prediction of crop failure, with more severe failures being more predictable. Thirdly, the use of yield ensemble means to predict interannual variability in crop yield is examined and their skill assessed relative to baseline simulations using ERA40. The accuracy of multi-model yield ensemble means is equal to or greater than the accuracy using ERA40. Fourthly, the impact of two key uncertainties, sowing window and spatial scale, is briefly examined. The impact of uncertainty in the sowing window is greater with ERA40 than with the multi-model yield ensemble mean. Subgrid heterogeneity affects model accuracy: where correlations are low on the grid scale, they may be significantly positive on the subgrid scale. The implications of the results of this study for yield forecasting on seasonal time-scales are as follows. (i) There is the potential for probabilistic forecasting of crop failure (defined by a threshold yield value); forecasting of yield terciles shows less potential. (ii) Any improvement in the skill of climate models has the potential to translate into improved deterministic yield prediction. (iii) Whilst model input uncertainties are important, uncertainty in the sowing window may not require specific modelling. The implications of the results of this study for yield forecasting on multidecadal (climate change) time-scales are as follows. (i) The skill in the ensemble mean suggests that the perturbation, within uncertainty bounds, of crop and climate parameters, could potentially average out some of the errors associated with mean yield prediction. (ii) For a given technology trend, decadal fluctuations in the yield-gap parameter used by GLAM may be relatively small, implying some predictability on those time-scales.

Development and assessment of a coupled crop-climate model

It is well established that crop production is inherently vulnerable to variations in the weather and climate. More recently the influence of vegetation on the state of the atmosphere has been recognized. The seasonal growth of crops can influence the atmosphere and have local impacts on the weather, which in turn affects the rate of seasonal crop growth and development. Considering the coupled nature of the crop-climate system, and the fact that a significant proportion of land is devoted to the cultivation of crops, important interactions may be missed when studying crops and the climate system in isolation, particularly in the context of land use and climate change. To represent the two-way interactions between seasonal crop growth and atmospheric variability, we integrate a crop model developed specifically to operate at large spatial scales (General Large Area Model for annual crops) into the land surface component of a global climate model (GCM; HadAM3). In the new coupled crop-climate model, the simulated environment (atmosphere and soil states) influences growth and development of the crop, while simultaneously the temporal variations in crop leaf area and height across its growing season alter the characteristics of the land surface that are important determinants of surface fluxes of heat and moisture, as well as other aspects of the land-surface hydrological cycle. The coupled model realistically simulates the seasonal growth of a summer annual crop in response to the GCM's simulated weather and climate. The model also reproduces the observed relationship between seasonal rainfall and crop yield. The integration of a large-scale single crop model into a GCM, as described here, represents a first step towards the development of fully coupled crop and climate models. Future development priorities and challenges related to coupling crop and climate models are discussed.

Adaptation to climate change and variability: farmer responses to intra-seasonal precipitation trends in South Africa

We describe the nature of recent (50 year) rainfall variability in the summer rainfall zone, South Africa, and how variability is recognised and responded to on the ground by farmers. Using daily rainfall data and self-organising mapping (SOM) we identify 12 internally homogeneous rainfall regions displaying differing parameters of precipitation change. Three regions, characterised by changing onset and timing of rains, rainfall frequencies and intensities, in Limpopo, North West and KwaZulu Natal provinces, were selected to investigate farmer perceptions of, and responses to, rainfall parameter changes. Village and household level analyses demonstrate that the trends and variabilities in precipitation parameters differentiated by the SOM analysis were clearly recognised by people living in the areas in which they occurred. A range of specific coping and adaptation strategies are employed by farmers to respond to climate shifts, some generic across regions and some facilitated by specific local factors. The study has begun to understand the complexity of coping and adaptation, and the factors that influence the decisions that are taken.

Changes of interannual NAO variability in response to greenhouse gases forcing

Observations show that there was change in interannual North Atlantic Oscillation (NAO) variability in the mid-1970s. This change was characterized by an eastward shift of the NAO action centres, a poleward shift of zonal wind anomalies and a downstream extension of climate anomalies associated with the NAO. The NAO interannual variability for the period after the mid-1970s has an annular mode structure that penetrates deeply into the stratosphere, indicating a strengthened relationship between the NAO and the Arctic Oscillation (AO) and strengthened stratosphere-troposphere coupling. In this study we have investigated possible causes of these changes in the NAO by carrying out experiments with an atmospheric GCM. The model is forced either by doubling CO2, or increasing sea surface temperatures (SST), or both. In the case of SST forcing the SST anomaly is derived from a coupled model simulation forced by increasing CO2. Results indicate that SST and CO2 change both force a poleward and eastward shift in the pattern of interannual NAO variability and the associated poleward shift of zonal wind anomalies, similar to the observations. The effect of SST change can be understood in terms of mean changes in the troposphere. The direct effect of CO2 change, in contrast, can not be understood in terms of mean changes in the troposphere. However, there is a significant response in the stratosphere, characterized by a strengthened climatological polar vortex with strongly enhanced interannual variability. In this case, the NAO interannual variability has a strong link with the variability over the North Pacific, as in the annular AO pattern, and is also strongly related to the stratospheric vortex, indicating strengthened stratosphere-troposphere coupling. The similarity of changes in many characteristics of NAO interannual variability between the model response to doubling CO2 and those in observations in the mid-1970s implies that the increase of greenhouse gas concentration in the atmosphere, and the resulting changes in the stratosphere, might have played an important role in the multidecadal change of interannual NAO variability and its associated climate anomalies during the late twentieth century. The weak change in mean westerlies in the troposphere in response to CO2 change implies that enhanced and eastward extended mid-latitude westerlies in the troposphere might not be a necessary condition for the poleward and eastward shift of the NAO action centres in the mid-1970s.

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UKMeteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is underestimated (over-estimated) over wet (dry) regions of southern Africa.

The precipitation climate of Central Asia: intercomparison of observational and numerical data sources in a remote semiarid region

In this study, we systematically compare a wide range of observational and numerical precipitation datasets for Central Asia. Data considered include two re-analyses, three datasets based on direct observations, and the output of a regional climate model simulation driven by a global re-analysis. These are validated and intercompared with respect to their ability to represent the Central Asian precipitation climate. In each of the datasets, we consider the mean spatial distribution and the seasonal cycle of precipitation, the amplitude of interannual variability, the representation of individual yearly anomalies, the precipitation sensitivity (i.e. the response to wet and dry conditions), and the temporal homogeneity of precipitation. Additionally, we carried out part of these analyses for datasets available in real time. The mutual agreement between the observations is used as an indication of how far these data can be used for validating precipitation data from other sources. In particular, we show that the observations usually agree qualitatively on anomalies in individual years while it is not always possible to use them for the quantitative validation of the amplitude of interannual variability. The regional climate model is capable of improving the spatial distribution of precipitation. At the same time, it strongly underestimates summer precipitation and its variability, while interannual variations are well represented during the other seasons, in particular in the Central Asian mountains during winter and spring

Hydrological cycle in the Danube basin in present-day and XXII century simulations by IPCCAR4 global climate models

We present an intercomparison and verification analysis of 20 GCMs (Global Circulation Models) included in the 4th IPCC assessment report regarding their representation of the hydrological cycle on the Danube river basin for 1961–2000 and for the 2161–2200 SRESA1B scenario runs. The basin-scale properties of the hydrological cycle are computed by spatially integrating the precipitation, evaporation, and runoff fields using the Voronoi-Thiessen tessellation formalism. The span of the model- simulated mean annual water balances is of the same order of magnitude of the observed Danube discharge of the Delta; the true value is within the range simulated by the models. Some land components seem to have deficiencies since there are cases of violation of water conservation when annual means are considered. The overall performance and the degree of agreement of the GCMs are comparable to those of the RCMs (Regional Climate Models) analyzed in a previous work, in spite of the much higher resolution and common nesting of the RCMs. The reanalyses are shown to feature several inconsistencies and cannot be used as a verification benchmark for the hydrological cycle in the Danubian region. In the scenario runs, for basically all models the water balance decreases, whereas its interannual variability increases. Changes in the strength of the hydrological cycle are not consistent among models: it is confirmed that capturing the impact of climate change on the hydrological cycle is not an easy task over land areas. Moreover, in several cases we find that qualitatively different behaviors emerge among the models: the ensemble mean does not represent any sort of average model, and often it falls between the models’ clusters.

Variation in the global-scale impacts of climate change on crop productivity due to climate model uncertainty and adaptation

Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs. Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation.