The impact of a seasonally ice free Arctic Ocean on the temperature, precipitation and surface mass balance of Svalbard

The observed decline in summer sea ice extent since the 1970s is predicted to continue until the Arctic Ocean is seasonally ice free during the 21st Century. This will lead to a much perturbed Arctic climate with large changes in ocean surface energy flux. Svalbard, located on the present day sea ice edge, contains many low lying ice caps and glaciers and is expected to experience rapid warming over the 21st Century. The total sea level rise if all the land ice on Svalbard were to melt completely is 0.02 m. The purpose of this study is to quantify the impact of climate change on Svalbard’s surface mass balance (SMB) and to determine, in particular, what proportion of the projected changes in precipitation and SMB are a result of changes to the Arctic sea ice cover. To investigate this a regional climate model was forced with monthly mean climatologies of sea surface temperature (SST) and sea ice concentration for the periods 1961–1990 and 2061–2090 under two emission scenarios. In a novel forcing experiment, 20th Century SSTs and 21st Century sea ice were used to force one simulation to investigate the role of sea ice forcing. This experiment results in a 3.5 m water equivalent increase in Svalbard’s SMB compared to the present day. This is because over 50 % of the projected increase in winter precipitation over Svalbard under the A1B emissions scenario is due to an increase in lower atmosphere moisture content associated with evaporation from the ice free ocean. These results indicate that increases in precipitation due to sea ice decline may act to moderate mass loss from Svalbard’s glaciers due to future Arctic warming.

A proposal for a new scenario framework to support research and assessment in different climate research communities

In this paper, we propose a scenario framework that could provide a scenario “thread” through the different climate research communities (climate change – vulnerability, impact, and adaptation (VIA) and mitigation) in order to provide assessment of mitigation and adaptation strategies and other VIA challenges. The scenario framework is organised around a matrix with two main axes: radiative forcing levels and socio-economic conditions. The radiative forcing levels (and the associated climate signal) are described by the new Representative Concentration Pathways. The second axis, socio-economic developments, comprises elements that affect the capacity for mitigation and adaptation, as well as the exposure to climate impacts. The proposed scenarios derived from this framework are limited in number, allow for comparison across various mitigation and adaptation levels, address a range of vulnerability characteristics, provide information across climate forcing and vulnerability states and span a full century time scale. Assessments based on the proposed scenario framework would strengthen cooperation between integrated-assessment modelers, climate modelers and vulnerability, impact and adaptation researchers, and most importantly, facilitate the development of more consistent and comparable research within and across communities.

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.

Assessing and understanding the impact of stratospheric dynamics and variability on the earth system

Advances in weather and climate research have demonstrated the role of the stratosphere in the Earth system across a wide range of temporal and spatial scales. Stratospheric ozone loss has been identified as a key driver of Southern Hemisphere tropospheric circulation trends, affecting ocean currents and carbon uptake, sea ice, and possibly even the Antarctic ice sheets. Stratospheric variability has also been shown to affect short term and seasonal forecasts, connecting the tropics and midlatitudes and guiding storm track dynamics. The two-way interactions between the stratosphere and the Earth system have motivated the World Climate Research Programme's (WCRP) Stratospheric Processes and Their Role in Climate (SPARC) DynVar activity to investigate the impact of stratospheric dynamics and variability on climate. This assessment will be made possible by two new multi-model datasets. First, roughly 10 models with a well resolved stratosphere are participating in the Coupled Model Intercomparison Project 5 (CMIP5), providing the first multi-model ensemble of climate simulations coupled from the stratopause to the sea floor. Second, the Stratosphere Historical Forecasting Project (SHFP) of WCRP's Climate Variability and predictability (CLIVAR) program is forming a multi-model set of seasonal hindcasts with stratosphere resolving models, revealing the impact of both stratospheric initial conditions and dynamics on intraseasonal prediction. The CMIP5 and SHFP model-data sets will offer an unprecedented opportunity to understand the role of the stratosphere in the natural and forced variability of the Earth system and to determine whether incorporating knowledge of the middle atmosphere improves seasonal forecasts and climate projections. Capsule New modeling efforts will provide unprecedented opportunities to harness our knowledge of the stratosphere to improve weather and climate prediction.

Calibration and bias correction of climate projections for crop modelling: an idealised case study over Europe

Producing projections of future crop yields requires careful thought about the appropriate use of atmosphere-ocean global climate model (AOGCM) simulations. Here we describe and demonstrate multiple methods for ‘calibrating’ climate projections using an ensemble of AOGCM simulations in a ‘perfect sibling’ framework. Crucially, this type of analysis assesses the ability of each calibration methodology to produce reliable estimates of future climate, which is not possible just using historical observations. This type of approach could be more widely adopted for assessing calibration methodologies for crop modelling. The calibration methods assessed include the commonly used ‘delta’ (change factor) and ‘nudging’ (bias correction) approaches. We focus on daily maximum temperature in summer over Europe for this idealised case study, but the methods can be generalised to other variables and other regions. The calibration methods, which are relatively easy to implement given appropriate observations, produce more robust projections of future daily maximum temperatures and heat stress than using raw model output. The choice over which calibration method to use will likely depend on the situation, but change factor approaches tend to perform best in our examples. Finally, we demonstrate that the uncertainty due to the choice of calibration methodology is a significant contributor to the total uncertainty in future climate projections for impact studies. We conclude that utilising a variety of calibration methods on output from a wide range of AOGCMs is essential to produce climate data that will ensure robust and reliable crop yield projections.

The impact of stratospheric ozone recovery on the Southern Hemisphere westerly jet

In the past several decades, the tropospheric westerly winds in the Southern Hemisphere have been observed to accelerate on the poleward side of the surface wind maximum. This has been attributed to the combined anthropogenic effects of increasing greenhouse gases and decreasing stratospheric ozone and is predicted to continue by the Intergovernmental Panel on Climate Change/Fourth Assessment Report (IPCC/AR4) models. In this paper, the predictions of the Chemistry-Climate Model Validation (CCMVal) models are examined: Unlike the AR4 models, the CCMVal models have a fully interactive stratospheric chemistry. Owing to the expected disappearance of the ozone hole in the first half of the 21st century, the CCMVal models predict that the tropospheric westerlies in Southern Hemisphere summer will be decelerated, on the poleward side, in contrast with the prediction of most IPCC/AR4 models.

Changing climate and the Irish landscape

The impacts of current and future changes in climate have been investigated for Irish vegetation. Warming has been observed over the last two decades, with impacts that are also strongly influenced by natural oscillations of the surrounding ocean, seen as fluctuations in the North Atlantic Oscillation and the Atlantic Multidecadal Oscillation. Satellite observations show that vegetation greenness increases in warmer years, a feature mirrored by increases in net ecosystem production observed for a grassland and a plantation forest. An ensemble of general circulation model simulations of future climates indicate temperature rises over the twenty-first century ranging from 1°C to 7°C, depending on future scenarios of greenhouse gas emissions. Net primary production is simulated to increase under all scenarios, due to the positive impacts of rising temperature, a modest rise of precipitation and rising carbon dioxide concentrations. In an optimistic scenario of reducing future emissions, CO2 concentration is simulated to flatten from about 2070, although temperatures continue to increase. Under this scenario Ireland could become a source of carbon, whereas under all other emission scenarios Ireland is a sink for carbon that may increase by up to three-fold over the twenty-first century. A likely and unavoidable impact of changing climate is the arrival of alien plant species, which may disrupt ecosystems and exert negative impacts on native biodiversity. Alien species arrive continually, with about 250 dated arrivals in the twentieth century. A simulation model indicates that this rate of alien arrival may increase by anything between two and ten times, dependent on the future climatic scenario, by 2050. Which alien species may become severely disruptive is, however, not known.

Climate change, extreme weather events and issues of human perception

The central proposition of Toby Pillatt is that in developing an understanding of past human affairs weather is as important as, or more so than, climate. Climate may be simply defined as average weather, whilst weather is the day-to-day occurrence of atmospheric phenomena which impact in perceptible ways on people's lives. The general proposition is sound enough; the challenges come in implementing these ideas in ways which advance our understanding of past people–environment relationships.

Climate change and the South Asian summer monsoon

The vagaries of South Asian summer monsoon rainfall on short and long timescales impact the lives of more than one billion people. Understanding how the monsoon will change in the face of global warming is a challenge for climate science, not least because our state-of-the-art general circulation models still have difficulty simulating the regional distribution of monsoon rainfall. However, we are beginning to understand more about processes driving the monsoon, its seasonal cycle and modes of variability. This gives us the hope that we can build better models and ultimately reduce the uncertainty in our projections of future monsoon rainfall.

A framework for agricultural adaptation to climate change in Southern Nigeria

The agricultural sector which contributes between 20-50% of gross domestic product in Africa and employs about 60% of the population is greatly affected by climate change impacts. Agricultural productivity and food prices are expected to rise due to this impact thereby worsening the food insecurity and poor nutritional health conditions in the continent. Incidentally, the capacity in the continent to adapt is very low. Addressing these challenges will therefore require a holistic and integrated adaptation framework hence this study. A total of 360 respondents selected through a multi-stage random sampling technique participated in the study that took place in Southern Nigeria from 2008-2011. Results showed that majority of respondents (84%) were aware that some climate change characteristics such as uncertainties at the onset of farming season, extreme weather events including flooding and droughts, pests, diseases, weed infestation, and land degradation have all been on the increase. The most significant effects of climate change that manifested in the area were declining soil fertility and weed infestation. Some of the adaptation strategies adopted by farmers include increased weeding, changing the timing of farm operations, and processing of crops to reduce post-harvest losses. Although majority of respondents were aware of government policies aimed at protecting the environment, most of them agreed that these policies were not being effectively implemented. A mutually inclusive framework comprising of both indigenous and modern techniques, processes, practices and technologies was then developed from the study in order to guide farmers in adapting to climate change effects/impacts.

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.

Climate change impacts on crop productivity in Africa and South Asia

Climate change is a serious threat to crop productivity in regions that are already food insecure. We assessed the projected impacts of climate change on the yield of eight major crops in Africa and South Asia using a systematic review and meta-analysis of data in 52 original publications from an initial screen of 1144 studies. Here we show that the projected mean change in yield of all crops is − 8% by the 2050s in both regions. Across Africa, mean yield changes of − 17% (wheat), − 5% (maize), − 15% (sorghum) and − 10% (millet) and across South Asia of − 16% (maize) and − 11% (sorghum) were estimated. No mean change in yield was detected for rice. The limited number of studies identified for cassava, sugarcane and yams precluded any opportunity to conduct a meta-analysis for these crops. Variation about the projected mean yield change for all crops was smaller in studies that used an ensemble of > 3 climate (GCM) models. Conversely, complex simulation studies that used biophysical crop models showed the greatest variation in mean yield changes. Evidence of crop yield impact in Africa and South Asia is robust for wheat, maize, sorghum and millet, and either inconclusive, absent or contradictory for rice, cassava and sugarcane.

Impact of duration thresholds on Atlantic tropical cyclone counts*

Records of Atlantic basin tropical cyclones (TCs) since the late nineteenth century indicate a very large upward trend in storm frequency. This increase in documented TCs has been previously interpreted as resulting from anthropogenic climate change. However, improvements in observing and recording practices provide an alternative interpretation for these changes: recent studies suggest that the number of potentially missed TCs is sufficient to explain a large part of the recorded increase in TC counts. This study explores the influence of another factor—TC duration—on observed changes in TC frequency, using a widely used Atlantic hurricane database (HURDAT). It is found that the occurrence of short-lived storms (duration of 2 days or less) in the database has increased dramatically, from less than one per year in the late nineteenth–early twentieth century to about five per year since about 2000, while medium- to long-lived storms have increased little, if at all. Thus, the previously documented increase in total TC frequency since the late nineteenth century in the database is primarily due to an increase in very short-lived TCs. The authors also undertake a sampling study based upon the distribution of ship observations, which provides quantitative estimates of the frequency of missed TCs, focusing just on the moderate to long-lived systems with durations exceeding 2 days in the raw HURDAT. Upon adding the estimated numbers of missed TCs, the time series of moderate to long-lived Atlantic TCs show substantial multidecadal variability, but neither time series exhibits a significant trend since the late nineteenth century, with a nominal decrease in the adjusted time series. Thus, to understand the source of the century-scale increase in Atlantic TC counts in HURDAT, one must explain the relatively monotonic increase in very short-duration storms since the late nineteenth century. While it is possible that the recorded increase in short-duration TCs represents a real climate signal, the authors consider that it is more plausible that the increase arises primarily from improvements in the quantity and quality of observations, along with enhanced interpretation techniques. These have allowed National Hurricane Center forecasters to better monitor and detect initial TC formation, and thus incorporate increasing numbers of very short-lived systems into the TC database.

Using seasonal hindcasts to understand the origin of the equatorial cold tongue bias in CGCMs and its impact on ENSO

The cold equatorial SST bias in the tropical Pacific that is persistent in many coupled OAGCMs severely impacts the fidelity of the simulated climate and variability in this key region, such as the ENSO phenomenon. The classical bias analysis in these models usually concentrates on multi-decadal to centennial time series needed to obtain statistically robust features. Yet, this strategy cannot fully explain how the models errors were generated in the first place. Here, we use seasonal re-forecasts (hindcasts) to track back the origin of this cold bias. As such hindcasts are initialized close to observations, the transient drift leading to the cold bias can be analyzed to distinguish pre-existing errors from errors responding to initial ones. A time sequence of processes involved in the advent of the final mean state errors can then be proposed. We apply this strategy to the ENSEMBLES-FP6 project multi-model hindcasts of the last decades. Four of the five AOGCMs develop a persistent equatorial cold tongue bias within a few months. The associated systematic errors are first assessed separately for the warm and cold ENSO phases. We find that the models are able to reproduce either El Niño or La Niña close to observations, but not both. ENSO composites then show that the spurious equatorial cooling is maximum for El Niño years for the February and August start dates. For these events and at this time of the year, zonal wind errors in the equatorial Pacific are present from the beginning of the simulation and are hypothesized to be at the origin of the equatorial cold bias, generating too strong upwelling conditions. The systematic underestimation of the mixed layer depth in several models can also amplify the growth of the SST bias. The seminal role of these zonal wind errors is further demonstrated by carrying out ocean-only experiments forced by the AOCGCMs daily 10-meter wind. In a case study, we show that for several models, this forcing is sufficient to reproduce the main SST error patterns seen after 1 month in the AOCGCM hindcasts.

Wildfire responses to abrupt climate change in North America

It is widely accepted, based on data from the last few decades and on model simulations, that anthropogenic climate change will cause increased fire activity. However, less attention has been paid to the relationship between abrupt climate changes and heightened fire activity in the paleorecord. We use 35 charcoal and pollen records to assess how fire regimes in North America changed during the last glacial–interglacial transition (15 to 10 ka), a time of large and rapid climate changes. We also test the hypothesis that a comet impact initiated continental-scale wildfires at 12.9 ka; the data do not support this idea, nor are continent-wide fires indicated at any time during deglaciation. There are, however, clear links between large climate changes and fire activity. Biomass burning gradually increased from the glacial period to the beginning of the Younger Dryas. Although there are changes in biomass burning during the Younger Dryas, there is no systematic trend. There is a further increase in biomass burning after the Younger Dryas. Intervals of rapid climate change at 13.9, 13.2, and 11.7 ka are marked by large increases in fire activity. The timing of changes in fire is not coincident with changes in human population density or the timing of the extinction of the megafauna. Although these factors could have contributed to fire-regime changes at individual sites or at specific times, the charcoal data indicate an important role for climate, and particularly rapid climate change, in determining broad-scale levels of fire activity.