Increasing impacts of climate change upon ecosystems with increasing global mean temperature rise

In a meta-analysis we integrate peer-reviewed studies that provide quantified estimates of future projected ecosystem changes related to quantified projected local or global climate changes. In an advance on previous analyses, we reference all studies to a common pre-industrial base-line for temperature, employing up-scaling techniques where necessary, detailing how impacts have been projected on every continent, in the oceans, and for the globe, for a wide range of ecosystem types and taxa. Dramatic and substantive projected increases of climate change impacts upon ecosystems are revealed with increasing annual global mean temperature rise above the pre-industrial mean (ΔT_g). Substantial negative impacts are commonly projected as ΔT_g reaches and exceeds 2°C, especially in biodiversity hotspots. Compliance with the ultimate objective of the United Nations Framework Convention on Climate Change (Article 2) requires that greenhouse gas concentrations be stabilized within a time frame “sufficient to allow ecosystems to adapt naturally to climate change”. Unless ΔT_g is constrained to below 2°C at most, results here imply that it will be difficult to achieve compliance. This underscores the need to limit greenhouse gas emissions by accelerating mitigation efforts and by protecting existing ecosystems from greenhouse-gas producing land use change processes such as deforestation.     

Mechanism development and modelling of tropospheric multiphase halogen chemistry: The CAPRAM Halogen Module 2.0 (HM2)

A new detailed multiphase halogen mechanism, the CAPRAM Halogen Module 2.0 (HM2), has been developed and coupled to the multiphase chemistry mechanism RACM-MIM2ext/CAPRAM 3.0n. The overall mechanism comprises 1,705 reactions including 595 reactions of the HM2. Halogen chemistry box model studies have been, for the first time, performed with a non-permanent cloud scenario for pristine open ocean regions in mid-latitudes. Moreover, detailed time-resolved reaction flux analysis has been used to investigate the multiphase halogen reaction cycles in more detail. Clouds significantly change the multiphase halogen chemical system and new reaction cycles are proposed for in-cloud conditions. While most gas phase concentrations are decreased for chlorine and iodine species, they are increased for bromine. Flux analyses determined the relative contributions of the methylene dihalides CH₂IX (X = Cl, Br, I) as the main I atom source with a contribution of about 80 % to the total iodocarbon sources. Furthermore, HOI was confirmed to be important for chlorine activation. It is shown that 25 % of the ozone loss can be attributed to halogens. VOC oxidation by halogens is important as halogens account for about 20 % of the methane oxidation and up to 80 % of the oxidation of other VOCs. In other cases, enhanced VOC and VOC oxidation product concentration levels were found. For example, 15 % of the methyl peroxyl radicals are formed after the reaction of chlorine atoms with methane or methyl hydroperoxide. In the aqueous phase, changes in the oxidation of organics do only occur for highly oxidised organics without a C-H bond. For example, over 80 % of oxalic acid are oxidised by electron transfer with Cl₂ ^? in deliquescent particles during non-cloud periods.     

Relevance of thermal environment to human health: a case study of Ondo State, Nigeria

The interconnection between weather and climate and the performance, well-being, and human health cannot be overemphasized. The relationship between them is of both local and global significance. Information about weather, climate, and thermal environment is very important to human health and medical practitioners. The most crucial environmental information needed by medical practitioners and for maintaining human health, performance, and well-being are thermal conditions. The study used meteorological variables: air temperature, relative humidity, wind speed, solar radiation, and RayMan model as an analytical tool to compute physiologically equivalent temperature (PET) in order to assess thermo-physiological thresholds in Ondo State. The study revealed that there are marked spatial and seasonal variations in the environmental thermal conditions in the study area. The results of physiologically equivalent temperature for different grades of thermal sensation and physiological stress on human beings indicate that about 60 % of the total study period (1998–2008) fall under physiological stress level of moderate heat stress (PET 31–36 °C). In derived savannah, 32.6 % out of the total study period was under strong heat stress. In view of this, the study concluded that Ondo State may likely be prone to heat-related ailments and that some of the death recorded in the State, in recent times, may be heat-related mortality, but this is difficult to ascertain because there is no postmortem records in Nigeria where it could be confirmed. This type of study is relevant to help government to improve health care interventions and achieve Millennium Development Goals in health sector.     

Multi-variable error correction of regional climate models

Climate change impact research needs regional climate scenarios of multiple meteorological variables. Those variables are available from regional climate models (RCMs), but affected by considerable biases. We evaluate the application of an empirical-statistical error correction method, quantile mapping (QM), for a small ensemble of RCMs and six meteorological variables. Annual and monthly biases are reduced to close to zero by QM for all variables in most cases. Exceptions are found, if non-stationarity of the model’s error characteristics occur. Even in the worst cases of non-stationarity, QM clearly improves the biases of raw RCMs. In addition, QM successfully adjusts the distributions of the analysed variables. To approach the question whether time series and inter-variable relationships are still plausible after correction, we evaluate the root-mean-square error (RMSE), autocorrelation and inter-variable correlation. We found improvement or no clear effect in RMSE and autocorrelation, and no clear effect on the correlation between meteorological variables. These results demonstrate that QM retains the quality of the temporal structure in time series and the inter-variable dependencies of RCMs. It has to be emphasised that this cannot be interpreted as an improvement and that deficiencies of the RCMs in those features are retained as well. Our results give some indication for the performance of QM applied to future scenarios, since our evaluation relies on independent calibration and evaluation periods, which are affected by climate variability and change. The effect of non-stationarity, however, can be expected to be larger in far future. We demonstrate the retainment of the RCM’s temporal structure and inter-variable dependencies, and large improvements in biases. This qualifies QM as a valuable, though not perfect, method in the interface between climate models and climate change impact research. Nonetheless, in case of no correlation between re-analysis driven RCM and observation, one should consider that QM does not correct this correlation.     

Basic analysis of climate and urban bioclimate of Dar es Salaam, Tanzania

Better understanding of urban microclimate and bioclimate of any city is imperative today when the world is constrained by both urbanisation and global climate change. Urbanisation generally triggers changes in land cover and hence influencing the urban local climate. Dar es Salaam city in Tanzania is one of the fast growing cities. Assessment of its urban climate and the human biometeorological conditions was done using the easily available synoptic meteorological data covering the period 2001–2011. In particular, the physiologically equivalent temperature (PET) was calculated using the RayMan software and results reveal that the afternoon period from December to February (DJF season) is relatively the most thermal stressful period to human beings in Dar es Salaam where PET values of above 35 °C were found. Additionally, the diurnal cycle of the individual meteorological elements that influence the PET index were analysed and found that air temperature of 30–35 °C dominate the afternoon period from 12:00 to 15:00 hours local standard time at about 60 % of occurrence. The current results, though considered as preliminary to the ongoing urban climate study in the city, provide an insight on how urban climate research is of significant importance in providing useful climatic information for ensuring quality of life and wellbeing of city dwellers.     

Uncertainty, learning and ambiguity in economic models on climate policy: some classical results and new directions

We present how uncertainty and learning are classically studied in economic models. Specifically, we study a standard expected utility model with two sequential decisions, and consider two particular cases of this model to illustrate how uncertainty and learning may affect climate policy. While uncertainty has generally a negative effect on welfare, learning has always a positive, and thus opposite, effect. The effects of both uncertainty and learning on decisions are less clear. Neither uncertainty nor learning can be used as a general argument to increase or reduce emissions today without studying the specific intertemporal costs and benefits. Considering limits in applying the expected utility framework to climate change problems, we then consider a more recent framework with ambiguity-aversion which accounts for situations of imprecise or multiple probability distributions. We discuss both the impact of ambiguity-aversion on decisions and difficulties in applying such a non-expected utility framework to a dynamic context.     

Observing upper troposphere–lower stratosphere climate with radio occultation data from the CHAMP satellite

High quality observations of the atmosphere are particularly required for monitoring global climate change. Radio occultation (RO) data, using Global Navigation Satellite System (GNSS) signals, are well suited for this challenge. The special climate utility of RO data arises from their long-term stability due to their self-calibrated nature. The German research satellite CHAllenging Minisatellite Payload for geoscientific research (CHAMP) continuously records RO profiles since August 2001 providing the first opportunity to create RO based climatologies for a multi-year period of more than 5 years. A period of missing CHAMP data from July 3, 2006 to August 8, 2006 can be bridged with RO data from the GRACE satellite (Gravity Recovery and Climate Experiment). We have built seasonal and zonal mean climatologies of atmospheric (dry) temperature, microwave refractivity, geopotential height and pressure with 10° latitudinal resolution. We show representative results with focus on dry temperatures and compare them with analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Although we have available only about 150 CHAMP profiles per day (compared to millions of data entering the ECMWF analyses) the overall agreement between 8 and 30 km altitude is in general very good with systematic differences <0.5 K in most parts of the domain. Pronounced systematic differences (exceeding 2 K) in the tropical tropopause region and above Antarctica in southern winter can almost entirely be attributed to errors in the ECMWF analyses. Errors resulting from uneven sampling in space and time are a potential error source for single-satellite climatologies. The average CHAMP sampling error for seasonal zonal means is <0.2 K, higher values occur in restricted regions and time intervals which can be clearly identified by the sampling error estimation approach we introduced (which is based on ECMWF analysis fields). The total error of this new type of temperature climatologies is estimated to be <0.5 K below 30 km. The recently launched Taiwan/U.S. FORMOSAT-3/COSMIC constellation of 6 RO satellites started to provide thousands of RO profiles per day, but already now the single-satellite CHAMP RO climatologies improve upon modern operational climatologies in the upper troposphere–lower stratosphere and can act as absolute reference climatologies for validation of more bias-sensitive climate datasets and models.     

The simulation of European heat waves from an ensemble of regional climate models within the EURO-CORDEX project

The ability of a large ensemble of regional climate models to accurately simulate heat waves at the regional scale of Europe was evaluated. Within the EURO-CORDEX project, several state-of-the art models, including non-hydrostatic meso-scale models, were run for an extended time period (20 years) at high resolution (12 km), over a large domain allowing for the first time the simultaneous representation of atmospheric phenomena over a large range of spatial scales. Eight models were run in this configuration, and thirteen models were run at a classical resolution of 50 km. The models were driven with the same boundary conditions, the ERA-Interim re-analysis, and except for one simulation, no observations were assimilated in the inner domain. Results, which are compared with daily temperature and precipitation observations (ECA&D and E-OBS data sets) show that, even forced by the same re-analysis, the ensemble exhibits a large spread. A preliminary analysis of the sources of spread, using in particular simulations of the same model with different parameterizations, shows that the simulation of hot temperature is primarily sensitive to the convection and the microphysics schemes, which affect incoming energy and the Bowen ratio. Further, most models exhibit an overestimation of summertime temperature extremes in Mediterranean regions and an underestimation over Scandinavia. Even after bias removal, the simulated heat wave events were found to be too persistent, but a higher resolution reduced this deficiency. The amplitude of events as well as the variability beyond the 90th percentile threshold were found to be too strong in almost all simulations and increasing resolution did not generally improve this deficiency. Resolution increase was also shown to induce large-scale 90th percentile warming or cooling for some models, with beneficial or detrimental effects on the overall biases. Even though full causality cannot be established on the basis of this evaluation work, the drivers of such regional differences were shown to be linked to changes in precipitation due to resolution changes, affecting the energy partitioning. Finally, the inter-annual sequence of hot summers over central/southern Europe was found to be fairly well simulated in most experiments despite an overestimation of the number of hot days and of the variability. The accurate simulation of inter-annual variability for a few models is independent of the model bias. This indicates that internal variability of high summer temperatures should not play a major role in controlling inter-annual variability. Despite some improvements, especially along coastlines, the analyses conducted here did not allow us to generally conclude that a higher resolution is clearly beneficial for a correct representation of heat waves by regional climate models. Even though local-scale feedbacks should be better represented at high resolution, combinations of parameterizations have to be improved or adapted accordingly.     

Tracking suitable habitat for tree populations under climate change in western North America

An important criticism of bioclimate envelope models is that many wide-ranging species consist of locally adapted populations that may all lag behind their optimal climate habitat under climate change, and thus should be modeled separately. Here, we apply a bioclimate envelope model that tracks habitat of individual populations to estimate adaptational lags for 15 wide-ranging forest tree species in western North America. An ensemble classifier modeling approach (RandomForest) was used to spatially project the climate space of tree populations under observed climate trends (1970s to 2000s) and multi-model projections for the 2020s, 2050s and 2080s. We find that, on average, populations already lag behind their optimal climate niche by approximately 130 km in latitude, or 60 m in elevation. For the 2020s we expect an average lag of approximately 310 km in latitude or 140 m in elevation, with the most pronounced geographic lags in the Rocky Mountains and the boreal forest. We show that our results could in principle be applied to guide assisted migration of planting stock in reforestation programs using a general formula where 100 km north shift is equivalent to approximately 44 m upward shift in elevation. However, additional non-climatic factors should be considered when matching reforestation stock to suitable planting environments.     

Constraints on 2-Way Transport across the Arctic Tropopause Based on O3, Stratospheric Tracer (SF6) Ages, and Water Vapor Isotope (D, T) Tracers

Based upon airborne trace gas and isotope observations in the winter months 1991/1992 to1994/1995, transport pathways across the mid-latitude and Arctic tropopause areinvestigated. A powerful set of contrasting transport tracers are examined, such asdeuterated water vapor (HDO) which is shown to trace the passage of water vapor from thetroposphere into the lowermost stratosphere (LS), or the `SF₆ age' defined as theresidence time of an air parcel within the stratosphere since its entry at thetropopause. Cross-tropopause transport in both directions was found near mid-latitudecyclones (at baroclinic flanks of troughs in the polar front), in which about 80% of thestratosphere-to-troposphere flux proceeded along potential temperature ()surfaces of 300 ± 10 K. As these isentropes are the lowest which reach into the LS(in winter), a mixing zone just above the Arctic tropopause (at least 1.5 km thick) isformed. Here, upwelling tropospheric air is mixed with downwelling LS air which isaffected by air from higher altitudes, the surf-zone and the polar vortex. The observedelevated D/H isotope ratio of water vapor within the mixing zone can be explained byinjection of subtropical water vapor that is transported to the tropopause by the warmconveyor belt associated with mid-latitude cyclones. Downward vertical transport ofArctic LS air, which may be influenced by ouflowing chemically disturbed polar vortexair, into the Arctic troposphere was found to be small.