A common-sense climate index: Is climate changing noticeably?

We propose an index of climate change based on practical climate indicators such as heating degree days and the frequency of intense precipitation. We find that in most regions the index is positive, the sense predicted to accompany global warming. In a few regions, especially in Asia and western North America, the index indicates that climate change should be apparent already, but in most places climate trends are too small to stand out above year-to-year variability. The climate index is strongly correlated with global surface temperature, which has increased as rapidly as projected by climate models in the 1980s. We argue that the global area with obvious climate change will increase notably in the next few years. But we show that the growth rate of greenhouse gas climate forcing has declined in recent years, and thus there is an opportunity to keep climate change in the 21st century less than “business-as-usual” scenarios.

Climate change is affecting altitudinal migrants and hibernating species

Calendar date of the beginning of the growing season at high altitude in the Colorado Rocky Mountains is variable but has not changed significantly over the past 25 years. This result differs from growing evidence from low altitudes that climate change is resulting in a longer growing season, earlier migrations, and earlier reproduction in a variety of taxa. At our study site, the beginning of the growing season is controlled by melting of the previous winter's snowpack. Despite a trend for warmer spring temperatures the average date of snowmelt has not changed, perhaps because of the trend for increased winter precipitation. This disjunction between phenology at low and high altitudes may create problems for species, such as many birds, that migrate over altitudinal gradients. We present data indicating that this already may be true for American robins, which are arriving 14 days earlier than they did in 1981; the interval between arrival date and the first date of bare ground has grown by 18 days. We also report evidence for an effect of climate change on hibernation behavior; yellow-bellied marmots are emerging 38 days earlier than 23 years ago, apparently in response to warmer spring air temperatures. Migrants and hibernators may experience problems as a consequence of these changes in phenology, which may be exacerbated if climate models are correct in their predictions of increased winter snowfall in our study area. The trends we report for earlier formation of permanent snowpack and for a longer period of snow cover also have implications for hibernating species.

Airborne minerals and related aerosol particles: Effects on climate and the environment

Aerosol particles are ubiquitous in the troposphere and exert an important influence on global climate and the environment. They affect climate through scattering, transmission, and absorption of radiation as well as by acting as nuclei for cloud formation. A significant fraction of the aerosol particle burden consists of minerals, and most of the remainder— whether natural or anthropogenic—consists of materials that can be studied by the same methods as are used for fine-grained minerals. Our emphasis is on the study and character of the individual particles. Sulfate particles are the main cooling agents among aerosols; we found that in the remote oceanic atmosphere a significant fraction is aggregated with soot, a material that can diminish the cooling effect of sulfate. Our results suggest oxidization of SO2 may have occurred on soot surfaces, implying that even in the remote marine troposphere soot provided nuclei for heterogeneous sulfate formation. Sea salt is the dominant aerosol species (by mass) above the oceans. In addition to being important light scatterers and contributors to cloud condensation nuclei, sea-salt particles also provide large surface areas for heterogeneous atmospheric reactions. Minerals comprise the dominant mass fraction of the atmospheric aerosol burden. As all geologists know, they are a highly heterogeneous mixture. However, among atmospheric scientists they are commonly treated as a fairly uniform group, and one whose interaction with radiation is widely assumed to be unpredictable. Given their abundances, large total surface areas, and reactivities, their role in influencing climate will require increased attention as climate models are refined.

Results of Heinrich event 1 simulation from the University of Victoria Earth System-Climate Model (UVic ESCM) and the Community Climate System Model (CCSM3)

We investigated changes in tropical climate and vegetation cover associated with abrupt climate change during Heinrich Event 1 (HE1, ca. 17.5 ka BP) using two different global climate models: the University of Victoria Earth System-Climate Model (UVic ESCM) and the Community Climate System Model version 3 (CCSM3). Tropical South American and African pollen records suggest that the cooling of the North Atlantic Ocean during HE1 influenced the tropics through a southward shift of the rain belt. In this study, we simulated the HE1 by applying a freshwater perturbation to the North Atlantic Ocean. The resulting slowdown of the Atlantic Meridional Overturning Circulation was followed by a temperature seesaw between the Northern and Southern Hemispheres, as well as a southward shift of the tropical rain belt. The shift and the response pattern of the tropical vegetation around the Atlantic Ocean were more pronounced in the CCSM3 than in the UVic ESCM simulation. For tropical South America, opposite changes in tree and grass cover were modeled around 10° S in the CCSM3 but not in the UVic ESCM. In tropical Africa, the grass cover increased and the tree cover decreased around 15° N in the UVic ESCM and around 10° N in the CCSM3. In the CCSM3 model, the tree and grass cover in tropical Southeast Asia responded to the abrupt climate change during the HE1, which could not be found in the UVic ESCM. The biome distributions derived from both models corroborate findings from pollen records in southwestern and equatorial western Africa as well as northeastern Brazil.

Modeling the Impacts of Climate Change on Phytogeographical Units. A Case Study of the Moesz Line

Regional climate models (RCMs) provide reliable climatic predictions for the next 90 years with high horizontal and temporal resolution. In the 21st century northward latitudinal and upward altitudinal shift of the distribution of plant species and phytogeographical units is expected. It is discussed how the modeling of phytogeographical unit can be reduced to modeling plant distributions. Predicted shift of the Moesz line is studied as case study (with three different modeling approaches) using 36 parameters of REMO regional climate data-set, ArcGIS geographic information software, and periods of 1961-1990 (reference period), 2011-2040, and 2041-2070. The disadvantages of this relatively simple climate envelope modeling (CEM) approach are then discussed and several ways of model improvement are suggested. Some statistical and artificial intelligence (AI) methods (logistic regression, cluster analysis and other clustering methods, decision tree, evolutionary algorithm, artificial neural network) are able to provide development of the model. Among them artificial neural networks (ANN) seems to be the most suitable algorithm for this purpose, which provides a black box method for distribution modeling.

Changing visual value of deciduous species in the climate change

The article deals with the changing visual value of deciduous species. Due to climate change, the climatic patterns found on the plants’ growing area may change. Therefore, foliage of deciduous trees changes itscolor in the fall season witha different timing and intensity. This shift can modify the functional, ornamental and ecological value of these plants in the fall season, which is of special interest in the context of landscape design. However, this effect of climate change hasn’t been examined in terms of landscape architecture yet.In the article we are looking for deciduous species that can be appropriate subjectsforresearch, we are giving suggestions for choosing the right location for a future research and proposing available resources of satellite images, that can provide the basis for evaluation of leaf coloring. We also review already existing methods for calculating the degree of fall leaf coloring.We propose a novel method of satellite image processing to evaluate the coloring of a stand. Leaf Coloring Index (LCI) shows the leaf color’s relation to the color realms. LCI is appropriate for setting up a phenological model based onclimate data in a future research. Based on future climate models, the change of the examined stand’s visual value can be predicted. The results might affect the future use of plant species in landscape architecture.

Climate forecast data (Nino3.4 SST, Arctic sea ice extent) and observational references, link to files in Rdata format

This data set contains seasonal forecasts of sea surface temperature and Arctic sea ice extent from state-of-the-art climate models, along with observational references used to evaluate those forecasts. Common skill scores like the correlation between modelled and observed time series are also reported.

Surface wind stress modeled for the Panama Seaway with the Community Climate System Model 3

The early Pliocene warm phase was characterized by high sea surface temperatures and a deep thermocline in the eastern equatorial Pacific. A new hypothesis suggests that the progressive closure of the Panamanian seaway contributed substantially to the termination of this zonally symmetric state in the equatorial Pacific. According to this hypothesis, intensification of the Atlantic meridional overturning circulation (AMOC) - induced by the closure of the gateway - was the principal cause of equatorial Pacific thermocline shoaling during the Pliocene. In this study, twelve Panama seaway sensitivity experiments from eight ocean/climate models of different complexity are analyzed to examine the effect of an open gateway on AMOC strength and thermocline depth. All models show an eastward Panamanian net throughflow, leading to a reduction in AMOC strength compared to the corresponding closed-Panama case. In those models that do not include a dynamic atmosphere, deepening of the equatorial Pacific thermocline appears to scale almost linearly with the throughflow-induced reduction in AMOC strength. Models with dynamic atmosphere do not follow this simple relation. There are indications that in four out of five models equatorial wind-stress anomalies amplify the tropical Pacific thermocline deepening. In summary, the models provide strong support for the hypothesized relationship between Panama closure and equatorial Pacific thermocline shoaling.

Climate change and the long-term viability of the World’s busiest heavy haul ice road

Climate models project that the northern high latitudes will warm at a rate in excess of the global mean. This will pose severe problems for Arctic and sub-Arctic infrastructure dependent on maintaining low temperatures for structural integrity. This is the case for the economically important Tibbitt to Contwoyto Winter Road (TCWR)—the world’s busiest heavy haul ice road, spanning 400 km across mostly frozen lakes within the Northwest Territories of Canada. In this study, future climate scenarios are developed for the region using statistical downscaling methods. In addition, changes in lake ice thickness are projected based on historical relationships between measured ice thickness and air temperatures. These projections are used to infer the theoretical operational dates of the TCWR based on weight limits for trucks on the ice. Results across three climate models driven by four RCPs reveal a considerable warming trend over the coming decades. Projected changes in ice thickness reveal a trend towards thinner lake ice and a reduced time window when lake ice is at sufficient thickness to support trucks on the ice road, driven by increasing future temperatures. Given the uncertainties inherent in climate modelling and the resultant projections, caution should be exercised in interpreting the magnitude of these scenarios. More certain is the direction of change, with a clear trend towards winter warming that will reduce the operation time window of the TCWR. This illustrates the need for planners and policymakers to consider future changes in climate when planning annual haulage along the TCWR.

Transient simulations for present and last interglacials using a comprehensive coupled climate model CCSM3 (Community Climate System Model 3.0), links to model result files in NetCDF format

Transient simulations are widely used in studying the past climate as they provide better comparison with any exisiting proxy data. However, multi-millennial transient simulations using coupled climate models are usually computationally very expensive. As a result several acceleration techniques are implemented when using numerical simulations to recreate past climate. In this study, we compare the results from transient simulations of the present and the last interglacial with and without acceleration of the orbital forcing, using the comprehensive coupled climate model CCSM3 (Community Climate System Model 3). Our study shows that in low-latitude regions, the simulation of long-term variations in interglacial surface climate is not significantly affected by the use of the acceleration technique (with an acceleration factor of 10) and hence, large-scale model-data comparison of surface variables is not hampered. However, in high-latitude regions where the surface climate has a direct connection to the deep ocean, e.g. in the Southern Ocean or the Nordic Seas, acceleration-induced biases in sea-surface temperature evolution may occur with potential influence on the dynamics of the overlying atmosphere. The data provided here are from both accelerated and non-accelerated runs as decadal mean values.

Characterizing, modelling and understanding the climate variability of the deep water formation in the North-Western Mediterranean Sea

Observing, modelling and understanding the climate-scale variability of the deep water formation (DWF) in the North-Western Mediterranean Sea remains today very challenging. In this study, we first characterize the interannual variability of this phenomenon by a thorough reanalysis of observations in order to establish reference time series. These quantitative indicators include 31 observed years for the yearly maximum mixed layer depth over the period 1980–2013 and a detailed multi-indicator description of the period 2007–2013. Then a 1980–2013 hindcast simulation is performed with a fully-coupled regional climate system model including the high-resolution representation of the regional atmosphere, ocean, land-surface and rivers. The simulation reproduces quantitatively well the mean behaviour and the large interannual variability of the DWF phenomenon. The model shows convection deeper than 1000 m in 2/3 of the modelled winters, a mean DWF rate equal to 0.35 Sv with maximum values of 1.7 (resp. 1.6) Sv in 2013 (resp. 2005). Using the model results, the winter-integrated buoyancy loss over the Gulf of Lions is identified as the primary driving factor of the DWF interannual variability and explains, alone, around 50 % of its variance. It is itself explained by the occurrence of few stormy days during winter. At daily scale, the Atlantic ridge weather regime is identified as favourable to strong buoyancy losses and therefore DWF, whereas the positive phase of the North Atlantic oscillation is unfavourable. The driving role of the vertical stratification in autumn, a measure of the water column inhibition to mixing, has also been analyzed. Combining both driving factors allows to explain more than 70 % of the interannual variance of the phenomenon and in particular the occurrence of the five strongest convective years of the model (1981, 1999, 2005, 2009, 2013). The model simulates qualitatively well the trends in the deep waters (warming, saltening, increase in the dense water volume, increase in the bottom water density) despite an underestimation of the salinity and density trends. These deep trends come from a heat and salt accumulation during the 1980s and the 1990s in the surface and intermediate layers of the Gulf of Lions before being transferred stepwise towards the deep layers when very convective years occur in 1999 and later. The salinity increase in the near Atlantic Ocean surface layers seems to be the external forcing that finally leads to these deep trends. In the future, our results may allow to better understand the behaviour of the DWF phenomenon in Mediterranean Sea simulations in hindcast, forecast, reanalysis or future climate change scenario modes. The robustness of the obtained results must be however confirmed in multi-model studies.

Climate variability of the last 1000 years in the NW Pacific: high resolution, multi-biomarker records from Lake Toyoni

The East Asian Monsoon (EAM) is an active component of the global climate system and has a profound social and economic impact in East Asia and its surrounding countries. Its impact on regional hydrological processes may influence society through industrial water supplies, food productivity and energy use. In order to predict future rates of climate change, reliable and accurate reconstructions of regional temperature and rainfall are required from all over the world to test climate models and better predict future climate variability. Hokkaido is a region which has limited palaeo-climate data and is sensitive to climate change. Instrumental data show that the climate in Hokkaido is influenced by the East Asian Monsoon (EAM), however, instrumental data is limited to the past ~150 years. Therefore down-core climate reconstructions, prior to instrumental records, are required to provide a better understanding of the long-term behaviour of the climate drivers (e.g. the EAM, Westerlies, and teleconnections) in this region. The present study develops multi-proxy reconstructions to determine past climatic and hydrologic variability in Japan over the past 1000 years and aid in understanding the effects of the EAM and the Westerlies independently and interactively. A 250-cm long sediment core from Lake Toyoni, Hokkaido was retrieved to investigate terrestrial and aquatic input, lake temperature and hydrological changes over the past 1000-years within Lake Toyoni and its catchment using X-Ray Fluorescence (XRF) data, alkenone palaeothermometry, the molecular and hydrogen isotopic composition of higher plant waxes (δD(HPW)). Here, we conducted the first survey for alkenone biomarkers in eight lakes in the Hokkaido, Japan. We detected the occurrence of alkenones within the sediments of Lake Toyoni. We present the first lacustrine alkenone record from Japan, including genetic analysis of the alkenone producer. C37 alkenone concentrations in surface sediments are 18µg C37 g−1 of dry sediment and the dominant alkenone is C37:4. 18S rDNA analysis revealed the presence of a single alkenone producer in Lake Toyoni and thus a single calibration is used for reconstructing lake temperature based on alkenone unsaturation patterns. Temperature reconstructions over the past 1000 years suggest that lake water temperatures varies between 8 and 19°C which is in line with water temperature changes observed in the modern Lake Toyoni. The alkenone-based temperature reconstruction provides evidence for the variability of the EAM over the past 1000 years. The δD(HPW) suggest that the large fluctuations (∼40‰) represent changes in temperature and source precipitation in this region, which is ultimately controlled by the EAM system and therefore a proxy for the EAM system. In order to complement the biomarker reconstructions, the XRF data strengthen the lake temperature and hydrological reconstructions by providing information on past productivity, which is controlled by the East Asian Summer monsoon (EASM) and wind input into Lake Toyoni, which is controlled by the East Asian Winter Monsoon (EAWM) and the Westerlies. By combining the data generated from XRF, alkenone palaeothermometry and the δD(HPW) reconstructions, we provide valuable information on the EAM and the Westerlies, including; the timing of intensification and weakening, the teleconnections influencing them and the relationship between them. During the Medieval Warm Period (MWP), we find that the EASM dominated and the EAWM was suppressed, whereas, during the Little Ice Age (LIA), the influence of the EAWM dominated with time periods of increased EASM and Westerlies intensification. The El Niño Southern Oscillation (ENSO) significantly influenced the EAM; a strong EASM occurred during El Niño conditions and a strong EAWM occurred during La Niña. The North Atlantic Oscillation, on the other hand, was a key driver of the Westerlies intensification; strengthening of the Westerlies during a positive NAO phase and weakening of the Westerlies during a negative NAO phase. A key finding from this study is that our data support an anti-phase relationship between the EASM and the EAWM (e.g. the intensification of the EASM and weakening of the EAWM and vice versa) and that the EAWM and the Westerlies vary independently from each other, rather than coincide as previously suggested in other studies.

The Impacts of Climate Change on Irrigated Agriculture in Southern Portugal

Climate change projections point to increasing air temperature and reduced precipitation in southern Portugal, which would affect farming systems. This study aims to assess the impacts of climate change on irrigated agriculture in southern Portugal. These impacts were assessed by combining climate model data with a soil water balance model and a numerical model for the design of irrigation systems. Meteorological data from two weather stations were used along with three climate models (HadRM3P, HIRHAMh and HIRHAMhh; 2071–2100). The crop rotations studied included sugar beet–maize–tomato–wheat and sunflower–wheat–barley. Two adaptation measures were considered: (i) maintaining the current crop varieties; (ii) using new crop varieties. The results from the considered climate change scenarios indicated that the impacts of climate change on irrigation requirements depend on the adopted adaptation measures. On average, the seasonal irrigation requirements increased by 13–70% when new crop varieties were used and by −13 to 7% when the current crop varieties were maintained. The impacts of climate change on irrigation system design were considerable, with the design flow rate increasing by 5–24%.

Evolution and challenges of dynamic global vegetation models for some aspects of plant physiology and elevated atmospheric CO2.

Dynamic global vegetation models (DGVMs) simulate surface processes such as the transfer of energy, water, CO2, and momentum between the terrestrial surface and the atmosphere, biogeochemical cycles, carbon assimilation by vegetation, phenology, and land use change in scenarios of varying atmospheric CO2 concentrations. DGVMs increase the complexity and the Earth system representation when they are coupled with atmospheric global circulation models (AGCMs) or climate models. However, plant physiological processes are still a major source of uncertainty in DGVMs. The maximum velocity of carboxylation (Vcmax), for example, has a direct impact over productivity in the models. This parameter is often underestimated or imprecisely defined for the various plant functional types (PFTs) and ecosystems. Vcmax is directly related to photosynthesis acclimation (loss of response to elevated CO2), a widely known phenomenon that usually occurs when plants are subjected to elevated atmospheric CO2 and might affect productivity estimation in DGVMs. Despite this, current models have improved substantially, compared to earlier models which had a rudimentary and very simple representation of vegetation?atmosphere interactions. In this paper, we describe this evolution through generations of models and the main events that contributed to their improvements until the current state-of-the-art class of models. Also, we describe some main challenges for further improvements to DGVMs.

Observational Characterization of the Downward Atmospheric Longwave Radiation at the Surface in the City of Sao Paulo

This work describes the seasonal and diurnal variations of downward longwave atmospheric irradiance (LW) at the surface in Sao Paulo, Brazil, using 5-min-averaged values of LW, air temperature, relative humidity, and solar radiation observed continuously and simultaneously from 1997 to 2006 on a micrometeorological platform, located at the top of a 4-story building. An objective procedure, including 2-step filtering and dome emission effect correction, was used to evaluate the quality of the 9-yr-long LW dataset. The comparison between LW values observed and yielded by the Surface Radiation Budget project shows spatial and temporal agreement, indicating that monthly and annual average values of LW observed in one point of Sao Paulo can be used as representative of the entire metropolitan region of Sao Paulo. The maximum monthly averaged value of the LW is observed during summer (389 +/- 14 W m(-2): January), and the minimum is observed during winter (332 +/- 12 W m(-2); July). The effective emissivity follows the LW and shows a maximum in summer (0.907 +/- 0.032; January) and a minimum in winter (0.818 +/- 0.029; June). The mean cloud effect, identified objectively by comparing the monthly averaged values of the LW during clear-sky days and all-sky conditions, intensified the monthly average LW by about 32.0 +/- 3.5 W m(-2) and the atmospheric effective emissivity by about 0.088 +/- 0.024. In August, the driest month of the year in Sao Paulo, the diurnal evolution of the LW shows a minimum (325 +/- 11 W m(-2)) at 0900 LT and a maximum (345 12 W m-2) at 1800 LT, which lags behind (by 4 h) the maximum diurnal variation of the screen temperature. The diurnal evolution of effective emissivity shows a minimum (0.781 +/- 0.027) during daytime and a maximum (0.842 +/- 0.030) during nighttime. The diurnal evolution of all-sky condition and clear-sky day differences in the effective emissivity remain relatively constant (7% +/- 1%), indicating that clouds do not change the emissivity diurnal pattern. The relationship between effective emissivity and screen air temperature and between effective emissivity and water vapor is complex. During the night, when the planetary boundary layer is shallower, the effective emissivity can be estimated by screen parameters. During the day, the relationship between effective emissivity and screen parameters varies from place to place and depends on the planetary boundary layer process. Because the empirical expressions do not contain enough information about the diurnal variation of the vertical stratification of air temperature and moisture in Sao Paulo, they are likely to fail in reproducing the diurnal variation of the surface emissivity. The most accurate way to estimate the LW for clear-sky conditions in Sao Paulo is to use an expression derived from a purely empirical approach.