Understanding public complacency about climate change: adults’ mental models of climate change violate conservation of matter

Public attitudes about climate change reveal a contradiction. Surveys show most Americans believe climate change poses serious risks but also that reductions in greenhouse gas (GHG) emissions sufficient to stabilize atmospheric GHG concentrations can be deferred until there is greater evidence that climate change is harmful. US policymakers likewise argue it is prudent to wait and see whether climate change will cause substantial economic harm before undertaking policies to reduce emissions. Such wait-and-see policies erroneously presume climate change can be reversed quickly should harm become evident, underestimating substantial delays in the climate’s response to anthropogenic forcing. We report experiments with highly educated adults – graduate students at MIT – showing widespread misunderstanding of the fundamental stock and flow relationships, including mass balance principles, that lead to long response delays. GHG emissions are now about twice the rate of GHG removal from the atmosphere. GHG concentrations will therefore continue to rise even if emissions fall, stabilizing only when emissions equal removal. In contrast, most subjects believe atmospheric GHG concentrations can be stabilized while emissions into the atmosphere continuously exceed the removal of GHGs from it. These beliefs – analogous to arguing a bathtub filled faster than it drains will never overflow – support wait-and-see policies but violate conservation of matter. Low public support for mitigation policies may arise from misconceptions of climate dynamics rather than high discount rates or uncertainty about the impact of climate change. Implications for education and communication between scientists and nonscientists (the public and policymakers) are discussed.     

Adaptation of agriculture to warming in Northeast China

Northeast China comprises Heilongjiang, Jilin and Liaoning Provinces, with a total area of 790,000 km² and a population of about 107 million. Northeast China, located at relatively high latitudes, (from about 39 to 53°N), is one of the coolest regions in China with long and cold winters, a short growth season and frequent cold extreme events, which are adverse to agricultural production. However, since the 1980s, Northeast China has experienced significant warming with annual mean temperature rising by 1.0–2.5°C. The increase of accumulated temperature, the extension of the growth period and the recession of summer cool disasters all contributed to improved conditions for crop growth and led to a northward movement of the agricultural climate zone. In addition, the adaptation to warming including the adjustment of crop composition and structure as well as the adoption of advanced technologies greatly facilitated agricultural development. As a result, total grain production in the region increased rapidly. This paper describes in detail climate change, adaptation measures and final agricultural outcomes, alongside with economic and political factors and the role of different political actors in Northeast China.     

Carbon cycle–climate feedback sensitivity to parameter changes of a zero-dimensional terrestrial carbon cycle scheme in a climate model of intermediate complexity

Summary A series of sensitivity runs have been performed with a coupled climate–carbon cycle model. The climatic component consists of the climate model of intermediate complexity IAP RAS CM. The carbon cycle component is formulated as a simple zero-dimensional model. Its terrestrial part includes gross photosynthesis, and plant and soil respirations, depending on temperature via Q ₁₀-relationships (Lenton, 2000). Oceanic uptake of anthropogenic carbon is formulated is a bi-linear function of tendencies of atmospheric concentration of CO₂ and globally averaged annual mean sea surface temperature. The model is forced by the historical industrial and land use emissions of carbon dioxide for the second half of the 19th and the whole of the 20th centuries, and by the emission scenario SRES A2 for the 21st century. For the standard set of the governing parameters, the model realistically captures the main features of the Earth’s observed carbon cycle. A large number of simulations have been performed, perturbing the governing parameters of the terrestrial carbon cycle model. In addition, the climate part is perturbed, either by zeroing or artificially increasing the climate model sensitivity to the doubling of the atmospheric CO₂ concentration. Performing the above mentioned perturbations, it is possible to mimic most of the range found in the C4MIP simulations. In this way, a wide range of the climate–carbon cycle feedback strengths is obtained, differing even in the sign of the feedback. If the performed simulations are subjected to the constraints of a maximum allowed deviation of the simulated atmospheric CO₂ concentration (pCO_2(a)) from the observed values and correspondence between simulated and observed terrestrial uptakes, it is possible to narrow the corresponding uncertainty range. Among these constraints, considering pCO_2(a) and uptakes are both important. However, the terrestrial uptakes constrain the simulations more effectively than the oceanic ones. These constraints, while useful, are still unable to rule out both extremely strong positive and modest negative climate–carbon cycle feedback.     

Spring Phenophases in Recent Decades Over Eastern China and Its Possible Link to Climate Changes

In light of the observed climate changes in recent decades over eastern China, we studied the changes in spring phenophases of woody plants observed at 16-stations during 1963–1996, and explored the possible link between the spring phenophases changes and climate changes before the phenophase onset. It is found that, in the region north of 33^∘N (including Northeast, North China and the lower reaches of the Huaihe River), the phenophase advanced 1.1–4.3 days per decade for early spring and 1.4–5.4 days per decade for late spring, but in the eastern part of the southwest China it was dealyed by 2.9–6.9 days per decade in early spring and 2.4–6.2 days per decade in late spring. One outstanding feature is identified in Guangzhou in south China, where significant advance of 7.5 days per decade in early spring and delay of 4.6 days per decade in late spring were detected. Statistically siginficant correlation was found between the changes of spring phenophase and the temperatures of one or several months before the phenophase onset. The relationship between the trend of phenophase change and temperature change was highly non-linear (more sensitivity to cooling than to warming) and reached an asymptote 0.5^∘C per decade, which may have implication in the responses of the ecosystem in a future global warming scenario. In addition, we also examined the link between the spring phenophase, and length and mean temperature of the growing season, and the analyses suggested that they were highly correlated as well.     

Spatial-temporal characteristics of temperature variation in China

Summary Spatial-temporal characteristics of temperature variations were analyzed from China daily temperature based on 486 stations during the period 1960–2000. The method of hierarchical cluster analysis was used to divide the territory into sub-regional areas with a coherent evolution, both annually and seasonally. Areas numbering 7–9 are chosen to describe the regional features of air temperature in mainland China. All regions in mainland China experienced increasing trends of annual mean temperature. The trend of increasing temperature was about 0.2–0.3 °C/10 yr in northern China and less than 0.1 °C/10 yr in southern China. In the winter season, the increasing trend of temperature was about 0.5–0.7 °C/10 yr in northern China and about 0.2–0.3 °C/10 yr in southern China. The increasing trend of autumn temperature was mainly located in northwestern China and southwestern China including the Tibetan Plateau. In spring, the rising trend of temperature was concentrated in Northeast China and North China while there was a declining temperature trend of −0.13 °C/10 yr in the upper Yangtze River. In summer, the declining trend of temperature was only concentrated in the mid-low valley of the Yangtze and Yellow Rivers while surrounding this valley there were increasing trends in South China, Southwest China, Northwest China, and Northeast China. Rapid changes in temperature in various regions were detected by the multiple timescale t-test method. The year 1969 was a rapid change point from a high temperature to a low temperature along the Yangtze River and South China. In the years 1977–1979, temperature significantly increased from a lower level to a higher level in many places except for regions in North China and the Yangtze River. Another rapid increasing temperature trend was observed in 1987. In the years 1976–1979, a positive rapid change of summer temperature occurred in northwestern China and southwestern China while a decreasing temperature was found between the Yellow River and the Yangtze River. A rapid increase of winter temperature was found for 1977–1979 and 1985–1986 in many places. There were increasing events of extreme temperature in broad areas except in the north part of Northeast China and the north part of the Xinjiang region. In winter, increasing temperature of the climate state and weakening temperature extremes are observed in northern China. In summer, both increasing temperature of the climate state and enhancing temperature extremes were commonly exhibited in northern China. Present address: Linfen Meteorological Office, Linfen 041000, Shanxi Province, China.     

The impact of local temperature volatility on attention to climate change: Evidence from Spanish tweets

Variability in local weather patterns has long been suggested as a major barrier impeding laypeople from recognizing long-term climate trends. However, as humans are able to detect and interpret rapid signal fluctuations, it seems psychologically plausible to assume that they are able to integrate short-term variations of weather variables into their mental representations of climate change. Using a combined analysis of social media and weather station data, here we investigated the impact of the short-term volatility of local temperature on climate change-related tweets from 2014 to 2017. We found a nonlinear hockey stick relationship between weekly temperature volatility and climate change-related tweets, a volatility rise of 1 °C corresponds to an 82% increase in climate change tweets when volatility is above 3.5 °C. This volatility effect was observed from 2016 onwards, suggesting a recent change in people’s mental representations of climate change. This study provides empirical evidence illustrating that in the public mind, climate change may not be represented as a mere temperature increase any more, but as a disruption of the climate system in general.     

Will the tropical land biosphere dominate the climate–carbon cycle feedback during the twenty-first century?

Global warming caused by anthropogenic CO₂ emissions is expected to reduce the capability of the ocean and the land biosphere to take up carbon. This will enlarge the fraction of the CO₂ emissions remaining in the atmosphere, which in turn will reinforce future climate change. Recent model studies agree in the existence of such a positive climate–carbon cycle feedback, but the estimates of its amplitude differ by an order of magnitude, which considerably increases the uncertainty in future climate projections. Therefore we discuss, in how far a particular process or component of the carbon cycle can be identified, that potentially contributes most to the positive feedback. The discussion is based on simulations with a carbon cycle model, which is embedded in the atmosphere/ocean general circulation model ECHAM5/MPI-OM. Two simulations covering the period 1860–2100 are conducted to determine the impact of global warming on the carbon cycle. Forced by historical and future carbon dioxide emissions (following the scenario A2 of the Intergovernmental Panel on Climate Change), they reveal a noticeable positive climate–carbon cycle feedback, which is mainly driven by the tropical land biosphere. The oceans contribute much less to the positive feedback and the temperate/boreal terrestrial biosphere induces a minor negative feedback. The contrasting behavior of the tropical and temperate/boreal land biosphere is mostly attributed to opposite trends in their net primary productivity (NPP) under global warming conditions. As these findings depend on the model employed they are compared with results derived from other climate–carbon cycle models, which participated in the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP).

Climatic Change, Wars and Dynastic Cycles in China Over the Last Millennium

In recent years, the phenomenon of global warming and its implications for the future of the human race have been intensively studied. In contrast, few quantitative studies have been attempted on the notable effects of past climatic changes upon human societies. This study explored the relationship between climatic change and war in China by comparing high-resolution paleo-climatic reconstructions with known war incidences in China in the last millennium. War frequencies showed a cyclic pattern that closely followed the global paleo-temperature changes. Strong and significant correlations were found between climatic change, war occurrence, harvest level, population size and dynastic transition. During cold phases, China suffered more often from frequent wars, population decline and dynastic changes. The quantitative analyses suggested that the reduction of thermal energy input during a cold phase would lower the land carrying capacity in the traditional agrarian society, and the population size, with significant accretions accrued in the previous warm phase, could not be sustained by the shrinking resource base. The stressed human-nature relationship generated a ‘push force’, leading to more frequent wars between states, regions and tribes, which could lead to the collapse of dynasties and collapses of human population size. War frequencies varied according to geographical locations (North, Central and South China) due to spatial variations in the physical environment and hence differential response to climatic change. Moreover, war occurrences demonstrated an obvious time lag after an episode of temperature fall, and the three geographical regions experienced different length of time lags. This research also shows that human population increases and collapses were correlated with the climatic phases and the social instabilities that were induced by climate changes during the last millennium. The findings proposed a new interpretation of human-nature relationship in the past, with implications for the impacts of anomalous global warming on future human conflicts.     

A comparison of explicit and implicit spatial downscaling of GCM output for soil erosion and crop production assessments

Spatial downscaling of climate change scenarios can be a significant source of uncertainty in simulating climatic impacts on soil erosion, hydrology, and crop production. The objective of this study is to compare responses of simulated soil erosion, surface hydrology, and wheat and maize yields to two (implicit and explicit) spatial downscaling methods used to downscale the A2a, B2a, and GGa1 climate change scenarios projected by the Hadley Centre’s global climate model (HadCM3). The explicit method, in contrast to the implicit method, explicitly considers spatial differences of climate scenarios and variability during downscaling. Monthly projections of precipitation and temperature during 1950–2039 were used in the implicit and explicit spatial downscaling. A stochastic weather generator (CLIGEN) was then used to disaggregate monthly values to daily weather series following the spatial downscaling. The Water Erosion Prediction Project (WEPP) model was run for a wheat–wheat–maize rotation under conventional tillage at the 8.7 and 17.6% slopes in southern Loess Plateau of China. Both explicit and implicit methods projected general increases in annual precipitation and temperature during 2010–2039 at the Changwu station. However, relative climate changes downscaled by the explicit method, as compared to the implicit method, appeared more dynamic or variable. Consequently, the responses to climate change, simulated with the explicit method, seemed more dynamic and sensitive. For a 1% increase in precipitation, percent increases in average annual runoff (soil loss) were 3–6 (4–10) times greater with the explicit method than those with the implicit method. Differences in grain yield were also found between the two methods. These contrasting results between the two methods indicate that spatial downscaling of climate change scenarios can be a significant source of uncertainty, and further underscore the importance of proper spatial treatments of climate change scenarios, and especially climate variability, prior to impact simulation. The implicit method, which applies aggregated climate changes at the GCM grid scale directly to a target station, is more appropriate for simulating a first-order regional response of nature resources to climate change. But for the site-specific impact assessments, especially for entities that are heavily influenced by local conditions such as soil loss and crop yield, the explicit method must be used.     

Climate changes and its impact on tundra ecosystem in Qinghai-Tibet Plateau,China

Alpine ecosystems in permafrost region are extremely sensitive to climate change. The headwater regions of Yangtze River and Yellow River of the Qinghai-Tibet plateau permafrost area were selected. Spatial-temporal shifts in the extent and distribution of tundra ecosystems were investigated for the period 1967–2000 by landscape ecological method and aerial photographs for 1967, and satellite remote sensing data (the Landsat’s TM) for 1986 and 2000. The relationships were analyzed between climate change and the distribution area variation of tundra ecosystems and between the permafrost change and tundra ecosystems. The responding model of tundra ecosystem to the combined effects of climate and permafrost changes was established by using statistic regression method, and the contribution of climate changes and permafrost variation to the degradation of tundra ecosystems was estimated. The regional climate exhibited a tendency towards significant warming and desiccation with the air temperature increased by 0.4–0.67°C/10a and relative stable precipitation over the last 45 years. Owing to the climate continuous warming, the intensity of surface heat source (HI) increased at the average of 0.45 W/m² per year, the difference of surface soil temperature and air temperature (DT) increased at the range of 4.1°C–4.5°C, and the 20-cm depth soil temperature within the active layer increased at the range of 1.1°C–1.4°C. The alpine meadow and alpine swamp meadow were more sensitive to permafrost changes than alpine steppe. The area of alpine swamp meadow decreased by 13.6–28.9%, while the alpine meadow area decreased by 13.5–21.3% from 1967 to 2000. The contributions of climate change to the degradation of the alpine meadow and alpine swamp was 58–68% and 59–65% between 1967 and 2000. The synergic effects of climate change and permafrost variation were the major drivers for the observed degradation in tundra ecosystems of the Qinghai-Tibet plateau.     

On the relationship between winter thunder and the climatic change in China in the past 2200 years

An analysis of winter thunder records in China from 250 B.C. to A.D. 1900 shows that there is a relationship between the pattern of winter thunder frequency fluctuation with that of temperature fluctuation. We hypothesized that such a temperature—thunder relationship may possibly be due to the strong frontal movement by cold air masses of well-defined low temperature.     

Sensitivity of discharge and flood frequency to twenty-first century and late Holocene changes in climate and land use (River Meuse,northwest Europe)

We used a calibrated coupled climate–hydrological model to simulate Meuse discharge over the late Holocene (4000–3000 BP and 1000–2000 AD). We then used this model to simulate discharge in the twenty-first century under SRES emission scenarios A2 and B1, with and without future land use change. Mean discharge and medium-sized high-flow (e.g. Q₉₉) frequency are higher in 1000–2000 AD than in 4000–3000 BP; almost all of this increase can be attributed to the conversion of forest to agriculture. In the twentieth century, mean discharge and the frequency of medium-sized high-flow events are higher than in the nineteenth century; this increase can be attributed to increased (winter half-year) precipitation. Between the twentieth and twenty-first centuries, anthropogenic climate change causes a further increase in discharge and medium-sized high-flow frequency; this increase is of a similar order of magnitude to the changes over the last 4,000 years. The magnitude of extreme flood events (return period 1,250-years) is higher in the twenty-first century than in any preceding period of the time-slices studied. In contrast to the long-term influence of deforestation on mean discharge, changes in forest cover have had little effect on these extreme floods, even on the millennial timescale.     

Tree rings and climate for the last 680 years in Wulan area of northeastern Qinghai-Tibetan Plateau

A 680-year ring-width chronology of Sabina przewalskii Kom. was developed for Wulan area of northeastern Qinghai-Tibetan Plateau, China. Response function and correlation analyses showed that spring precipitation (May–June) is the critical limiting factor for tree-ring growth, and temperature in prior November may also play a role in affecting tree-ring growth. Excessive spring precipitation occurred during AD 1380s–1390s, 1410s–1420s, 1520s–1560s and 1938 to present. Dry springs occurred during AD 1430s–1510s, 1640s–1730s and 1780s–1890s most of which generally coincided with cold intervals of the Little Ice Age (LIA) on the plateau, suggesting that the LIA climate on the northeastern Qinghai-Tibetan Plateau might be characterized by three episodes of dry spring and cold autumn. The relatively driest spring and probably coldest autumn occurred in AD 1710s–1720s, 1787–1797, 1815–1824, 1869–1879 and 1891–1895. The extreme drought in AD 1787–1797 might result from little monsoon precipitation due to the failure of Asian monsoon in this period. The tree-ring data produced in this study contribute to the spatial expansion of proxy climate records for the Qinghai-Tibetan Plateau.     

Interdecadal Change of the Relationship Between the Tropical Indian Ocean Dipole Mode and the Summer Climate Anomaly in China

The interdecadal change of the relationship between the tropical Indian Ocean dipole(IOD) mode and the summer climate anomaly in China is investigated by using monthly precipitation and temperature records at 210 stations in China and the NCEP/NCAR reanalysis data for 1957-2005.The results indicate that along with the interdecadal shift in the large-scale general circulation around the late 1970s,the relationship between the IOD mode and the summer climate anomaly in some regions of China has significantly changed.Before the late 1970s,a developing IOD event is associated with an enhanced East Asian summer monsoon,which tends to decrease summer precipitation and increase summer temperature in South China;while after the late 1970s,it is associated with a weakened East Asian summer monsoon,which tends to increase(decrease) precipitation and decrease(increase) temperature in the south(north) of the Yangtze River.During the next summer,following a positive IOD event,precipitation is increased in most of China before the late 1970s,while it is decreased(increased) south(north) of the Yangtze River after the late 1970s.There is no significant correlation between the IOD and surface air temperature anomaly in most of China in the next summer before the late 1970s;however,the IOD tends to increase the next summer temperature south of the Yellow River after the late 1970s.     

Impact of climate change on low-flows in the river Meuse

In this study observed precipitation, temperature, and discharge records from the Meuse basin for the period 1911–2003 are analysed. The primary aim is to establish which meteorological conditions generate (critical) low-flows of the Meuse. This is achieved by examining the relationships between observed seasonal precipitation and temperature anomalies, and low-flow indices. Secondly, the possible impact of climate change on the (joint) occurrence of these low-flow generating meteorological conditions is addressed. This is based on the outcomes of recently reported RCM climate simulations for Europe given a scenario with increased atmospheric greenhouse-gas concentrations. The observed record (1911–2003) hints at the importance of multi-seasonal droughts in the generation of critical low-flows of the river Meuse. The RCM simulations point to a future with wetter winters and drier summers in Northwest Europe. No increase in the likelihood of multi-seasonal droughts is simulated. However, the RCM scenario runs produce multi-seasonal precipitation and temperature anomalies that are out of the range of the observed record for the period 1911–2003. The impact of climate change on low-flows has also been simulated with a hydrological model. This simulation indicates that climate change will lead to a decrease in the average discharge of the Meuse during the low-flow season. However, the model has difficulties to simulate critical low-flow conditions of the Meuse.     

气溶胶对中国天气、气候和环境影响综述

空气污染、天气和气候与大众生活息息相关,全球变化与可持续发展更是全人类面临的共同挑战。空气污染与气候变化对发展中国家带来的挑战更为显著。中国作为人口最多、发展飞速的国家,面临这两方面的挑战尤为严峻。因此,深入了解空气污染与气候变化的成因和发展机制,摸清两者相互关系对提高人们的生活质量和科学发展方针政策的制定具有指导意义。随着全球变化研究的深入,气溶胶与温室气体作为影响地球气候的两个最重要的人类排放物,在气候变化科学中起着至关重要的作用,气溶胶研究也成为地球科学发展最快的一个分支学科。中国天气、气候的变化特征,如高温增多、寒潮变少、风速减小、大气变稳、小雨减少、大雨增多、雷暴增强、季风减弱等,与空气污染都存在不同程度的联系。本文主要综述气溶胶对我国天气、气候的影响以及与气象因素相关的空气污染问题,侧重于气溶胶与极端天气事件之间包括影响程度和影响机理在内的错综复杂的关系。研究方法涉及星、地、空综合观测资料分析和模式模拟等。观测资料包括长时间历史观测资料、短时段强化观测实验资料、全球卫星资料等。     

Past and future polar amplification of climate change: climate model intercomparisons and ice-core constraints

Climate model simulations available from the PMIP1, PMIP2 and CMIP (IPCC-AR4) intercomparison projects for past and future climate change simulations are examined in terms of polar temperature changes in comparison to global temperature changes and with respect to pre-industrial reference simulations. For the mid-Holocene (MH, 6,000 years ago), the models are forced by changes in the Earth’s orbital parameters. The MH PMIP1 atmosphere-only simulations conducted with sea surface temperatures fixed to modern conditions show no MH consistent response for the poles, whereas the new PMIP2 coupled atmosphere–ocean climate models systematically simulate a significant MH warming both for Greenland (but smaller than ice-core based estimates) and Antarctica (consistent with the range of ice-core based range). In both PMIP1 and PMIP2, the MH annual mean changes in global temperature are negligible, consistent with the MH orbital forcing. The simulated last glacial maximum (LGM, 21,000 years ago) to pre-industrial change in global mean temperature ranges between 3 and 7°C in PMIP1 and PMIP2 model runs, similar to the range of temperature change expected from a quadrupling of atmospheric CO₂ concentrations in the CMIP simulations. Both LGM and future climate simulations are associated with a polar amplification of climate change. The range of glacial polar amplification in Greenland is strongly dependent on the ice sheet elevation changes prescribed to the climate models. All PMIP2 simulations systematically underestimate the reconstructed glacial–interglacial Greenland temperature change, while some of the simulations do capture the reconstructed glacial–interglacial Antarctic temperature change. Uncertainties in the prescribed central ice cap elevation cannot account for the temperature change underestimation by climate models. The variety of climate model sensitivities enables the exploration of the relative changes in polar temperature with respect to changes in global temperatures. Simulated changes of polar temperatures are strongly related to changes in simulated global temperatures for both future and LGM climates, confirming that ice-core-based reconstructions provide quantitative insights on global climate changes. An erratum to this article can be found at     

CHANGE OF CLIMATE AND ITS INFLUENCE ON THE CROPPING SYSTEM IN CHINA

Tne global change of climate and its influence on the cropping system in China have been investigatedin this paper.It is found that the temperature was increased during the last decade and the precipitationdecreased in northern China and increased in southern China during the last 30 years.The sea level hasbeen rising by about 21—26 cm in the coastal areas south of 30°N in China during the last 100 years.The most of results as simulated by the general circulation models(GCMs)show that the temperature increasewould amount to about 2°—4°C in the most parts of China and precipitation and soil moisture might bedecreased in northern China and increased in sourthern China due to doubling of carbon dioxide(CO_2).The effects of doubled CO_2 on growth period and climatic yield capability in China have been estimatedroughly.It is shown that the regions of the growth period in China would be moved northward about fivedegrees latitude and the climatic yield capability might be increased by about 10％ in the most parts of China.     

Observed and projected climate change in Taiwan

Summary This study examined the secular climate change characteristics in Taiwan over the past 100 years and the relationship with the global climate change. Estimates for the likelihood of future climate changes in Taiwan were made based on the projection from the IPCC climate models. In the past 100 years, Taiwan experienced an island-wide warming trend (1.0–1.4 °C/100 years). Both the annual and daily temperature ranges have also increased. The warming in Taiwan is closely connected to a large-scale circulation and SAT fluctuations, such as the “cool ocean warm land” phenomenon. The water vapor pressure has increased significantly and could have resulted in a larger temperature increase in summer. The probability for the occurrence of high temperatures has increased and the result suggests that both the mean and variance in the SAT in Taiwan have changed significantly since the beginning of the 20th century. Although, as a whole, the precipitation in Taiwan has shown a tendency to increase in northern Taiwan and to decrease in southern Taiwan in the past 100 years, it exhibits a more complicated spatial pattern. The changes occur mainly in either the dry or rainy season and result in an enhanced seasonal cycle. The changes in temperature and precipitation are consistent with the weakening of the East Asian monsoon. Under consideration of both the warming effect from greenhouse gases and the cooling effect from aerosols, all projections from climate models indicated a warmer climate near Taiwan in the future. The projected increase in the area-mean temperature near Taiwan ranged from 0.9–2.7 °C relative to the 1961–1990 averaged temperature, when the CO₂ concentration increased to 1.9 times the 1961–1990 level. These simulated temperature increases were statistically significant and can be attributed to the radiative forcing associated with the increased concentration of greenhouse gases and aerosols. The projected changes in precipitation were within the range of natural variability for all five models. There is no evidence supporting the possibility of precipitation changes near Taiwan based on the simulations from five IPCC climate models. Received February 5, 2001 Revised July 30, 2001     

Where are Germany’s gains from Kyoto? Estimating the effects of global warming on agriculture

Motivated by the high abatement costs of the Kyoto Protocol for Germany, this paper is estimating the economic impact of global warming on agriculture in that country. The hedonic approach is used as theoretical background. Stating that land prices are – among others – determined by climatic factors, this approach can consequently be used to value global warming. To avoid a priori restrictions stemming from functional forms, the land price function is modeled as quadratic Box–Cox function that nests a wide range of specifications. In a second step, the estimated results are used to forecast the impact of climate change. The results indicate that German farmers will be winners of climate change in the short run, with maximum gains occurring at a temperature increase of +0.6°C against current levels. In the long run, there may be losses from global warming. However, the net present value from climate change is under the most probable scenarios positive.