Rise In Surface Air Temperature Research Articles

Long-term variations of aerosol optical depth according to satellite data and its effects on radiation and temperature in the Moscow megacity

The rapid development of large megacities, coupled with emission regulations, can lead to long-term variations in aerosol optical depth over urban area which has an impact on radiation and temperature. This study aims to evaluate the radiation effects of aerosol pollution in Moscow and its surrounding areas using MAIAC data obtained from MODIS satellite data for three distinct periods: 2000–2006, 2007–2014, and 2015–2021. A methodology has been developed to incorporate MCD19A2/MODIS data with some additional information from the AERONET Moscow MSU site into the COSMO non-hydrostatic weather forecast model. The aerosol radiative and temperature effects were estimated for cloudless conditions. The highest aerosol optical depth with an average of 0.18 were observed during the 2007–2014 over the newly developed Moscow territory during the active building construction period. In the most recent period, from 2015 to 2021, the mean AOD decreased to 0.1. This reduction resulted in an increase of net shortwave radiation at the bottom of the atmosphere by 15–20 W/m2 and a slight rise in surface air temperature of 0.08 °C compared to 2007–2014. The parameterizations were proposed for net radiation and air temperature at 2 m as a function of aerosol optical depth and solar zenith angle at low surface albedo.

Application of deep learning algorithms to correct bias in CMIP6 simulations of surface air temperature over the Indian monsoon core region

AbstractIndian subcontinent witnessed a rise in surface air temperature (SAT) in recent decades, during the summer months of March, April and May. The monsoon core region (MCR) of India experiences a hot and humid climate, with temperatures typically highest in May and June before the onset of the monsoon. Global climate model (GCM) simulations of SAT are very much essential to understand the future climate of Indian MCR. Biases in GCMs simulations are due to insufficient knowledge of parameterizations and various assumptions that are made to simulate the complex interactions between land, ocean and atmosphere. The objective of this study is to correct the bias in the Coupled Model Intercomparison Project Phase 6 (CMIP6)–GCM simulations of SAT during March, April and May months over MCR for the historical period 1985–2014 and shared socio‐economic pathways (SSPs) SSP2‐4.5 and SSP5‐8.5 for the period 2015–2100. SAT dataset of fifth‐generation reanalysis (ERA5) of the European Centre for Medium‐Range Weather Forecasts (ECMWF) is used as reference dataset to perform bias correction for the historical period. Preliminary investigation of both SAT datasets has shown that there exists considerable warm bias (1.47°C) over the MCR. Bias correction is performed using a one‐dimensional convolutional neural network (CNN‐1D) and a convolutional long short‐term memory network (CNN‐LSTM) deep learning algorithm. The performance of these algorithms is evaluated with the statistical metrics such as root‐mean‐square error (RMSE), normalized root‐mean‐square error, Nash–Sutcliffe efficiency, mean absolute error, percent bias, correlation coefficient and dynamic time warping. RMSE and percent bias were decreased to 0.35°C and 0.8% with CNN‐LSTM algorithm. The CNN‐LSTM algorithm also preserves the year‐to‐year variability of SAT. Hence, CNN‐LSTM algorithm is found to be suitable for the bias correction of GCM simulations of SAT with encouraging results.

Temperature extremes and their future projections in selected Indian cities along with their meteorological subdivisions and temperature homogeneous zones

Various observational and modelling studies indicate rise in surface air temperature and its extremes at several places in the world. With the availability of more data both from observations and models, it is possible to comprehensively examine future projections in order to get meaningful climate information and identify strong climate signals anywhere. This study is focused on rise in surface air temperatures and the associated temperature related extreme events such as warm days & nights and cold days and nights at four city clusters in India such as Delhi, Mumbai, Chennai and Guwahati. Dynamically downscaled future projections at the four selected city clusters are examined using RegCM CORDEX simulations. Further, selected CMIP model projections are used. In this study, uniformity of the trends in the selected indices found in each city are tested against those found in the corresponding Meteorological Sub-Divisions and Temperature Homogeneous Zones. Increase in the surface air minimum and maximum temperatures along with the frequency of occurrence of warm nights at all the four city clusters are the strong signals of climate projection obtained from this study.

New insights into the world's longest series of monthly snowfall (Parma, Northern Italy, 1777–2018)

AbstractThe emergence of decreasing trends in snowfall frequency and snow depth highlights the challenges arising from shifts in snow regimes. In particular, snow‐dependent southern Europe regions may be negatively impacted by such changes. Snow regimes strongly influence the water availability in reservoirs and groundwater. This study presents the world's longest series of monthly snowfall (fresh snow depth, snow days per year, days with snow on the ground) for the Parma Observatory, northern Italy (44°48′N and 10°19′E) between 1777 and 2018. These datasets were collected over the centuries using early rain gauges and recently, SIAP tipping bucket models. Sources of inhomogeneity were identified and analysed through the study of metadata and of nonparametric tests on datasets. Homogenized time series were obtained after correcting the observed snowfall data for the instruments response and localization characteristics, for the observing practices with the help of the standard normal homogeneity tests. The Buishand and the Mann–Kendall tests were further applied to check the correction and detect possible monotonic trends. Over the study period, days per year of snow decreased after the change point detected in 1897, in association with a rise in surface air temperature (including a distinct urban warming trend). In this study high numbers of snowy days per year (hereafter referred as snowfall frequency) and snow depth values during the latest phase of the LIA at Parma are consistent with a cycle of minimum solar activity, suggesting that enhanced, solar‐induced blocking activity dominated, with the arrival into the Mediterranean of large cold air masses developing over Siberia and northern Europe. Over the last century, snow appears to have resonance‐like characteristics as similar trends were observed over the Northern Hemisphere, where the extent of the snow cover has been reported to markedly decline in the transition spring and autumn seasons.

Effect of Climate Change on Cloud Properties Over Arabian Sea and Central India

Global warming is the average temperature of the earth’s surface which has increased over the past century by about 0.6 °C. This rising temperature may vary precipitation patterns, more frequent droughts, rise in sea level and intense storms and can be termed as climate change. To understand uneven precipitation pattern for monsoon dominated region like India, there is a need to study cloud processes at high resolution with the help of cloud microphysical properties. Ocean is the major and primary source of cloud whereas local water bodies and re-evaporated water over land could be secondary source. Paper focuses over ocean (Arabian Sea) as well as over land (central India) to know the effect of global warming on cloud microphysical properties such as cloud effective radius and cloud liquid water content. Warming signal in terms of rise in sea surface temperature (0.1 °C/decade) as well as rise in surface air temperature (0.05 °C/decade) are observed over Arabian Sea and central India respectively. Satellite data show an increasing (0.5 µm/decade) trend in cloud effective radius over Arabian Sea, whereas it decreases (− 0.1 µm/decade) over central India. Increasing trend in temperature and cloud properties is may be due to warming signal. Aerosol concentration over ocean and land further helped to understand cloud processes with cloud microphysical properties. Paper will focus on the effect of warming signal in cloud properties over Arabian Sea and central India. This type of high resolution study may help to understand cloud processes which in turn may help to understand precipitation patterns.

Heat flow and inferred ground surface temperature history at Tynong North, southeastern Australia

ABSTRACTBorehole temperature data have the potential to record historical variations in ground and air surface temperature, yet very few reliable, purpose-drilled, boreholes are available to explore such impacts, particularly in the southern hemisphere. The 400-m deep Tynong-1 borehole, approximately 65 km ESE of Melbourne, Australia, was drilled specifically to determine conductive heat flow and provides a unique dataset for evaluating ground surface temperature history in southeastern Australia. Steady-state conductive heat flow of 87 ± 1 mW m−2 was determined in the deeper borehole sections, with measured temperature profiles clearly demonstrating a progressive divergence of the observed temperature profile from the equilibrium model in the upper ∼150 m of the hole. We applied a Bayesian method employing a reverse jump Markov chain Monte Carlo search algorithm to explore the origins of this variation. Our results indicate a 2°C increase in ground surface temperature since 1800, after at least 500 years of relatively stable ground surface temperature. The inversion results are consistent with the trend of surface air temperature recorded in southeast Victoria by historical meteorological data since 1950. The inferred increase in ground surface temperature evident prior to 1950 is likely a cumulative effect of land clearing and a rise in surface air temperature.

Impact of urban land-use change in eastern China on the East Asian subtropical monsoon: A numerical study

The effect of urban land-use change in eastern China on the East Asian subtropical monsoon (EASTM) is investigated by using the Community Atmosphere Model version 5.1. Comparison of the results between the urban expansion and reference experiments shows that with the urban expansion, the land surface energy balance alters: surface net radiation and sensible heat fluxes enhance while the latent heat fluxes reduce. As a result, a significant increase in surface air temperature over eastern China is detected. The urban land-use change contributes to a change in the zonal land-sea temperature difference (LSTD), leading to a delay in the time when LSTD changes from positive to negative, and vice versa. Additionally, the onset and retreat dates of the EASTM are also delayed. Meanwhile, the rise in surface air temperature leads to formation of abnormal northerly air flows, which may be the reason for the slower northward movement of the EASTM and a more southward location of its northern boundary.

Economic losses from US hurricanes consistent with an influence from climate change

Warming of the climate system and its impacts on biophysical and human systems have been widely documented. The frequency and intensity of extreme weather events have also changed, but the observed increases in natural disaster losses are often thought to result solely from societal change, such as increases in exposure and vulnerability. Here we analyse the economic losses from tropical cyclones in the United States, using a regression-based approach instead of a standard normalization procedure to changes in exposure and vulnerability, to minimize the chance of introducing a spurious trend. Unlike previous studies, we use statistical models to estimate the contributions of socioeconomic factors to the observed trend in losses and we account for non-normal and nonlinear characteristics of loss data. We identify an upward trend in economic losses between 1900 and 2005 that cannot be explained by commonly used socioeconomic variables. Based on records of geophysical data, we identify an upward trend in both the number and intensity of hurricanes in the North Atlantic basin as well as in the number of loss-generating tropical cyclone records in the United States that is consistent with the smoothed global average rise in surface air temperature. We estimate that, in 2005, US$2 to US$14 billion of the recorded annual losses could be attributable to climate change, 2 to 12% of that year’s normalized losses. We suggest that damages from tropical cyclones cannot be dismissed when evaluating the current and future costs of climate change and the expected benefits of mitigation and adaptation strategies.

PM2.5 and tropospheric O3 in China and an analysis of the impact of pollutant emission control

This study reviewed the status of PM2.5 and tropospheric O3 observations in China (15–55°N, 72–136°E). Initially, the distribution of tropospheric O3 over the globe and China was determined based on satellite observations made during 2010–2013. The annual mean values were 29.78 DU and 33.97 DU over the globe and China, respectively. The distribution of PM2.5 and seasonal changes in concentrations in China were then simulated using an aerosol chemistry–climate coupled model system, with an annual mean value of 0.51 × 10−8 kg m−3. The contributions from five different aerosols to the simulated PM2.5 concentrations in different seasons were also determined. The relationships among the emissions of aerosols, greenhouse gases and their precursors and radiative forcings were determined with reference to the (IPCC AR5) Intergovernmental Panel on Climate Change the Fifth Assessment Report. From these relationships, the possible effects of controlling O3 precursors and (PM) particulate matter on the climate were considered. The influence of the control of O3 precursors was not totally clear, and reducing emissions of short-lived greenhouse gases and black carbon was considered a secondary measure for short-term (the next 50 years) climate-change mitigation. Reducing emissions of CO2 is still the best strategy for meeting the target of a global average rise in surface air temperature of less than 2 °C. Near- and short-term emission reduction strategies are important for both effective environmental protection and climate-change mitigation.

Changes in precipitation intensity over East Asia during the 20th and 21st centuries simulated by a global atmospheric model with a 60 km grid size

We conducted three‐member ensemble simulations using a global atmospheric model with a high horizontal resolution of a 60 km grid size for the period 1872–2099 (228 years). Between 1872 and 2005, the model was forced with observed historical sea surface temperatures (SST), while between 2006 and 2099, the boundary SST data were estimated using the multimodel ensemble of the Coupled Model Intercomparison Project Phase 3 models and assuming A1B emission scenario. Annual mean precipitation (PAVE), the Simple Daily Precipitation Intensity Index (SDII), and the maximum 5 day precipitation total (R5d) averaged over East Asia increase almost monotonically through the 21st century. The statistically significant area of precipitation intensity increase is larger for 2080–2099 than for 2046–2065. In particular, intense rainfall will increase over northern and southern China during 2080–2099. The conversion rate from water vapor to precipitation per 1°C rise in surface air temperature for SDII and R5D is much larger than that for PAVE during the 21st century. This suggests that extreme rainfall events will occur more frequently than moderate rainfall events even if the amount of temperature rise is same. Future changes in the horizontal transport of water vapor also lead to more intense precipitation over East Asia. In particular, the increase in clockwise water vapor transport due to intensification of the subtropical high contributes to increased intense precipitation over southern China.

Detection and quantification of local anthropogenic and regional climatic transient signals in temperature logs from Czechia and Slovenia

The paper reports on detection and quantification of the impact of local anthropogenic structures and regional climatic changes on subsurface temperature field. The analyzed temperature records were obtained by temperature monitoring in a borehole in Prague-Spořilov (Czechia) and by repeated logging of a borehole in Sempeter (Slovenia). The observed data were compared with temperatures yielded by mathematical 3D time-variable geothermal models of the boreholes’ sites with the aim to decompose the observed transient component of the subsurface temperature into the part affected by construction of new buildings and other anthropogenic structures in surroundings of the boreholes and into the part affected by the ground surface temperature warming due to the surface air temperature rise. A direct human impact on the subsurface temperature warming was proved and contributions of individual anthropogenic structures to this change were evaluated. In the case of Spořilov, where the mean annual warming rate reached 0.034°C per year at the depth of 38.3 m during the period 1993–2008, it turned out that about half of the observed warming can be attributed to the air (ground) surface temperature change and half to the human activity on the surface in the immediate vicinity of the borehole. The situation is similar in Sempeter, where the effect of the recently built surface anthropogenic structures is detectable down to the depth of 80 m and the share of the anthropogenic signal on the non-stationary component of the observed subsurface temperature amounts to 30% at the depth of 50 m.

Growth and physiological responses of Chinese cabbage and radish to long-term exposure to elevated carbon dioxide and temperature

Future forecasts for climate change predict the global mean surface air temperature rise by 1–4°C and double current atmospheric CO2 level before the end of 21 century. Increased atmospheric temperature and CO2 concentration are particularly important concerns for agricultural, horticultural and native plant production. In this study, effects of long-term exposure to elevated temperature and carbon dioxide (CO2) on the growth and physiological responses of 3 cultivars of Chinese radish (Raphanus sativus L.) and 3 cultivars of Chinese cabbage (Brassica campestris L.) were examined. In result, the radishes exposed to elevated CO2 for 90 days after sowing (DAS) resulted in little or no change in the root dry weights and the rate of photosynthesis compared with those grown in ambient levels of CO2. In contrast, long-term exposure to elevated CO2 in cabbage had variable effects on the leaf dry weight. As a result of acclimating to the elevated temperature, the radish ‘Chunha’ had a higher rate of photosynthesis, stomatal conductance and internal CO2 concentration than in the control condition. Furthermore, the long-term exposure to a combination condition of elevated temperature and CO2 increased root dry weights of the radishes ‘Cheongdae’ and ‘Chunha’ more than elevated temperature alone. The combination of elevated CO2 and temperature stimulated the growth of roots more than that of shoots in the radish ‘Chunha’, and thus may have led a higher rate of nutrient uptake than other radish cultivars. In contrast, when the cabbage ‘Chun-gwang’ was exposed to a combination of elevated temperature and CO2 for 90 DAS, the leaf dry weight decreased about 3-fold more than that only exposed to elevated CO2 with drastic decreases in stomatal conductance, internal CO2 and photosynthesis rate. When the cabbage ‘Samjin’ was exposed to either elevated temperature alone or both elevated temperature and CO2 for 80 DAS, the decrease in the leaf dry weight was less than that of the other cabbage cultivars. Results indicated that the radish ‘Chunha’ and the cabbage ‘Samjin’ tolerated either elevated temperature alone or combination condition of elevated temperature and CO2 more than other cultivars.

Correlation of green house molecules with global and surface temperature and its effect on environment

A critical analysis has been made on contribution to green house molecules on global warming and surface air temperature rise. The nature of yearly variations of concentrations of green house molecules and global and surface temperature has been presented. Climate change, environmental and economic effects are briefly mentioned. Various diseases caused by global warming are also discussed.

Implications of climate change in sustained agricultural productivity in South Asia

One of the targets of the United Nations ‘Millennium Development Goals’ adopted in 2000 is to cut in half the number of people who are suffering from hunger between 1990 and 2015. However, crop yield growth has slowed down in much of the world because of declining investments in agricultural research, irrigation, and rural infrastructure and increasing water scarcity. New challenges to food security are posed by accelerated climatic change. Considerable uncertainties remain as to when, where and how climate change will affect agricultural production. Even less is known about how climate change might influence other aspects that determine food security, such as accessibility of food for various societal groups and the stability of food supply. This paper presents the likely impacts of thermal and hydrological stresses as a consequence of projected climate change in the future potential agriculture productivity in South Asia based on the crop simulation studies with a view to identify critical climate thresholds for sustained food productivity in the region. The study suggests that, on an aggregate level, there might not be a significant impact of global warming on food production of South Asia in the short term (<2°C; until 2020s), provided water for irrigation is available and agricultural pests could be kept under control. The increasing frequency of droughts and floods would, however, continue to seriously disrupt food supplies on year to year basis. In long term (2050s and beyond), productivity of Kharif crops would decline due to increased climate variability and pest incidence and virulence. Production of Rabi crops is likely to be more seriously threatened in response to 2°C warming. The net cereal production in South Asia is projected to decline at least between 4 and 10% under the most conservative climate change projections (a regional warming of 3°C) by the end of this century. In terms of the reference to UNFCCC Article 2 on dangerous anthropogenic (human-induced) interference with the climate system, the critical threshold for sustained food productivity in South Asia appears to be a rise in surface air temperature of ~2°C and a marginal decline in water availability for irrigation or decrease in rainfall during the cropping season.

Recent air-temperature changes in the Arctic

AbstractA detailed analysis of the spatial and temporal changes in mean seasonal and annual surface air temperature (SAT) in the Arctic is presented mainly for the period 1951–2005. Mean seasonal and annual homogenized and complete series of SAT from up to 35 Arctic stations were used in the analysis. The focus in this paper is on the 11 years 1995–2005, a period which saw dramatic warming in the Arctic (&gt;1˚C for annual values in relation to the 1951–90 mean). An abrupt rise in SAT occurred in the mid-1990s and was most pronounced in autumn and winter (&gt;2˚C). The greatest warming in the period 1995–2005 occurred in the Pacific and Canadian regions (&gt;1˚C), while the lowest was in the Siberian region (0.82˚C). This period has been the warmest since at least the 17th century. In particular, 2005 was an exceptionally warm year (&gt;2˚C in relation to the 1951–90 mean) and was warmer than 1938, the warmest year in the 20th century. The seasonal and annual trends of the areally averaged Arctic SAT for the periods 1936–2005, 1951–2005 and 1976–2005 are positive, with the exception of winter and autumn for the first period. The majority of trends calculated for the last two periods are statistically significant. While there are varying opinions about the forces driving the present warming, it seems likely that the marked rise in SAT in the mid-1990s (mainly from 1994 to 1995) was caused by (i) a set of natural factors, (ii) non-linear effects of greenhouse-gas loading, or (iii) the combined effect of these two groups of factors.

An efficient climate forecasting method using an intermediate complexity Earth System Model and the ensemble Kalman filter

We present the implementation and results of a model tuning and ensemble forecasting experiment using an ensemble Kalman filter for the simultaneous estimation of 12 parameters in a low resolution coupled atmosphere-ocean Earth System Model by tuning it to realistic data sets consisting of Levitus ocean temperature/salinity climatology, and NCEP/NCAR atmospheric temperature/humidity reanalysis data. The resulting ensemble of tuned model states is validated by comparing various diagnostics, such as mass and heat transports, to observational estimates and other model results. We show that this ensemble has a very reasonable climatology, with the 3-D ocean in particular having comparable realism to much more expensive coupled numerical models, at least in respect of these averaged indicators. A simple global warming experiment is performed to investigate the response and predictability of the climate to a change in radiative forcing, due to 100 years of 1% per annum atmospheric CO2 increase. The equilibrium surface air temperature rise for this CO2 increase is 4.2±0.1°C, which is approached on a time scale of 1,000 years. The simple atmosphere in this version of the model is missing several factors which, if included, would substantially increase the uncertainty of this estimate. However, even within this ensemble, there is substantial regional variability due to the possibility of collapse of the North Atlantic thermohaline circulation (THC), which switches off in more than one third of the ensemble members. For these cases, the regional temperature is not only 3–5°C colder than in the warmed worlds where the THC remains switched on, but is also 1–2°C colder than the current climate. Our results, which illustrate how objective probabilistic projections of future climate change can be efficiently generated, indicate a substantial uncertainty in the long-term future of the THC, and therefore the regional climate of western Europe. However, this uncertainty is only apparent in long-term integrations, with the initial transient response being similar across the entire ensemble. Application of this ensemble Kalman filtering technique to more complete climate models would improve the objectivity of probabilistic forecasts and hence should lead to significantly increased understanding of the uncertainty of our future climate.

Mitigating climate change impact on soybean productivity in India: a simulation study

Field experiments with soybean were conducted over a period of 1990–1998 in diverse Indian locations ranging in latitude, longitude, and elevation. These locations provided a wide range of environments for testing and validation of the crop growth (CROPGRO) model considered in this study with observed changes in soils, rainfall and other weather parameters. Model predicted satisfactorily the trends of days to flowering, maturity and grain yields. The deviations of simulated results were within ±15% of the measurements. Validated CROPGRO model has been used to simulate the impact of climate change on soybean production in India. The projected scenarios for the Indian subcontinent as inferred from three state-of-the-art global climate models (GCMs) have been used in the present study. There was a decrease (ranging between about 10 and 20%) in soybean yield in all the three future scenarios when the effect of rise in surface air temperature at the time of the doubling of CO 2 concentration was considered. The results obtained on the mitigatory option for reducing the negative impacts of temperature increases indicate that delaying the sowing dates would be favorable for increased soybean yields at all the locations in India. Sowing in the second season would also be able to mitigate the detrimental effects of future increases in surface temperature due to global warming at some locations.

Future Climate Change Scenarios for Asia as Inferred from Selected Coupled Atmosphere-ocean Global Climate Models.

The response of the Asian continent to transient increases in future anthropogenic radiative forcings using the data generated in a set of numerical experiments performed with four coupled atmosphere-ocean global climate models (A-O GCMs) is examined here. These A-O GCMs have demonstrated reasonable skill as regards their ability to simulate the broad features of present-day observed climatological features over the Asian region. A plausible scenario of climate change over Asia and its six sub-regions as inferred from these A-O GCMs due to the future emissions of greenhouse gases and/or sulfate aerosols is presented. In general, the projected warming over Asia is higher during NH winter than during summer for both the decades 2050s (2040-2069) and 2080s (2070-2099). The rise in surface air temperature is likely to be most pronounced over the North Asia region in all the seasons. Each of the four A-O GCMs considered here simulates an enhanced hydrological cycle and an increase in annual precipitation over most of Asia. The inter-model differences in projections of precipitation are quite large even when averaged for the entire Asian continent suggesting rather limited confidence in the future projections of regional scale precipitation in currently available A-O GCM simulations.

Growth and yield responses of soybean in Madhya Pradesh, India to climate variability and change

This study is aimed at assessing the impact of thermal and moisture stresses associated with observed intraseasonal and interannual variability in key climatic elements on the nature and extent of losses in growth and yield of soybean crop in central India through the use of CROPGRO model. The crops are found to be more sensitive to higher cumulative heat units during cropping season. The yields respond substantially to temporal variations in rainfall (associated with observed swings in the continuity of monsoon). Prolonged dry spells at critical life stages of the soybean crop are found to adversely affect crop development and growth and hence the yields at selected sites. We have also examined the plausible effects of future climate change on soybean yields in the selected region based on simulations carried out for doubled atmospheric CO 2 level and with modified weather variables using the available seasonal projections for the future. Our findings on the response of elevated CO 2 concentrations in the atmosphere suggest higher yields (50% increase) for soybean crop for a doubling of CO 2. However, a 3°C rise in surface air temperature almost cancels out the positive effects of elevated CO 2 on the yield. Soybean crops at selected site are more vulnerable to increases in maximum temperature than in minimum temperature. The combined effect of doubled CO 2 and anticipated thermal stress (likely by middle of the next century) on soybean crop is about 36% increase in yield at the selected sites. A decline in daily rainfall amount by 10% restricts this yield gain to about 32%. Deficient rainfall with uneven distribution during the monsoon season could be a critical factor for the soybean productivity even under the positive effects of elevated CO 2 in the future.