Contribution of solar radiation to decadal temperature variability over land

Chiral NMR analysis reveals the environmental dependence of areolal scalemization in Piptothrix areolare

The occurrence of racemic and enantiomerically enriched (scalemic) mixtures of secondary metabolites in their natural sources is a rare phenomenon. The unprecedent case of enantiomeric variations from levorotatory to dextrorotatory, and back to levorotatory, passing through an almost racemic mixture, was recently documented for areolal, the major epoxythymol of Piptothrix areolare. In an attempt to shed some light to understand the reasons for such an unusual behavior, herein, we evaluated this phenomenon by correlating the areolal enantiomeric purity with several environmental variables, including temperature, humidity, rain precipitation, wind speed, and radiation during over 1 year of the plant life cycle. The specific rotation and enantiomeric excess determined by ¹ H-NMR-BINOL measurements provided the scalemic variations of areolal samples isolated from the roots collected from the same location along a 427-day period. The ¹ H-NMR-BINOL methodology provided better sensitivity to enantiomeric variations than specific rotation measurements. Statistical data, including matrix correlation analysis, exploratory analysis by heatmap plotting, and the principal component analysis (PCA), suggested direct correlation of the scalemic variation with humidity, rain precipitation, and radiation variables with the best PCA explanation (78.4%) and noncritical or poor correlations in PCA explained in 60.2% and 48.4%, respectively. When variations in the optical activity parameter of any metabolite are observed, the search for scalemic mixtures along their host plant life cycle should be undertaken. Herein, this phenomenon could be associated with interactions with soil microorganisms and with evolutionary aspects of Piptothrix areolare which belongs to Asteraceae, one of the most successfully adaptable plant families.

A Multifaceted Action of Phytochrome B in Plant Environmental Adaptation

Light acts as a vital external cue that conveys surrounding information into plant growth and performance to facilitate plants to coordinate with changing environmental conditions. Upon exposure to light illumination, plants trigger a burst of molecular and physiological signaling cascades that induces not only photomorphogenic responses but also diverse adaptive behaviors. Notably, light responses and photomorphogenic traits are often associated with plant responses to other environmental cues, such as heat, cold, drought, and herbivore and pathogen attack. Growing evidence in recent years demonstrate that the red/far-red light-absorbing phytochrome (phy) photoreceptors, in particular phyB, play an essential role in plant adaptation responses to abiotic and biotic tensions by serving as a key mediator of information flow. It is also remarkable that phyB mediates the plant priming responses to numerous environmental challenges. In this minireview, we highlight recent advances on the multifaceted role of phyB during plant environmental adaptation. We also discuss the biological relevance and efficiency of the phy-mediated adaptive behaviors in potentially reducing fitness costs under unfavorable environments.

Merging High-Resolution Satellite Surface Radiation Data with Meteorological Sunshine Duration Observations over China from 1983 to 2017

Surface solar radiation (Rs) is essential to climate studies. Thanks to long-term records from the Advanced Very High-Resolution Radiometers (AVHRR), the recent release of International Satellite Cloud Climatology Project (ISCCP) HXG cloud products provide a promising opportunity for building long-term Rs data with high resolutions (3 h and 10 km). In this study, we compare three satellite Rs products based on AVHRR cloud products over China from 1983 to 2017 with direct observations of Rs and sunshine duration (SunDu)-derived Rs. The results show that SunDu-derived Rs have higher accuracy than the direct observed Rs at time scales of a month or longer by comparing with the satellite Rs products. SunDu-derived Rs is available from the 1960s at more than 2000 stations over China, which provides reliable decadal estimations of Rs. However, the three AVHRR-based satellite Rs products have significant biases in quantifying the trend of Rs from 1983 to 2016 (−4.28 W/m2/decade to 2.56 W/m2/decade) due to inhomogeneity in satellite cloud products and the lack of information on atmospheric aerosol optical depth. To adjust the inhomogeneity of the satellite Rs products, we propose a geographically weighted regression fusion method (HGWR) to merge ISCCP-HXG Rs with SunDu-derived Rs. The merged Rs product over China from 1983 to 2017 with a spatial resolution of 10 km produces nearly the same trend as that of the SunDu-derived Rs. This study makes a first attempt to adjust the inhomogeneity of satellite Rs products and provides the merged high-resolution Rs product from 1983 to 2017 over China, which can be downloaded freely.

Advances in sunphotometer-measured aerosol optical properties and related topics in China: Impetus and perspectives

Aerosol is a critical trace component of the atmosphere. Many processes in the Earth's climate system are intimately related to aerosols via their direct and indirect radiative effects. Aerosol effects are not limited to these climatic aspects, however. They are also closely related to human health, photosynthesis, new energy, etc., which makes aerosol a central focus in many research fields. A fundamental requirement for improving our understanding of the diverse aerosol effects is to accumulate high-quality aerosol data by various measurement techniques. Sunphotometer remote sensing is one of the techniques that has been playing an increasingly important role in characterizing aerosols across the world. Much progress has been made on this aspect in China during the past decade, which is the work reviewed in this paper. Three sunphotometer networks have been established to provide high-quality observations of long-term aerosol optical properties across the country. Using this valuable dataset, our understanding of spatiotemporal variability and long-term trends of aerosol optical properties has been much improved. The radiative effects of aerosols both at the bottom and at the top of the atmosphere are comprehensively assessed. Substantial warming of the atmosphere by aerosol absorption is revealed. The long-range transport of dust from the Taklimakan Desert in Northwest China and anthropogenic aerosols from South Asia to the Tibetan Plateau is characterized based on ground-based and satellite remote sensing as well as model simulations. Effective methods to estimate chemical compositions from sunphotometer aerosol products are developed. Dozens of satellite and model aerosol products are validated, shedding new light on how to improve these products. These advances improve our understanding of the critical role played by aerosols in both the climate and environment. Finally, a perspective on future research is presented.

USRT: A Solar Radiative Transfer Model Dedicated to Estimating Urban 3D Surface Reflectance

Urban 3D surface reflectance is a critical parameter for the modeling of surface biophysical processes. It is of great significance to enhance the accuracy of reflectance in urban areas. Based on the urban solar radiative transfer (USRT) model, this study presents a methodology for estimating urban reflectance using the sky view factor (SVF) derived from airborne LiDAR data. Then, the USRT model was used to retrieve urban 3D surface reflectance from Landsat 8 data over the typical area of Beijing. The reflectance from USRT model was compared with the estimated value obtained from the model without considering the impact of morphological characteristics of the urban underlying surface (flat model). The results showed that the urban sample reflectance estimated by the USRT model was close to the sample reflectance of the suburban underlying surface which was less affected by morphological characteristics. The research summaries are as follows: (1) The definite physical meaning is presented in the USRT model, and can be applied to estimate the physical parameters of the urban underlying surface. (2) The reflectance from the USRT model is slightly larger than the reflectance derived from the flat model, which indicates that the accuracy of urban 3D surface reflectance is improved by the USRT model. (3) The effects of the SVF and building reflectance are different. The SVF presents a strong sensitivity to the estimation of the urban 3D surface reflectance, and the variations of building reflectance setting have little impact on urban reflectance, which is characterized by low sensitivity. Generally, the methodology of estimating urban reflectance proposed in this study can better clarify the impact mechanism of urban geometry on the radiative transfer processes and further promote the application and development of urban quantitative remote sensing.

Radiation dimming and decreasing water clarity fuel underwater darkening in lakes

Long-term decreases in the incident total radiation and water clarity might substantially affect the underwater light environment in aquatic ecosystems. However, the underlying mechanism and relative contributions of radiation dimming and decreasing water clarity to the underwater light environment on a national or global scale remains largely unknown. Here, we present a comprehensive dataset of unprecedented scale in China's lakes to address the combined effects of radiation dimming and decreasing water clarity on underwater darkening. Long-term total radiation and sunshine duration showed 5.8% and 7.9% decreases, respectively, after 2000 compared to 1961-1970, resulting in net radiation dimming. An in situ Secchi disk depth (SDD) dataset in 170 lakes showed that the mean SDD significantly decreased from 1.80 ± 2.19 m before 1995 to 1.28 ± 1.82 m after 2005. SDD remote sensing estimations for 641 lakes with areas ≥ 10 km² showed that SDD markedly decreased from 1.26 ± 0.62 m during 1985-1990 to 1.14 ± 0.66 m during 2005-2010. Radiation dimming and decreasing water clarity jointly caused an approximately 10% decrease in the average available photosynthetically active radiation (PAR) in the euphotic layer. Our results revealed a more important role of decreasing water clarity in underwater darkening than radiation dimming. A meta-analysis of long-term SDD observation data from 61 various waters further elucidated a global extensive underwater darkening. Underwater darkening implies a decrease in water quality for potable water supplies, recession in macrophytes and benthic algae, and decreases in benthic primary production, fishery production, and biodiversity.

Surface temperature variations and their relationships with land cover in the Pearl River Delta

The characteristics of land use/land cover (LULC) types may affect the thermal environment of urban zones. In this study, the urban zones of the Pearl River Delta (PRD) were examined to explore the spatiotemporal variations in land surface temperature (LST) from 2001 to 2017, as well as the relationships between LST and various influencing factors. Landscape pattern analysis was undertaken to explore the correlation between patch metrics and LST with resolutions from 100 m to 1 km. The results showed that (1) the high-temperature zones were mainly distributed on built-up land; the area of LST hot spots increased from 16% (2001) to 23% (2017). (2) The mean LST of each LULC type was calculated, indicating that the temperature of forestland was more than 5 °C lower than that of built-up land. (3) The landscape patterns of different land use types exhibited various effects on LST in terms of magnitude and importance. Considering the significance of the landscape indexes, it is necessary to avoid a large-scale layout of a single built-up land type when planning an urban environment. It is thus recommended that multiple contiguous forestlands be planned to mitigate urban heat island (UHI) effects. Furthermore, the landscape patterns and structure of different LULC types have various effects on LST and need to be explored in fine detail. This study helped reveal the impact of different LULC types on LST and provides urban planners in the PRD with optional schemes for mitigating the impacts of urbanization on the UHI.

Ecological and conceptual consequences of Arctic pollution

Although the effect of pollution on forest health and decline received much attention in the 1980s, it has not been considered to explain the 'Divergence Problem' in dendroclimatology; a decoupling of tree growth from rising air temperatures since the 1970s. Here we use physical and biogeochemical measurements of hundreds of living and dead conifers to reconstruct the impact of heavy industrialisation around Norilsk in northern Siberia. Moreover, we develop a forward model with surface irradiance forcing to quantify long-distance effects of anthropogenic emissions on the functioning and productivity of Siberia's taiga. Downwind from the world's most polluted Arctic region, tree mortality rates of up to 100% have destroyed 24,000 km² boreal forest since the 1960s, coincident with dramatic increases in atmospheric sulphur, copper, and nickel concentrations. In addition to regional ecosystem devastation, we demonstrate how 'Arctic Dimming' can explain the circumpolar 'Divergence Problem', and discuss implications on the terrestrial carbon cycle.

Skillful prediction of hot temperature extremes over the source region of ancient Silk Road

The source region of ancient Silk Road (SRASR) in China, a region of around 150 million people, faces a rapidly increased risk of extreme heat in summer. In this study, we develop statistical models to predict summer hot temperature extremes over the SRASR based on a timescale decomposition approach. Results show that after removing the linear trends, the inter-annual components of summer hot days and heatwaves over the SRASR are significantly related with those of spring soil temperature over Central Asia and sea surface temperature over Northwest Atlantic while their inter-decadal components are closely linked to those of spring East Pacific/North Pacific pattern and Atlantic Multidecadal Oscillation for 1979-2016. The physical processes involved are also discussed. Leave-one-out cross-validation for detrended 1979-2016 time series indicates that the statistical models based on identified spring predictors can predict 47% and 57% of the total variances of summer hot days and heatwaves averaged over the SRASR, respectively. When the linear trends are put back, the prediction skills increase substantially to 64% and 70%. Hindcast experiments for 2012-2016 show high skills in predicting spatial patterns of hot temperature extremes over the SRASR. The statistical models proposed herein can be easily applied to operational seasonal forecasting.

Perception and signalling of light and temperature cues in plants

Light and temperature patterns are often correlated under natural plant growth conditions. In this review, we analyse the perception and signalling mechanisms shared by both these environmental cues and discuss the functional implications of their convergence to control plant growth. The first point of integration is the phytochrome B (phyB) receptor, which senses light and temperature. Downstream of phyB, the signalling core comprises two branches, one involving PHYTOCHROME INTERACTING FACTOR 4 (PIF4) and the other CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1) and ELONGATED HYPOCOTYL 5 (HY5). The dynamics of accumulation and/or localization of each of these core signalling components depend on light and temperature conditions. These pathways are connected through COP1, which enhances the activity of PIF4. The circadian clock modulates this circuit, since EARLY FLOWERING 3 (ELF3), an essential component of the evening complex (EC), represses expression of the PIF4 gene and PIF4 transcriptional activity. Phytochromes are probably not the only entry point of temperature into this network, but other sensors remain to be established. The sharing of mechanisms of action for two distinct environmental cues is to some extent unexpected, as it renders these responses mutually dependent. There are nonetheless many ecological contexts in which such a mutual influence could be beneficial.

Desert Amplification in a Warming Climate

Here I analyze the observed and projected surface temperature anomalies over land between 50°S-50°N for the period 1950–2099 by large-scale ecoregion and find strongest warming consistently and persistently seen over driest ecoregions such as the Sahara desert and the Arabian Peninsula during various 30-year periods, pointing to desert amplification in a warming climate. This amplification enhances linearly with the global mean greenhouse gases(GHGs) radiative forcing and is attributable primarily to a stronger GHGs-enhanced downward longwave radiation forcing reaching the surface over drier ecoregions as a consequence of a warmer and thus moister atmosphere in response to increasing GHGs. These results indicate that desert amplification may represent a fundamental pattern of global warming associated with water vapor feedbacks over land in low- and mid- latitudes where surface warming rates depend inversely on ecosystem dryness. It is likely that desert amplification might involve two types of water vapor feedbacks that maximize respectively in the tropical upper troposphere and near the surface over deserts, with both being very dry and thus extremely sensitive to changes of water vapor.

Coldest Temperature Extreme Monotonically Increased and Hottest Extreme Oscillated over Northern Hemisphere Land during Last 114 Years

Most studies on global warming rely on global mean surface temperature, whose change is jointly determined by anthropogenic greenhouse gases (GHGs) and natural variability. This introduces a heated debate on whether there is a recent warming hiatus and what caused the hiatus. Here, we presented a novel method and applied it to a 5° × 5° grid of Northern Hemisphere land for the period 1900 to 2013. Our results show that the coldest 5% of minimum temperature anomalies (the coldest deviation) have increased monotonically by 0.22 °C/decade, which reflects well the elevated anthropogenic GHG effect. The warmest 5% of maximum temperature anomalies (the warmest deviation), however, display a significant oscillation following the Atlantic Multidecadal Oscillation (AMO), with a warming rate of 0.07 °C/decade from 1900 to 2013. The warmest (0.34 °C/decade) and coldest deviations (0.25 °C/decade) increased at much higher rates over the most recent decade than last century mean values, indicating the hiatus should not be interpreted as a general slowing of climate change. The significant oscillation of the warmest deviation provides an extension of previous study reporting no pause in the hottest temperature extremes since 1979, and first uncovers its increase from 1900 to 1939 and decrease from 1940 to 1969.

Solar pacing of storm surges, coastal flooding and agricultural losses in the Central Mediterranean

Storm surges, leading to catastrophic coastal flooding, are amongst the most feared natural hazards due to the high population densities and economic importance of littoral areas. Using the Central Mediterranean Sea as a model system, we provide strong evidence for enhanced periods of storminess leading to coastal flooding during the last 4500 years. We show that long-term correlations can be drawn between storminess and solar activity, acting on cycles of around 2200-yr and 230-yr. We also find that phases of increased storms and coastal flooding have impacted upon mid- to late Holocene agricultural activity on the Adriatic coast. Based on the general trend observed during the second half of the 20^th century, climate models are predicting a weakening of Mediterranean storminess. By contrast, our new data suggest that a decrease in solar activity will increase and intensify the risk of frequent flooding in coastal areas.

Impacts of wind stilling on solar radiation variability in China

Solar dimming and wind stilling (slowdown) are two outstanding climate changes occurred in China over the last four decades. The wind stilling may have suppressed the dispersion of aerosols and amplified the impact of aerosol emission on solar dimming. However, there is a lack of long-term aerosol monitoring and associated study in China to confirm this hypothesis. Here, long-term meteorological data at weather stations combined with short-term aerosol data were used to assess this hypothesis. It was found that surface solar radiation (SSR) decreased considerably with wind stilling in heavily polluted regions at a daily scale, indicating that wind stilling can considerably amplify the aerosol extinction effect on SSR. A threshold value of 3.5 m/s for wind speed is required to effectively reduce aerosols concentration. From this SSR dependence on wind speed, we further derived proxies to quantify aerosol emission and wind stilling amplification effects on SSR variations at a decadal scale. The results show that aerosol emission accounted for approximately 20% of the typical solar dimming in China, which was amplified by approximately 20% by wind stilling.

Parameterization of clear-sky surface irradiance and its implications for estimation of aerosol direct radiative effect and aerosol optical depth

Aerosols impact clear-sky surface irradiance () through the effects of scattering and absorption. Linear or nonlinear relationships between aerosol optical depth (τ_a) and have been established to describe the aerosol direct radiative effect on (ADRE). However, considerable uncertainties remain associated with ADRE due to the incorrect estimation of (τ_a in the absence of aerosols). Based on data from the Aerosol Robotic Network, the effects of τ_a, water vapor content (w) and the cosine of the solar zenith angle (μ) on are thoroughly considered, leading to an effective parameterization of as a nonlinear function of these three quantities. The parameterization is proven able to estimate with a mean bias error of 0.32 W m⁻², which is one order of magnitude smaller than that derived using earlier linear or nonlinear functions. Applications of this new parameterization to estimate τ_a from , or vice versa, show that the root-mean-square errors were 0.08 and 10.0 Wm⁻², respectively. Therefore, this study establishes a straightforward method to derive from τ_a or estimate τ_a from measurements if water vapor measurements are available.

Regional Contrasts of the Warming Rate over Land Significantly Depend on the Calculation Methods of Mean Air Temperature

Global analyses of surface mean air temperature (T_m) are key datasets for climate change studies and provide fundamental evidences for global warming. However, the causes of regional contrasts in the warming rate revealed by such datasets, i.e., enhanced warming rates over the northern high latitudes and the “warming hole” over the central U.S., are still under debate. Here we show these regional contrasts depend on the calculation methods of T_m. Existing global analyses calculate T_m from daily minimum and maximum temperatures (T₂). We found that T₂ has a significant standard deviation error of 0.23 °C/decade in depicting the regional warming rate from 2000 to 2013 but can be reduced by two-thirds using T_m calculated from observations at four specific times (T₄), which samples diurnal cycle of land surface air temperature more often. From 1973 to 1997, compared with T₄, T₂ significantly underestimated the warming rate over the central U.S. and overestimated the warming rate over the northern high latitudes. The ratio of the warming rate over China to that over the U.S. reduces from 2.3 by T₂ to 1.4 by T₄. This study shows that the studies of regional warming can be substantially improved by T₄ instead of T₂.

Measurement biases explain discrepancies between the observed and simulated decadal variability of surface incident solar radiation

Observations have reported a widespread dimming of surface incident solar radiation (R_s) from the 1950s to the 1980s and a brightening afterwards. However, none of the state-of-the-art earth system models, including those from the Coupled Model Intercomparison Project phase 5 (CMIP5), could successfully reproduce the dimming/brightening rates over China. We find that the decadal variability of observed R_s may have important errors due to instrument sensitivity drifting and instrument replacement. While sunshine duration (SunDu), which is a robust measurement related to R_s, is nearly free from these problems. We estimate R_s from SunDu with a method calibrated by the observed R_s at each station. SunDu-derived R_s declined over China by −2.8 (with a 95% confidence interval of −1.9 to −3.7) W m⁻² per decade from 1960 to 1989, while the observed R_s declined by −8.5 (with a 95% confidence interval of −7.3 to −9.8) W m⁻² per decade. The former trend was duplicated by some high-quality CMIP5 models, but none reproduced the latter trend.

Sampling biases in datasets of historical mean air temperature over land

Global mean surface air temperature (T_a) has been reported to have risen by 0.74°C over the last 100 years. However, the definition of mean T_a is still a subject of debate. The most defensible definition might be the integral of the continuous temperature measurements over a day (T_d0). However, for technological and historical reasons, mean T_a over land have been taken to be the average of the daily maximum and minimum temperature measurements (T_d1). All existing principal global temperature analyses over land rely heavily on T_d1. Here, I make a first quantitative assessment of the bias in the use of T_d1 to estimate trends of mean T_a using hourly T_a observations at 5600 globally distributed weather stations from the 1970s to 2013. I find that the use of T_d1 has a negligible impact on the global mean warming rate. However, the trend of T_d1 has a substantial bias at regional and local scales, with a root mean square error of over 25% at 5° × 5° grids. Therefore, caution should be taken when using mean T_a datasets based on T_d1 to examine high resolution details of warming trends.

500-year climate cycles stacking of recent centennial warming documented in an East Asian pollen record

Here we presented a high-resolution 5350-year pollen record from a maar annually laminated lake in East Asia (EA). Pollen record reflected the dynamics of vertical vegetation zones and temperature change. Spectral analysis on pollen percentages/concentrations of Pinus and Quercus, and a temperature proxy, revealed ~500-year quasi-periodic cold-warm fluctuations during the past 5350 years. This ~500-year cyclic climate change occurred in EA during the mid-late Holocene and even the last 150 years dominated by anthropogenic forcing. It was almost in phase with a ~500-year periodic change in solar activity and Greenland temperature change, suggesting that ~500-year small variations in solar output played a prominent role in the mid-late Holocene climate dynamics in EA, linked to high latitude climate system. Its last warm phase might terminate in the next several decades to enter another ~250-year cool phase, and thus this future centennial cyclic temperature minimum could partially slow down man-made global warming.

Climatic variation and runoff from partially-glacierised Himalayan tributary basins of the Ganges

Climate records for locations across the southern slope of the Himalaya between 77°E and 91°E were selected together with discharge measurements from gauging stations on rivers draining partially-glacierised basins tributary to the Ganges, with a view to assessing impacts of climatic fluctuations on year-to-year variations of runoff during a sustained period of glacier decline. The aims were to describe temporal patterns of variation of glaciologically- and hydrologically-relevant climatic variables and of river flows from basins with differing percentages of ice-cover. Monthly precipitation and air temperature records, starting in the mid-nineteenth century at high elevation sites and minimising data gaps, were selected from stations in the Global Historical Climatology Network and CRUTEM3. Discharge data availability was limited to post 1960 for stations in Nepal and at Khab in the adjacent Sutlej basin. Strengths of climate-runoff relationships were assessed by correlation between overlapping portions of annual data records. Summer monsoon precipitation dominates runoff across the central Himalaya. Flow in tributaries of the Ganges in Nepal fluctuated from year to year but the general background level of flow was usually maintained from the 1960s to 2000s. Flow in the Sutlej, however, declined by 32% between the 1970s and 1990s, reflecting substantially reduced summer precipitation. Over the north-west Ganges-upper Sutlej area, monsoon precipitation declined by 30-40% from the 1960s to 2000s. Mean May-September air temperatures along the southern slope of the central Himalayas dipped from the 1960s, after a long period of slow warming or sustained temperatures, before rising rapidly from the mid-1970s so that in the 2000s summer air temperatures reached those achieved in earlier warmer periods. There are few measurements of runoff from highly-glacierised Himalayan headwater basins; runoff from one of which, Langtang Khola, was less than that of the monsoon-dominated Narayani river, in which basin Langtang is nested.