Do Satellites Detect Trends in Surface Solar Radiation?

India's photovoltaic potential amidst air pollution and land constraints

India aims for ambitious solar energy goal to fulfill its climate commitment but there are limited studies on solar resource assessment considering both environmental and land availability constraints. The present work attempts to address this issue using satellite-derived air pollution, radiation, and land use data over the Indian region. Surface insolation over India has been decreasing at a rate of -0.29 ± 0.19 Wm-2 y-1 between 2001 and 2018. Solar resources over nearly 98%, 40%, and 39% of the Indian landmass are significantly impacted by aerosols, clouds, and both aerosols and clouds respectively. Only 29.3% of the Indian landmass is presently suitable for effective solar photovoltaic harnessing, but this is further declining by -0.21% annually, causing a presumptive loss of 50 GW solar potential, translating 75 TWh power generation. Lowering two decades of aerosol burden can make 8% additional landmass apt for photovoltaic use. Alleviating aerosol-induced dimming can fast-track India's solar energy expansion.

Effect of solar radiation on natural organic matter composition in surface waters and resulting impacts on drinking water treatment

Solar radiation experiments showed a shift in the composition of natural organic matter (NOM). Due to irradiation, the concentration of high molecular weight (HMW) molecules decreased, and that of the low molecular weight (LMW) fraction increased. Microbiological analyses showed that biodegradation was neglectable. To assess the consequences for water treatment processes, coagulation jar tests were performed by comparing the removal effectivity for NOM fractions from irradiated and unirradiated raw water. The degree of dissolved organic carbon (DOC) removal by coagulation was lower for irradiated waters. As primarily HMW organic compounds are removed by coagulation, the decrease in coagulation performance is attributed to the increase in the LMW concentration due to photochemical reactions induced by solar radiation. Flocs were about 15% larger for irradiated water. Possibilities to adapt water treatment to respond to changes in DOC composition and concentration are outlined. Ozonation-biofiltration is judged as the most promising treatment process to cope with climate change-related challenges in drinking water treatment.

Budyko-Based Long-Term Water and Energy Balance Closure in Global Watersheds From Earth Observations

Earth observations offer potential pathways for accurately closing the water and energy balance of watersheds, a fundamental challenge in hydrology. However, previous attempts based on purely satellite-based estimates have focused on closing the water and energy balances separately. They are hindered by the lack of estimates of key components, such as runoff. Here, we posit a novel approach based on Budyko's water and energy balance constraints. The approach is applied to quantify the degree of long-term closure at the watershed scale, as well as its associated uncertainties, using an ensemble of global satellite data sets. We find large spatial variability across aridity, elevation, and other environmental gradients. Specifically, we find a positive correlation between elevation and closure uncertainty, as derived from the Budyko approach. In mountainous watersheds the uncertainty in closure is 3.9 ± 0.7 (dimensionless). Our results show that uncertainties in terrestrial evaporation contribute twice as much as precipitation uncertainties to errors in the closure of water and energy balance. Moreover, our results highlight the need for improving satellite-based precipitation and evaporation data in humid temperate forests, where the closure error in the Budyko space is as high as 1.1 ± 0.3, compared to only 0.2 ± 0.03 in tropical forests. Comparing the results with land surface model-based data sets driven by in situ precipitation, we find that Earth observation-based data sets perform better in regions where precipitation gauges are sparse. These findings have implications for improving the understanding of global hydrology and regional water management and can guide the development of satellite remote sensing-based data sets and Earth system models.

Potential Driving Factors on Surface Solar Radiation Trends over China in Recent Years

The annual mean surface solar radiation (SSR) trends under all-sky, clear-sky, all-sky-no-aerosol, and clear-sky-no-aerosol conditions as well as their possible causes are analyzed during 2005–2018 across China based on different satellite-retrieved datasets to determine the major drivers of the trends. The results confirm clouds and aerosols as the major contributors to such all-sky SSR trends over China but play differing roles over sub-regions. Aerosol variations during this period result in a widespread brightening, while cloud effects show opposite trends from south to north. Moreover, aerosols contribute more to the increasing all-sky SSR trends over northern China, while clouds dominate the SSR decline over southern China. A radiative transfer model is used to explore the relative contributions of cloud cover from different cloud types to the all-types-of-cloud-cover-induced (ACC-induced) SSR trends during this period in four typical sub-regions over China. The simulations point out that the decreases in low-cloud-cover (LCC) over the North China Plain are the largest positive contributor of all cloud types to the marked annual and seasonal ACC-induced SSR increases, and the positive contributions from both high-cloud-cover (HCC) and LCC declines in summer and winter greatly contribute to the ACC-induced SSR increases over East China. The contributions from medium-low-cloud-cover (mid-LCC) and LCC variations dominate the ACC-caused SSR trends over southwestern and South China all year round, except for the larger HCC contribution in summer.

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.

Solar Brightening/Dimming over China’s Mainland: Effects of Atmospheric Aerosols, Anthropogenic Emissions, and Meteorological Conditions

Surface solar radiation (SSR) is the main factor affecting the earth’s climate and environment and its variations and the reason for these variations are an important part of climate change research. In this research, we investigated the long-term variations of SSR during 1984–2016 and the quantitative influences of atmospheric aerosols, anthropogenic emissions, and meteorological conditions on SSR over China’s mainland. The results show the following: (1) The annual average SSR values had a decline trend at a rate of −0.371 Wm−2 yr−1 from 1984 to 2016 over China. (2) The aerosol optical depth (AOD) plays the main role in inducing variations in SSR over China, with r values of −0.75. Moreover, there are marked regional differences in the influence of anthropogenic emissions and meteorological conditions on SSR trends. (3) From a regional perspective, AOD is the main influencing factor on SSR in northeast China (NEC), Yunnan Plateau and surrounding regions (YPS), North China (NC), and Loess Plateau (LP), with r values of −0.65, −0.60, −0.89, and −0.50, respectively. However, the main driving factors for SSR in northwest China (NWC) are “in cloud optical thickness of all clouds” (TAUTOT) (−0.26) and black carbon (BC) anthropogenic emissions (−0.21). TAUTOT (−0.39) and total precipitable water vapor (TQV) (−0.29) are the main influencing factors of SSR in the middle-lower Yangtze Plain (MYP). The main factors that influence SSR in southern China (SC) are surface pressure (PS) (−0.66) and AOD (−0.43). This research provides insights in understanding the variations of SSR and its relationships with anthropogenic conditions and meteorological factors.

The accuracy improvement of clear-sky surface shortwave radiation derived from CERES SSF dataset with a simulation analysis

Towards the Xiaotang region along the northern margin of the China's largest desert, a quantitative assessment of the precision of clear-sky satellite observations (the Single Scanner Footprint TOA/Surface Fluxes and Clouds downward surface shortwave radiation product of Clouds and the Earth's Radiant Energy System (CERES), DSSR_CER) is conducted, the localized inversion mode of "absolutely clear-sky" downward surface shortwave radiation (DSSR) is established, and the "absolutely clear-sky" DSSR in Xiaotang during 2005-2018 is simulated by the Santa Barbara Discrete Atmospheric Radiative Transfer (SBDART) model. In general, under the "absolutely clear-sky" condition of Xiaotang region, there is a significant error in DSSR_CER, and the simulated results of SBDART (DSSR_SBD) with same input parameters as DSSR_CER is better and more comparable. Single scattering albedo (SSA), asymmetry parameter (ASY) and aerosol optical depth (AOD) play crucial roles in deciding the accuracy of DSSR, and after parameter adjustment, the DSSR_SBD is better than the initial, which is improved remarkably with all indexes of the fitting results greatly improved. The temporal variation of the DSSR during 2005-2018 indicates that the highest annual average value is found in 2008 (770.00 W·m^-2), while the lowest appears in 2010 (600.97 W·m^-2). Besides, the highest seasonal mean DSSR appears in summer, which between 860.6 and 935.07 W·m^-2, while reaches the lowest in winter (403.79-587.53 W·m^-2). Moreover, the monthly average DSSR changes as a curve with a single peak and is close to normal distribution, the highest appears in June (934.61 W·m^-2), while the minimum with the value of 390.34 W·m^-2 is found in December. All of the solar elevation angle, the characteristics of climate and aerosol particles in different seasons may contribute to the temporal variation.

A New Long-Term Downward Surface Solar Radiation Dataset over China from 1958 to 2015

Downward surface solar radiation (Rs) plays a dominant role in determining the climate and environment on the Earth. However, the densely distributed ground observations of Rs are usually insufficient to meet the increasing demand of the climate diagnosis and analysis well, so it is essential to build a long-term accurate Rs dataset. The extremely randomized trees (ERT) algorithm was used to generate Rs using routine meteorological observations (2000–2015) from the Climate Data Center of the Chinese Meteorological Administration (CDC/CMA). The estimated Rs values were validated against ground measurements at the national scale with an overall correlation coefficient value of 0.97, a mean bias of 0.04 Wm⁻², a root-mean-square-error value of 23.12 Wm⁻², and a mean relative error of 9.81%. It indicates that the estimated Rs from the ERT-based model is reasonably accurate. Moreover, the ERT-based model was used to generate a new daily Rs dataset at 756 CDC/CMA stations from 1958 to 2015. The long-term variation trends of Rs at 454 stations covering 46 consecutive years (1970–2015) were also analyzed. The Rs in China showed a significant decline trend (−1.1 Wm⁻² per decade) during 1970–2015. A decreasing trend (−2.8 Wm⁻² per decade) in Rs during 1970–1992 was observed, followed by a recovery trend (0.23 Wm⁻² per decade) during 1992–2015. The recovery trends at individual stations were found at 233 out of 454 stations during 1970–2015, which were mainly located in southern and northern China. The new Rs dataset would substantially provide basic data for the related studies in agriculture, ecology, and meteorology.

The Atmosphere

The atmosphere is composed of nitrogen, oxygen and argon, a variety of trace gases, and particles or aerosols from a variety of sources. Reactive, trace gases have short mean residence time in the atmosphere and large spatial and temporal variations in concentration. Many trace gases are removed by reaction with hydroxyl radical and deposition in rainfall or dryfall at the Earth's surface. The upper atmosphere, the stratosphere, contains ozone that screens ultraviolet light from the Earth's surface. Chlorofluorocarbons released by humans lead to the loss of stratospheric ozone, which might eventually render the Earth's land surface uninhabitable. Changes in the composition of the atmosphere, especially rising concentrations of CO₂, CH₄, and N₂O, will lead to climatic changes over much of the Earth's surface.

Improvement of Air Pollution in China Inferred from Changes between Satellite-Based and Measured Surface Solar Radiation

The air pollution crisis in China has become a global concern due to its profound effects on the global environment and human health. To significantly improve the air quality, mandatory reductions were imposed on pollution emissions and energy consumption within the framework of the 11th and 12th Five Year Plans of China. This study takes the first step to quantify the implications of recent pollution control efforts for surface solar radiation (SSR), the primary energy source for our planet. The observed bias between satellite-retrieved and surface-observed SSR time series is proposed as a useful indicator for the radiative effects of aerosol changes. This is due to the fact that the effects of temporal variations of aerosols are neglected in satellite retrievals but well captured in surface observations of SSR. The implemented pollution control measures and actions have successfully brought back SSR by an average magnitude of 3.5 W m−2 decade−1 for the whole of China from 2008 onwards. Regionally, effective pollution regulations are indicated in the East Coast regions of South and North China, including the capital Beijing, with the SSR brightening induced by aerosol reduction of 7.5 W m−2 decade−1, 5.2 W m−2 decade−1, and 5.9 W m−2 decade−1, respectively. Seasonally, the SSR recovery in China mainly occurs in the warm seasons of spring and summer, with the magnitudes induced by the aerosol radiative effects of 5.9 W m−2 decade−1 and 4.7 W m−2 decade−1, respectively.

Comparison of manual and automatic daily sunshine duration measurements at German climate reference stations

Abstract. Precise quantification of climate change depends on long time series of meteorological variables. Such time series should be as homogeneous as possible but some changes of measurement conditions cannot be prevented. At German climate reference stations, parallel measurements are used to analyze the effects of changes in measurement systems for example for the transition from manual to automatic instruments. These parallel measurements aim to identify measurement uncertainties and to analyze the comparability of measurement systems to investigate the homogeneity. In this study, we investigate daily sunshine duration. Traditionally, manual measurements of daily sunshine duration are taken with Campbell-Stokes sunshine recorders. For automatic measurements the SONIe or SCAPP instrument is used. The different measurement principles (glass sphere and photodiode) cause systematic differences between the observations. During summer, values for manual observations are larger especially in case of frequent alternations between sunny and cloudy conditions. Furthermore, the standard deviation of the differences between the two measurement systems is larger during summer because of the greater day length. To adjust the automatic measurements a linear regression model is suggested based on parallel measurements from 13 climate reference stations in Germany. To validate the regression coefficients, a leave-one-out cross validation was performed (by leaving out data of individual stations). The regression coefficients (derived from different sets of stations) are similar, thereby indicating a robust data set for the estimation of the linear model. With this method we want to prevent breaks in long time series of daily sunshine duration caused by the transition from manual to automatic instruments.

Entrance Pupil Irradiance Estimating Model for a Moon-Based Earth Radiation Observatory Instrument

A Moon-based Earth radiation observatory (MERO) could provide a longer-term continuous measurement of radiation exiting the Earth system compared to current satellite-based observatories. In order to parameterize the detector for such a newly-proposed MERO, the evaluation of the instrument’s entrance pupil irradiance (EPI) is of great importance. The motivation of this work is to build an EPI estimating model for a simplified single-pixel MERO instrument. The rationale of this model is to sum the contributions of every location in the MERO-viewed region on the Earth’s top of atmosphere (TOA) to the MERO sensor’s EPI, taking into account the anisotropy in the longwave radiance at the Earth TOA. Such anisotropy could be characterized by the TOA anisotropic factors, which can be derived from the Clouds and the Earth’s Radiant Energy System (CERES) angular distribution models (ADMs). As an application, we estimated the shortwave (SW) (0.3–5 µm) and longwave (LW) (5–200 µm) EPIs for a hypothetic MERO instrument located at the Apollo 15 landing site. Results show that the SW EPI varied from 0 to 0.065 W/m2, while the LW EPI ranged between 0.061 and 0.075 W/m2 from 1 to 29 October, 2017. We also utilized this model to predict the SW and LW EPIs for any given location within the MERO-deployable region (region of 80.5°W–80.5°E and 81.5°S–81.5°N on the nearside of the Moon) for the future 18.6 years from October 2017 to June 2036. Results suggest that the SW EPI will vary between 0 and 0.118 W/m2, while the LW EPI will range from 0.056 to 0.081 W/m2. Though the EPI estimating model in this study was built for a simplistic single-pixel instrument, it could eventually be extended and improved in order to estimate the EPI for a multi-pixel MERO sensor.

Global Radiative Flux and Cloudiness Variability for the Period 1959–2010 in Belgium: A Comparison between Reanalyses and the Regional Climate Model MAR

The use of regional climate models (RCMs) can partly reduce the biases in global radiative flux (Eg↓) that are found in reanalysis products and global models, as they allow for a finer spatial resolution and a finer parametrisation of surface and atmospheric processes. In this study, we assess the ability of the MAR («Modèle Atmosphérique Régional») RCM to reproduce observed changes in Eg↓, and we investigate the added value of MAR with respect to reanalyses. Simulations were performed at a horizontal resolution of 5 km for the period 1959–2010 by forcing MAR with different reanalysis products: ERA40/ERA-interim, NCEP/NCAR-v1, ERA-20C, and 20CRV2C. Measurements of Eg↓ from the Global Energy Balance Archive (GEBA) and from the Royal Meteorological Institute of Belgium (RMIB), as well as cloud cover observations from Belgocontrol and RMIB, were used for the evaluation of the MAR model and the forcing reanalyses. Results show that MAR enables largely reducing the mean biases that are present in the reanalyses. The trend analysis shows that only MAR forced by ERA40/ERA-interim shows historical trends, which is probably because the ERA40/ERA-interim has a better horizontal resolution and assimilates more observations than the other reanalyses that are used in this study. The results suggest that the solar brightening observed since the 1980s in Belgium has mainly been due to decreasing cloud cover.

Sunshine duration reconstruction in the southeastern Tibetan Plateau based on tree-ring width and its relationship to volcanic eruptions

Sunshine is as essential as temperature and precipitation for tree growth, but sunshine duration reconstructions based on tree rings have not yet been conducted in China. In this study, we presented a 497-year sunshine duration reconstruction for the southeastern Tibetan Plateau using a width chronology of Abies forrestii from the central Hengduan Mountains. The reconstruction accounted for 53.5% of the variance in the observed sunshine during the period of 1961-2013 based on a stable and reliable linear regression. This reconstructed sunshine duration contained six sunny periods (1630-1656, 1665-1697, 1731-1781, 1793-1836, 1862-1895 and 1910-1992) and seven cloudy periods (1522-1629, 1657-1664, 1698-1730, 1782-1792, 1837-1861, 1896-1909 and 1993-2008) at a low-frequency scale. There was an increasing trend from the 16th century to the late 18th and early 19th centuries and a decreasing trend from the mid-19th to the early 21st centuries. Sunshine displayed inverse patterns to the local Palmer drought severity index on a multidecadal scale, indicating that this region likely experienced droughts under more sunshine conditions. The decrease in sunshine particularly in recent decades was mainly due to increasing atmospheric anthropogenic aerosols. In terms of the interannual variations in sunshine, weak sunshine years matched well with years of major volcanic eruptions. The significant cycles of the 2- to 7-year, 20.0-year and 35.2-year durations as well as the 60.2-year and 78.7-year durations related to the El-Niño Southern Oscillation, the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation suggested that the variation in sunshine duration in the southeastern Tibetan Plateau was possibly affected by large-scale ocean-atmosphere circulations.

Diurnal cycle and seasonal variation of cloud cover over the Tibetan Plateau as determined from Himawari-8 new-generation geostationary satellite data

Analysis of cloud cover and its diurnal variation over the Tibetan Plateau (TP) is highly reliant on satellite data; however, the accuracy of cloud detection from both polar-orbiting and geostationary satellites over this area remains unclear. The new-generation geostationary Himawari-8 satellites provide high-resolution spatial and temporal information about clouds over the Tibetan Plateau. In this study, the cloud detection of MODIS and AHI is investigated and validated against CALIPSO measurements. For AHI and MODIS, the false alarm rate of AHI and MODIS in cloud identification over the TP was 7.51% and 1.94%, respectively, and the cloud hit rate was 73.55% and 80.15%, respectively. Using hourly cloud-cover data from the Himawari-8 satellites, we found that at the monthly scale, the diurnal cycle in cloud cover over the TP tends to increase throughout the day, with the minimum and maximum cloud fractions occurring at 10:00 a.m. and 18:00 p.m. local time. Due to the limited time resolution of polar-orbiting satellites, the underestimation of MODIS daytime average cloud cover is approximately 4.00% at the annual scale, with larger biases during the spring (5.40%) and winter (5.90%).

Long-term spatial distributions and trends of the latent heat fluxes over the global cropland ecosystem using multiple satellite-based models

Estimating cropland latent heat flux (LE) from continental to global scales is vital to modeling crop production and managing water resources. Over the past several decades, numerous LE models were developed, such as the moderate resolution imaging spectroradiometer LE (MOD16) algorithm, revised remote sensing-based Penman-Monteith LE algorithm (RRS), the Priestley-Taylor LE algorithm of the Jet Propulsion Laboratory (PT-JPL) and the modified satellite-based Priestley-Taylor LE algorithm (MS-PT). However, these LE models have not been directly compared over the global cropland ecosystem using various algorithms. In this study, we evaluated the performances of these four LE models using 34 eddy covariance (EC) sites. The results showed that mean annual LE for cropland varied from 33.49 to 58.97 W/m2 among the four models. The interannual LE slightly increased during 1982-2009 across the global cropland ecosystem. All models had acceptable performances with the coefficient of determination (R2) ranging from 0.4 to 0.7 and a root mean squared error (RMSE) of approximately 35 W/m2. MS-PT had good overall performance across the cropland ecosystem with the highest R2, lowest RMSE and a relatively low bias. The reduced performances of MOD16 and RRS, with R2 ranging from 0.4 to 0.6 and RMSEs from 30 to 39 W/m2, might be attributed to empirical parameters in the structure algorithms and calibrated coefficients.

The Contribution of Solar Brightening to the US Maize Yield Trend

Predictions of crop yield under future climate change are predicated on historical yield trends^1-3, hence it is important to identify the contributors to historical yield gains and their potential for continued increase. The large gains in maize yield in the US Corn Belt have been attributed to agricultural technologies⁴, ignoring the potential contribution of solar brightening (decadal-scale increases in incident solar radiation) reported for much of the globe since the mid-1980s. In this study, using a novel biophysical/empirical approach, we show that solar brightening contributed approximately 27% of the US Corn Belt yield trend from 1984 to 2013. Accumulated solar brightening during the post-flowering phase of development of maize increased during the past 3 decades, causing the yield increase that previously had been attributed to agricultural technology. Several factors are believed to cause solar brightening, but their relative importance and future outlook are unknown^5-9, making prediction of continued solar brightening and its future contribution to yield gain uncertain. Consequently, results of this study call into question the implicit use of historical yield trends in predicting yields under future climate change scenarios.

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.

Recent observations of human-induced asymmetric effects on climate in very high-altitude area

Like urban heat islands (UHI), human-induced land degradation (HLD) is a phenomenon attributed to human activities, but this phenomenon occurs in non-urban areas. Although a large body of work has demonstrated that land-cover change influences local climate systems, little work has been done on separating the impact of HLD from naturally-occurring fluctuations in very high-altitude areas. We developed an innovative NDVI-difference method in order to evaluate HLD effects upon the climate system in the central Tibet Plateau. The results show that the minimum temperature increased at a significantly faster pace than the maximum temperature in the growing season at HLD meteorological stations, but this was reversed at stations with natural forces only. Further analysis revealed that abrupt changes of minimum temperature occurred five years earlier and amplitudes of these changes were 1.4 times larger than at stations with natural forces only. Therefore, our results complement other evidence that points to the fact that local effects from UHI contribute to climatic asymmetry observed between minimum and maximum temperature trends. Accordingly, we stress the need for consideration of non-urban factors from anthropogenic activities, such as human-induced land degradation, in understanding these asymmetric diurnal changes.

Ecotypic variation in response to light spectra in Scots pine (Pinus sylvestris L.)

We investigated Scots pine adaptive responses to the light spectra by measuring hypocotyl length in seeds sampled from three natural Scots pine ecotypes across a latitudinal cline ranging from 63° to 68° N in Sweden where the adaptive cline is known to be steeper. Seeds were germinated under dark (D) and three monochromatic continuous light wavelengths: blue (B), red (R) and far-red (FR). Analysis of variance revealed a northward decrease in the inhibitory effect of FR with respect to D, the so-called far red high irradiance response. Ecotypic variation for hypocotyl development was observed under the FR and D treatments, while the trends for the B and R treatments were not statistically significant. Under FR the ecotypic variation showed an increase in hypocotyl length northwards, in contrast to the treatment under D which showed a decrease in the hypocotyl length northwards. These results could be interpreted in view of the previously reported northward increase in FR requirement to maintain growth in Norway spruce and Scots pine. Prior to the performance of the main light experiment, the maternal effect on progeny performance was investigated, which showed the absence of maternal environment effect on the performance of the seedlings.