Observations of increased cloud cover over irrigated agriculture in an arid environment

Irrigated agriculture accounts for 20% of global cropland area and may alter climate locally and globally, but feedbacks on clouds and rainfall remain highly uncertain, particularly in arid regions. Non-renewable groundwater in arid regions accounts for 20% of global irrigation water demand, and quantifying these feedbacks is crucial for the prediction of long-term water use in a changing climate. Here we use satellite data to show how irrigated crops in an arid environment alter land-surface properties, cloud cover and rainfall patterns. Land surface temperatures (LST) over the cropland are 5-7 K lower than their surroundings, despite a lower albedo, suggesting that Bowen ratio is strongly reduced (and latent heat fluxes increased) over the irrigated cropland. Daytime cloud cover is increased by up to 15% points (a relative increase of 60%), with increased cloud development in the morning, and a greater afternoon peak in cloud. Cloud cover is significantly correlated with interannual variations in vegetation and LST. Afternoon rainfall also appears to be enhanced around the irrigation. The cloud feedback is the opposite of what has been previously observed in tropical and semiarid regions, suggesting different processes drive land-atmosphere feedbacks in very dry environments. Increased cloud and rainfall, and associated increases in diffuse radiation and reductions in temperature, are likely to benefit vegetation growth. Predictions of changes in crop productivity due to climate change and the impacts of global land-use change on climate and the use of water-resources would therefore benefit from including these effects

Old-Growth Forest Disturbance in the Ukrainian Carpathians

Human activity has greatly reduced the area of old-growth forest in Europe, with some of the largest remaining fragments in the Carpathian Mountains of south-western Ukraine. We used satellite image analysis to calculate old-growth forest disturbance in this region from 2010 to 2019. Over this period, we identified 1335 ha of disturbance in old-growth forest, equivalent to 1.8% of old-growth forest in the region. During 2015 to 2019, the average annual disturbance rate was 0.34%, varying with altitude, distance to settlements and location within the region. Disturbance rates were 7–8 times lower in protected areas compared to outside of protected areas. Only one third of old-growth forest is currently within protected areas; expansion of the protected area system to include more old-growth forests would reduce future loss. A 2017 law that gave protection to all old-growth forest in Ukraine had no significant impact on disturbance rates in 2018, but in 2019 disturbance rates reduced to 0.19%. Our analysis is the first indication that this new legislation may be reducing loss of old-growth forest in Ukraine

Importance of tropospheric volcanic aerosol for indirect radiative forcing of climate

Observations and models have shown that continuously degassing volcanoes have a potentially large effect on the natural background aerosol loading and the radiative state of the atmosphere. We use a global aerosol microphysics model to quantify the impact of these volcanic emissions on the cloud albedo radiative forcing under pre-industrial (PI) and present-day (PD) conditions. We find that volcanic degassing increases global annual mean cloud droplet number concentrations by 40% under PI conditions, but by only 10% under PD conditions. Consequently, volcanic degassing causes a global annual mean cloud albedo effect of −1.06 W m−2 in the PI era but only −0.56 W m−2 in the PD era. This non-equal effect is explained partly by the lower background aerosol concentrations in the PI era, but also because more aerosol particles are produced per unit of volcanic sulphur emission in the PI atmosphere. The higher sensitivity of the PI atmosphere to volcanic emissions has an important consequence for the anthropogenic cloud radiative forcing because the large uncertainty in volcanic emissions translates into an uncertainty in the PI baseline cloud radiative state. Assuming a −50/+100% uncertainty range in the volcanic sulphur flux, we estimate the annual mean anthropogenic cloud albedo forcing to lie between −1.16 W m−2 and −0.86 W m−2. Therefore, the volcanically induced uncertainty in the PI baseline cloud radiative state substantially adds to the already large uncertainty in the magnitude of the indirect radiative forcing of climate

What drives interannual variation in tree ring oxygen isotopes in the Amazon?

Oxygen isotope ratios in tree rings (δ18OTR) from northern Bolivia record local precipitation δ18O and correlate strongly with Amazon basin-wide rainfall. While this is encouraging evidence that δ18OTR can be used for palaeoclimate reconstructions, it remains unclear whether variation in δ18OTR is truly driven by within-basin processes, thus recording Amazon climate directly, or if the isotope signal may already be imprinted on incoming vapour, perhaps reflecting a pan-tropical climate signal. We use atmospheric back-trajectories combined with satellite observations of precipitation, together with water vapour transport analysis to show that δ18OTR in Bolivia are indeed controlled by basin-intrinsic processes, with rainout over the basin the most important factor. Furthermore, interannual variation in basin-wide precipitation and atmospheric circulation are both shown to affect δ18OTR. These findings suggest δ18OTR can be reliably used to reconstruct Amazon precipitation, and have implications for the interpretation of other palaeoproxy records from the Amazon basin

Synergistic Use of Sentinel-1 and Sentinel-2 to Map Natural Forest and Acacia Plantation and Stand Ages in North-Central Vietnam

Many remote sensing studies do not distinguish between natural and planted forests. We combine C-Band Synthetic Aperture Radar (Sentinel-1, S-1) and optical satellite imagery (Sentinel-2, S-2) and examine Random Forest (RF) classification of acacia plantations and natural forest in North-Central Vietnam. We demonstrate an ability to distinguish plantation from natural forest, with overall classification accuracies of 87% for S-1, and 92.5% and 92.3% for S-2 and for S-1 and S-2 combined respectively. We found that the ratio of the Short-Wave Infrared Band to the Red Band proved most effective in distinguishing acacia from natural forest. We used RF on S-2 imagery to classify acacia plantations into 6 age classes with an overall accuracy of 70%, with young plantation consistently separated from older. However, accuracy was lower at distinguishing between the older age classes. For both distinguishing plantation and natural forest, and determining plantation age, a combination of radar and optical imagery did nothing to improve classification accuracy

Aerosol size distribution and radiative forcing response to anthropogenically driven historical changes in biogenic secondary organic aerosol formation

Emissions of biogenic volatile organic compounds (BVOCs) have changed in the past millennium due to changes in land use, temperature, and CO2 concentrations. Recent reconstructions of BVOC emissions have predicted that global isoprene emissions have decreased, while monoterpene and sesquiterpene emissions have increased; however, all three show regional variability due to competition between the various influencing factors. In this work, we use two modeled estimates of BVOC emissions from the years 1000 to 2000 to test the effect of anthropogenic changes to BVOC emissions on secondary organic aerosol (SOA) formation, global aerosol size distributions, and radiative effects using the GEOS-Chem-TOMAS (Goddard Earth Observing System; TwO-Moment Aerosol Sectional) global aerosol microphysics model. With anthropogenic emissions (e.g., SO2, NOx, primary aerosols) turned off and BVOC emissions changed from year 1000 to year 2000 values, decreases in the number concentration of particles of size Dp > 80 nm (N80) of > 25% in year 2000 relative to year 1000 were predicted in regions with extensive land-use changes since year 1000 which led to regional increases in the combined aerosol radiative effect (direct and indirect) of > 0.5 W m−2 in these regions. We test the sensitivity of our results to BVOC emissions inventory, SOA yields, and the presence of anthropogenic emissions; however, the qualitative response of the model to historic BVOC changes remains the same in all cases. Accounting for these uncertainties, we estimate millennial changes in BVOC emissions cause a global mean direct effect of between +0.022 and +0.163 W m−2 and the global mean cloud-albedo aerosol indirect effect of between −0.008 and −0.056 W m−2. This change in aerosols, and the associated radiative forcing, could be a largely overlooked and important anthropogenic aerosol effect on regional climates

Identifying European Old-Growth Forests using Remote Sensing: A Study in the Ukrainian Carpathians

Old-growth forests are an important, rare and endangered habitat in Europe. The ability to identify old-growth forests through remote sensing would be helpful for both conservation and forest management. We used data on beech, Norway spruce and mountain pine old-growth forests in the Ukrainian Carpathians to test whether Sentinel-2 satellite images could be used to correctly identify these forests. We used summer and autumn 2017 Sentinel-2 satellite images comprising 10 and 20 m resolution bands to create 6 vegetation indices and 9 textural features. We used a Random Forest classification model to discriminate between dominant tree species within old-growth forests and between old-growth and other forest types. Beech and Norway spruce were identified with an overall accuracy of around 90%, with a lower performance for mountain pine (70%) and mixed forest (40%). Old-growth forests were identified with an overall classification accuracy of 85%. Adding textural features, band standard deviations and elevation data improved accuracies by 3.3%, 2.1% and 1.8% respectively, while using combined summer and autumn images increased accuracy by 1.2%. We conclude that Random Forest classification combined with Sentinel-2 images can provide an effective option for identifying old-growth forests in Europe

Determination of Structural Characteristics of Old-Growth Forest in Ukraine Using Spaceborne LiDAR

A forest’s structure changes as it progresses through developmental stages from establishment to old-growth forest. Therefore, the vertical structure of old-growth forests will differ from that of younger, managed forests. Free, publicly available spaceborne Laser Range and Detection (LiDAR) data designed for the determination of forest structure has recently become available through NASA’s General Ecosystem and Development Investigation (GEDI). We use this data to investigate the structure of some of the largest remaining old-growth forests in Europe in the Ukrainian Carpathian Mountains. We downloaded 18489 cloud-free shots in the old-growth forest (OGF) and 20398 shots in adjacent non-OGF areas during leaf-on, snow-free conditions. We found significant differences between OGF and non-OGF over a wide range of structural metrics. OGF was significantly more open, with a more complex vertical structure and thicker ground-layer vegetation. We used Random Forest classification on a range of GEDI-derived metrics to classify OGF shapefiles with an accuracy of 73%. Our work demonstrates the use of spaceborne LiDAR for the identification of old-growth forests

Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia.

Vegetation and peatland fires cause poor air quality and thousands of premature deaths across densely populated regions in Equatorial Asia. Strong El-Niño and positive Indian Ocean Dipole conditions are associated with an increase in the frequency and intensity of wildfires in Indonesia and Borneo, enhancing population exposure to hazardous concentrations of smoke and air pollutants. Here we investigate the impact on air quality and population exposure of wildfires in Equatorial Asia during Fall 2015, which were the largest over the past two decades. We performed high-resolution simulations using the Weather Research and Forecasting model with Chemistry based on a new fire emission product. The model captures the spatio-temporal variability of extreme pollution episodes relative to space- and ground-based observations and allows for identification of pollution sources and transport over Equatorial Asia. We calculate that high particulate matter concentrations from fires during Fall 2015 were responsible for persistent exposure of 69 million people to unhealthy air quality conditions. Short-term exposure to this pollution may have caused 11,880 (6,153-17,270) excess mortalities. Results from this research provide decision-relevant information to policy makers regarding the impact of land use changes and human driven deforestation on fire frequency and population exposure to degraded air quality.This research was supported in part by a L’Oréal-UNESCO UK and Ireland Fellowship For Women In Science (to PC), the Natural Environmental Research Council (NERC) through the LICS the SAMBBA project (ref. NE/J009822/1), the EPA STAR program (R835422), and the National Research Fellow Award (NRF2012NRFNRFF001-031). EB is partly supported by funding from UBoC. Further support was provided by the Lilly Endowment, Inc., through its support for the Indiana University Pervasive Technology Institute and the Indiana METACyt Initiative. This work makes use of the LandScan (2013)™ High Resolution global Population Data Set copyrighted by UT-Battelle, LLC, operator of Oak Ridge National Laboratory under Contract No. DE-AC05- 00OR22725 with the United States Department of Energy. Global Burden of Disease used in this study have been accessed from the Institute for Health Metric and Evaluation website: http://ghdx.healthdata.org/ihme_data. We gratefully acknowledge the National Environment Agency (NEA) of Singapore for collecting and providing PM2.5 and PSI data (available at http://www.nea.gov.sg/anti-pollution-radiation-protection/air-pollution-control/psi/historical-psi-readings). The National Center for Atmospheric Research is operated by the University Corporation for Atmospheric Research under the sponsorship of the National Science Foundation. We thank Louisa Emmons for providing the boundary conditions for dust from CAM-Chem. We also acknowledge the NASA scientists responsible for MODIS products, WRF-Chem developers and ACOM scientists at NCAR for useful discussion on model set-up

Airborne observations of regional variation in fluorescent aerosol across the United States

Airborne observations of fluorescent aerosol were made aboard an airship during CloudLab, a series of flights that took place in September and October of 2013 and covered a wideband of longitude across the continental U.S. between Florida and California and between 28 and 37-N latitudes. Sampling occurred from near the surface to 1000-m above the ground. A Wideband Integrated Bioaerosol Sensor (WIBS-4) measured average concentrations of supermicron fluorescent particles aloft (1-μm to 10-μm), revealing number concentrations ranging from 2.1-±-0.8 to 8.7-±-2.2-×-104 particles m-3 and representing up to 24% of total supermicron particle number. We observed distinct variations in size distributions and fluorescent characteristics in different regions, and attribute these to geographically diverse bioaerosol. Fluorescent aerosol detected in the east is largely consistent with mold spores observed in a laboratory setting, while a shift to larger sizes associated with different fluorescent patterns is observed in the west. Fluorescent bioaerosol loadings in the desert west were as high as those near the Gulf of Mexico, suggesting that bioaerosol is a substantial component of supermicron aerosol both in humid and arid environments. The observations are compared to model fungal and bacterial loading predictions, and good agreement in both particle size and concentrations is observed in the east. In the west, the model underestimated observed concentrations by a factor between 2 and 4 and the prescribed particle sizes are smaller than the observed fluorescent aerosol. A classification scheme for use with WIBS data is also presented. Key Points Fluorescent supermicron aerosol loads are reported across the southern U.S. Regional variations in fluorescent behavior and particle size are observed Comparison to modeled emissions shows an underestimate in the wes