Soil respiration is one of the dominant fluxes of CO2 from terrestrial ecosystems to the atmosphere. Accurate quantification of soil respiration is essential for robust projection of future climate variation and for reliable estimation of paleoatmospheric CO2 levels using soil carbonates. Soil-respired CO2, which is the most uncertain factor in estimating atmospheric CO2 concentration, has been calculated from modern observations of surface soils and from proxy indicators of paleosols formed during time periods of known atmospheric CO2. However, these estimations provide a wide range of S(z) values from past to present. To directly compare modern observation with past estimation, here we first monitored soil CO2 profiles in a Holocene profile on the western Chinese Loess Plateau (CLP) for two years, providing direct measurements of soil-respired (CO2 )at the depth where carbonate nodules likely formed. We then collected carbonate nodules below last interglacial paleosol (S1) from two N-S-aligned transects across the CLP to back-calculate soil-respired CO2. The mean back-calculated S(z) from S1 carbonate nodules vary from 539 +/- 87 ppm to 848 +/- 170 ppm in the sections on the northwestern and southeastern CLP, respectively. The mean value of directly measured soil-respired CO2 on the western CLP is 572 + 273 ppm before the onset of summer monsoon, consistent with the back-calculated S(z) in northwestern sections. Our results suggest that spatial S(z) variations are mainly controlled by monsoonal precipitation during the summer season on the CLP. To better constrain the high end of S(z), more monitoring work is needed in higher precipitation areas on the southeastern CLP.

Ambient fine particulate matter (PM2.5) concentrations in India frequently exceed 100 mu g/m(3) during fall and winter pollution episodes. We use the GEOS-Chem chemical transport model with the TwO-Moment Aerosol Sectional microphysics scheme with 15 size bins (TOMAS15) to assess PM2.5 composition and impacts on radiation and cloud condensation nuclei (CCN) during pollution episodes as compared to the seasonal (October-December) average. We conduct high resolution (0.25 degrees x 0.3125 degrees) nested-domain simulations over India for short-duration, high-PM2.5 episodes in the fall of 2015 and 2017. The simulations capture the magnitude and spatial patterns of pollution episodes measured by surface monitors (r(PM2.5)(2) = 0.69) although aerosol optical depth is underestimated. During the episodes, near-surface organic matter (OM), black carbon (BC), and secondary inorganic aerosol concentrations increase from seasonal averages by up to 36, 7, and 7 mu g/m(3), respectively. Episodic aerosol increases enhance cooling by lowering the top-of-atmosphere clear-sky direct radiative effect (DRETOA) during the 2015 episode (-6 W/m(2)), with a smaller impact during the 2017 episode (-1 W/m(2)). Differences in DRETOA reflect larger increases in scattering aerosols in the column during the 2015 episode (+17 mg/m(2)) than in 2017 (+13 mg/m(2)), while absorbing aerosol column enhancements are smaller (+3 mg/m(2)) in both years. Changes in shortwave radiation at the surface (SWsfc) are spatially similar to DRETOA and mostly negative during both episodes. CCN enhancements (0.2% supersaturation) during these episodes occur across the western Indo-Gangetic Plain, coincident with higher PM2.5 concentrations. Changes in DRETOA, SWsfc, and CCN during high-PM2.5 episodes may have implications for crops, the hydrologic cycle, and surface temperature.

Aeolian landscapes dominate the semiarid dune fields across the Asian summer monsoonal boundary (ASMB) of northern China, where the widespread palaeosols are usually regarded as indicators of enhanced monsoonal precipitation (moisture) during the Late Quaternary. However, the processes of palaeosol development, and their response to climate change, remain controversial due to the complex land-atmosphere interactions within different bioclimatic zones. Here, we review the patterns of palaeosol development, precipitation/moisture (P/ M) evolution, and lake level fluctuations across different sub-regions of the ASMB. With the aid of typical temperature and vegetation records, we qualitatively and quantitatively distinguish the contributions of different climatic factors to palaeosol development since 20 ka (1 ka = 1000 cal yr BP) and elucidate the underlying mechanisms. Our results indicate an asynchronous pattern of palaeosol development, with optimum develop-ment during 10-4, 8-4, and 6-2 ka in northeastern (NE) China, north central (NC) China, and on the NE Qinghai -Tibetan Plateau (QTP), respectively. This implies a transmeridional asynchronous pattern of palaeosol devel-opment on the scale of the ASMB. Our qualitative and quantitative analysis of the contributions of climatic variables elucidates the various relationships between palaeosol development and the climatic background across different sub-regions of the ASMB. The results demonstrate that temperature and precipitation are the dominant factors for palaeosol development in NE and NC China, respectively; whereas effective moisture, rather than temperature and precipitation alone, controls palaeosol development on the NE QTP, demonstrating different pedogenic responses against the same overall climatic background. These mechanisms are supported by the results of multiple studies of Holocene vegetation evolution and the associated climatic conditions. We conclude that the asynchronous pattern of palaeosol development across the ASMB was caused by variations in different dominant climatic factors, highlighting the diverse and complex interactions of climate change and Earth surface processes, even within the relatively uniform climatic environment of semiarid northern China. Our findings emphasize the differing responses of palaeosol development to regional climate change and provide new insights into the interactions of the land-atmosphere system in the critical zone of northern China.

As the amplifier of global climate change, climate warming exerts an important impact on the freezing/thawing cycles of soil over the Tibetan Plateau, and it shapes the trend of permafrost degradation. Intensified frozen soil collapse causes severe effects on ecosystem water and energy balance as well as on carbon cycle. Previous studies have focused on the direct effects of climate change on permafrost degradation. However, there is also growing evidence showing vegetation growth can affect regional climate system, and consequently we hypothesize that vegetation autumn phenology (i.e., the end of the growing season, EOS) may influence the start date of frozen (SOF) through feedbacks to regional climates. Using satellite greenness data derived EOS and the microwave remote sensing generated SOFESDR (freeze-thaw Earth system data record) over 2001-2018, we showed a dominant-negative (13.1% vs. 0.9%) relationship between SOFESDR and EOS, suggesting an earlier SOFESDR with a delayed EOS. We found that biogeophysical indicators served as potential connections, including surface al-bedo, soil temperature, soil water content, and evapotranspiration, for the observed relationship. We therefore proposed a new site-level SOFf(EOS)xESDR algorithm based on the EOS-SOF relationship. With ground SOFALT observed from the active layer thickness at 63 sites over Tibetan Plateau, the new model provided significantly improved estimates of SOF with Pearson's correlation coefficient (R) of 0.84 and root mean square error (RMSE) of 7.63 days, comapred with current remote sensing-based SOF product (R = 0.26, RMSE = 22.60 days). We further proposed a look-up table approach to map the SOF over TP and found an overall earlier SOF (24.0 +/- 15.8) than current SOFESDR products. Therefore, our results identified a significant correlation between the autumn phenology and the SOF variability, highlighting the importance of feedbacks of autumn phenology on climate change.

Climate-driven permafrost thaw alters the strongly coupled carbon and nitrogen cycles within the Arctic tundra, influencing the availability of limiting nutrients including nitrate (NO3-). Researchers have identified two primary mechanisms that increase nitrogen and NO3- availability within permafrost soils: (1) the 'frozen feast', where previously frozen organic material becomes available as it thaws, and (2) 'shrubification', where expansion of nitrogen-fixing shrubs promotes increased soil nitrogen. Through the synthesis of original and previously published observational data, and the application of multiple geospatial approaches, this study investigates and highlights a third mechanism that increases NO3- availability: the hydrogeomorphic evolution of polygonal permafrost landscapes. Permafrost thaw drives changes in microtopography, increasing the drainage of topographic highs, thus increasing oxic conditions that promote NO3- production and accumulation. We extrapolate relationships between NO3- and soil moisture in elevated topographic features within our study area and the broader Alaskan Coastal Plain and investigate potential changes in NO3- availability in response to possible hydrogeomorphic evolution scenarios of permafrost landscapes. These approximations indicate that such changes could increase Arctic tundra NO3- availability by similar to 250-1000%. Thus, hydrogeomorphic changes that accompany continued permafrost degradation in polygonal permafrost landscapes will substantially increase soil pore water NO3- availability and boost future fertilization and productivity in the Arctic.

Detailed examination of the impact of modern space launches on the Earth's atmosphere is crucial, given booming investment in the space industry and an anticipated space tourism era. We develop air pollutant emissions inventories for rocket launches and re-entry of reusable components and debris in 2019 and for a speculative space tourism scenario based on the recent billionaire space race. This we include in the global GEOS-Chem model coupled to a radiative transfer model to determine the influence on stratospheric ozone (O-3) and climate. Due to recent surge in re-entering debris and reusable components, nitrogen oxides from re-entry heating and chlorine from solid fuels contribute equally to all stratospheric O-3 depletion by contemporary rockets. Decline in global stratospheric O-3 is small (0.01%), but reaches 0.15% in the upper stratosphere (similar to 5 hPa, 40 km) in spring at 60-90 degrees N after a decade of sustained 5.6% a(-1) growth in 2019 launches and re-entries. This increases to 0.24% with a decade of emissions from space tourism rockets, undermining O-3 recovery achieved with the Montreal Protocol. Rocket emissions of black carbon (BC) produce substantial global mean radiative forcing of 8 mW m(-2) after just 3 years of routine space tourism launches. This is a much greater contribution to global radiative forcing (6%) than emissions (0.02%) of all other BC sources, as radiative forcing per unit mass emitted is similar to 500 times more than surface and aviation sources. The O-3 damage and climate effect we estimate should motivate regulation of an industry poised for rapid growth.

Floods are a widespread natural disaster with substantial economic implications and far-reaching consequences. In Northern Pakistan, the Hunza-Nagar valley faces vulnerability to floods, posing significant challenges to its sustainable development. This study aimed to evaluate flood risk in the region by employing a GIS-based Multi-Criteria Decision Analysis (MCDA) approach and big climate data records. By using a comprehensive flood risk assessment model, a flood hazard map was developed by considering nine influential factors: rainfall, regional temperature variation, distance to the river, elevation, slope, Normalized difference vegetation index (NDVI), Topographic wetness index (TWI), land use/land cover (LULC), curvature, and soil type. The analytical hierarchy process (AHP) analysis assigned weights to each factor and integrated with geospatial data using a GIS to generate flood risk maps, classifying hazard levels into five categories. The study assigned higher importance to rainfall, distance to the river, elevation, and slope compared to NDVI, TWI, LULC, curvature, and soil type. The weighted overlay flood risk map obtained from the reclassified maps of nine influencing factors identified 6% of the total area as very high, 36% as high, 41% as moderate, 16% as low, and 1% as very low flood risk. The accuracy of the flood risk model was demonstrated through the Receiver Operating Characteristics-Area Under the Curve (ROC-AUC) analysis, yielding a commendable prediction accuracy of 0.773. This MCDA approach offers an efficient and direct means of flood risk modeling, utilizing fundamental GIS data. The model serves as a valuable tool for decision-makers, enhancing flood risk awareness and providing vital insights for disaster management authorities in the Hunza-Nagar Valley. As future developments unfold, this study remains an indispensable resource for disaster preparedness and management in the Hunza-Nagar Valley region.

The absorption characteristics and source processes of aerosols are investigated at two nearby distinct altitude sites: Nainital, located over the central Himalayas (similar to 1958m amsl) and Pantnagar, in the adjacent foothill region (similar to 231m amsl) in the Indo-Gangetic Plain region (IGP); based on in-situ measurements and model (GEOS-Chem) simulations. The study reveals the significant influence of biomass burning sources over both the locations during spring, indicating the efficiency of the vertical transport of biomass burning aerosols during the peak of the fire activity period over the northern Indian region. On the other hand, the dominance of fossil fuel emission sources is seen during most part of the year at the mountain site, while biomass/biofuel sources are prevalent at the foothill site. Simulations of different aerosol components in the GEOS-Chem model have revealed that dust aerosols, in addition to carbonaceous aerosols from fossil fuel and biomass burning sources, significantly influence aerosol burden over this broad region covering both high-altitude site Nainital and adjacent foothill site Pantnagar in IGP. Examination of dominant aerosol types and their contribution to the columnar abundance of aerosols is performed. During spring, the contribution of dust aerosols is as high as 22%, even though inorganic aerosols (42%), organic carbon (29%) play a dominant role in modulating aerosol absorption characteristics in the column over this region. This study highlights the importance of absorbing aerosol, their types and quantification for better estimates of radiative forcing of aerosols over this region. This might also provide valuable information for the regional impact assessment of aerosols over the Himalayan region.

The Arctic is experiencing an unprecedented rate of environmental and climate change. The active layer ( the uppermost layer of soil between the atmosphere and permafrost that freezes in winter and thaws in summer) is sensitive to both climatic and environmental changes, and plays an important role in the functioning, planning, and economic activities of Arctic human and natural ecosystems. This study develops a methodology for modeling and estimating spatial-temporal variations in active layer thickness ( ALT) using data from several sites of the Circumpolar Active Layer Monitoring network, and demonstrates its use in spatial-temporal interpolation. The simplest model's stochastic component exhibits no spatial or spatio-temporal dependency and is referred to as the naive model, against which we evaluate the performance of the other models, which assume that the stochastic component exhibits either spatial or spatio-temporal dependency. The methods used to fit the models are then discussed, along with point forecasting. We compare the predicted fit of the various models at key study sites located in the North Slope of Alaska and demonstrate the advantages of space-time models through a series of error statistics such as mean squared error, mean absolute and percent deviance from observed data. We find the difference in performance between the spatio-temporal and remaining models is significant for all three error statistics. The best stochastic spatio-temporal model increases predictive accuracy, compared to the naive model, of 33.3%, 36.2% and 32.5% on average across the three error metrics at the key sites for a one-year hold out period.

Environmental factors that affect the activity-inactivity variation of periglacial features may differ from those factors that control the distributional patterns of active features. To explore this potential difference, a statistically based modelling approach and comprehensive data on active and inactive cryoturbation and solifluction features from a subarctic area of Finnish Lapland are investigated at a landscape scale. In the cryoturbation modelling, vegetation abundance is the most important environmental variable explaining both the activity-inactivity variation and the distribution of active sites. The next most important variables are soil moisture and (micro)climatological conditions in the activity modelling, and slope angle and ground material in the distribution modelling. For solifluction, the key variables determining the activity-inactivity variation are mean annual air temperature and mean maximum snow depth, whereas vegetation abundance and slope angle control the distribution of active sites. Comparison between the environmental conditions of active and inactive periglacial features may provide new insights into activity-environment relationships, which in turn are valuable when the effects of climate change on periglacial processes are explored. Copyright (c) 2014 John Wiley & Sons, Ltd.