Deep learning estimation of northern hemisphere soil freeze-thaw dynamics using satellite multi-frequency microwave brightness temperature observations.

Satellite microwave sensors are well suited for monitoring landscape freeze-thaw (FT) transitions owing to the strong brightness temperature (TB) or backscatter response to changes in liquid water abundance between predominantly frozen and thawed conditions. The FT retrieval is also a sensitive climate indicator with strong biophysical importance. However, retrieval algorithms can have difficulty distinguishing the FT status of soils from that of overlying features such as snow and vegetation, while variable land conditions can also degrade performance. Here, we applied a deep learning model using a multilayer convolutional neural network driven by AMSR2 and SMAP TB records, and trained on surface (~0-5 cm depth) soil temperature FT observations. Soil FT states were classified for the local morning (6 a.m.) and evening (6 p.m.) conditions corresponding to SMAP descending and ascending orbital overpasses, mapped to a 9 km polar grid spanning a five-year (2016-2020) record and Northern Hemisphere domain. Continuous variable estimates of the probability of frozen or thawed conditions were derived using a model cost function optimized against FT observational training data. Model results derived using combined multi-frequency (1.4, 18.7, 36.5 GHz) TBs produced the highest soil FT accuracy over other models derived using only single sensor or single frequency TB inputs. Moreover, SMAP L-band (1.4 GHz) TBs provided enhanced soil FT information and performance gain over model results derived using only AMSR2 TB inputs. The resulting soil FT classification showed favorable and consistent performance against soil FT observations from ERA5 reanalysis (mean percent accuracy, MPA: 92.7%) and in situ weather stations (MPA: 91.0%). The soil FT accuracy was generally consistent between morning and afternoon predictions and across different land covers and seasons. The model also showed better FT accuracy than ERA5 against regional weather station measurements (91.0% vs. 86.1% MPA). However, model confidence was lower in complex terrain where FT spatial heterogeneity was likely beneath the effective model grain size. Our results provide a high level of precision in mapping soil FT dynamics to improve understanding of complex seasonal transitions and their influence on ecological processes and climate feedbacks, with the potential to inform Earth system model predictions.

Carbon uptake in Eurasian boreal forests dominates the high-latitude net ecosystem carbon budget.

Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003-2015) vegetation gross primary productivity (GPP), ecosystem respiration (Reco ), net ecosystem CO2 exchange (NEE; Reco - GPP), and terrestrial methane (CH4 ) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km2 flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of -850 Tg CO2 -C year-1 . Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH4 emissions from tundra and boreal wetlands (not accounting for aquatic CH4 ) were estimated at 35 Tg CH4 -C year-1 . Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.

Pan-Arctic soil moisture control on tundra carbon sequestration and plant productivity.

Long-term atmospheric CO2 concentration records have suggested a reduction in the positive effect of warming on high-latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long-term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength. In this study, we used a record of nearly 100 site-years of eddy covariance data from 11 continuous permafrost tundra sites distributed across the circumpolar Arctic to test the temperature (expressed as growing degree days, GDD) responses of gross primary production (GPP), net ecosystem exchange (NEE), and ecosystem respiration (ER) at different periods of the summer (early, peak, and late summer) including dominant tundra vegetation classes (graminoids and mosses, and shrubs). We further tested GPP, NEE, and ER relationships with soil moisture and vapor pressure deficit to identify potential moisture limitations on plant productivity and net carbon exchange. Our results show a decrease in GPP with rising GDD during the peak summer (July) for both vegetation classes, and a significant relationship between the peak summer GPP and soil moisture after statistically controlling for GDD in a partial correlation analysis. These results suggest that tundra ecosystems might not benefit from increased temperature as much as suggested by several terrestrial biosphere models, if decreased soil moisture limits the peak summer plant productivity, reducing the ability of these ecosystems to sequester carbon during the summer.

Respiratory loss during late-growing season determines the net carbon dioxide sink in northern permafrost regions.

Warming of northern high latitude regions (NHL, > 50 °N) has increased both photosynthesis and respiration which results in considerable uncertainty regarding the net carbon dioxide (CO2) balance of NHL ecosystems. Using estimates constrained from atmospheric observations from 1980 to 2017, we find that the increasing trends of net CO2 uptake in the early-growing season are of similar magnitude across the tree cover gradient in the NHL. However, the trend of respiratory CO2 loss during late-growing season increases significantly with increasing tree cover, offsetting a larger fraction of photosynthetic CO2 uptake, and thus resulting in a slower rate of increasing annual net CO2 uptake in areas with higher tree cover, especially in central and southern boreal forest regions. The magnitude of this seasonal compensation effect explains the difference in net CO2 uptake trends along the NHL vegetation- permafrost gradient. Such seasonal compensation dynamics are not captured by dynamic global vegetation models, which simulate weaker respiration control on carbon exchange during the late-growing season, and thus calls into question projections of increasing net CO2 uptake as high latitude ecosystems respond to warming climate conditions.

Exceptional heat and atmospheric dryness amplified losses of primary production during the 2020 U.S. Southwest hot drought.

Earth's ecosystems are increasingly threatened by "hot drought," which occurs when hot air temperatures coincide with precipitation deficits, intensifying the hydrological, physiological, and ecological effects of drought by enhancing evaporative losses of soil moisture (SM) and increasing plant stress due to higher vapor pressure deficit (VPD). Drought-induced reductions in gross primary production (GPP) exert a major influence on the terrestrial carbon sink, but the extent to which hotter and atmospherically drier conditions will amplify the effects of precipitation deficits on Earth's carbon cycle remains largely unknown. During summer and autumn 2020, the U.S. Southwest experienced one of the most intense hot droughts on record, with record-low precipitation and record-high air temperature and VPD across the region. Here, we use this natural experiment to evaluate the effects of hot drought on GPP and further decompose those negative GPP anomalies into their constituent meteorological and hydrological drivers. We found a 122 Tg C (>25%) reduction in GPP below the 2015-2019 mean, by far the lowest regional GPP over the Soil Moisture Active Passive satellite record. Roughly half of the estimated GPP loss was attributable to low SM (likely a combination of record-low precipitation and warming-enhanced evaporative depletion), but record-breaking VPD amplified the reduction of GPP, contributing roughly 40% of the GPP anomaly. Both air temperature and VPD are very likely to continue increasing over the next century, likely leading to more frequent and intense hot droughts and substantially enhancing drought-induced GPP reductions.

A framework to integrate innovations in invasion science for proactive management.

Invasive alien species (IAS) are a rising threat to biodiversity, national security, and regional economies, with impacts in the hundreds of billions of U.S. dollars annually. Proactive or predictive approaches guided by scientific knowledge are essential to keeping pace with growing impacts of invasions under climate change. Although the rapid development of diverse technologies and approaches has produced tools with the potential to greatly accelerate invasion research and management, innovation has far outpaced implementation and coordination. Technological and methodological syntheses are urgently needed to close the growing implementation gap and facilitate interdisciplinary collaboration and synergy among evolving disciplines. A broad review is necessary to demonstrate the utility and relevance of work in diverse fields to generate actionable science for the ongoing invasion crisis. Here, we review such advances in relevant fields including remote sensing, epidemiology, big data analytics, environmental DNA (eDNA) sampling, genomics, and others, and present a generalized framework for distilling existing and emerging data into products for proactive IAS research and management. This integrated workflow provides a pathway for scientists and practitioners in diverse disciplines to contribute to applied invasion biology in a coordinated, synergistic, and scalable manner.

Earlier snowmelt may lead to late season declines in plant productivity and carbon sequestration in Arctic tundra ecosystems.

Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO2 sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO2 sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO2 later in the season.

Evaluation of trophic state for inland waters through combining Forel-Ule Index and inherent optical properties.

Eutrophication is a severe environmental pollution problem for inland waters and poses significant threats to the water safety. Monitoring trophic state of inland waters using optical remote sensing generally requires the inversion of water quality parameters, such as chlorophyll-a, secchi depth, etc. However, the accurate inversion of these individual indicators remains challenging, while the associated retrieval errors can propagate and degrade the evaluation of trophic state. Hence, we proposed a novel monitoring method by developing a Trophic State Index (TSI) based on optical remote-sensing parameters, i.e., Forel-Ule index (FUI) and non-water absorption coefficient at 674 nm (referred to as at-w(674)) retrieved from Sentinel-3 Ocean and Land Color Instrument (OLCI) imagery. The estimated TSI showed favorable correspondence with observed water quality data, including coefficient of determination (r2 = 0.91), root mean squared error (RMSE = 5.54), and mean absolute percentage error (MAPE = 10.69%). Using the Sentinel-3 OLCI data, the proposed method also had very good performance in the field spectrum (MAPE = 5.25 % , RMSE = 3.36). The monthly trophic state evaluation also showed congruence (MAPE = 12.51 % , RMSE = 6.41) with surface water quality monthly report (SWQMR) from the Ministry of Environment and Ecology of the People's Republic of China. The monthly TSI showed favorable agreement for 23 ungauged lakes (RMSE = 7.26, MAPE = 12.78%), indicating potential utility for regional lake water quality monitoring. The proposed method was then applied to 47 other large (>50 km2) water bodies in the Middle-and-Lower watershed of Yangtze River and the Huaihe watershed to evaluate the spatial and temporal variation of trophic state from 2016 to 2020. The TSI results revealed several lakes, such as Lake Honghu and Lake Luoma, with rapidly deteriorating water quality during the study period, while other lakes show relative improvement (e.g., Xiashan Reservoir), indicating unbalanced environmental pressure over the region. Overall, this study showed promising performance and potential for satellite-based monitoring of regional aquatic environments.

Satellite Flood Inundation Assessment and Forecast Using SMAP and Landsat.

The capability and synergistic use of multisource satellite observations for flood monitoring and forecasts is crucial for improving disaster preparedness and mitigation. Here, surface fractional water cover (FW) retrievals derived from Soil Moisture Active Passive (SMAP) L-band (1.4 GHz) brightness temperatures were used for flood assessment over southeast Africa during the Cyclone Idai event. We then focused on five subcatchments of the Pungwe basin and developed a machine learning based approach with the support of Google Earth Engine for daily (24-h) forecasting of FW and 30-m inundation downscaling and mapping. The Classification and Regression Trees model was selected and trained using retrievals derived from SMAP and Landsat coupled with rainfall forecasts from the NOAA Global Forecast System. Independent validation showed that FW predictions over randomly selected dates are highly correlated (R = 0.87) with the Landsat observations. The forecast results captured the flood temporal dynamics from the Idai event; and the associated 30-m downscaling results showed inundation spatial patterns consistent with independent satellite synthetic aperture radar observations. The data-driven approach provides new capacity for flood monitoring and forecasts leveraging synergistic satellite observations and big data analysis, which is particularly valuable for data sparse regions.

Cardiometabolic risks and atherosclerotic disease in ApoE knockout mice: Effect of spinal cord injury and Salsalate anti-inflammatory pharmacotherapy.

OBJECTIVE: To test in mice with a double mutation of the ApoE gene (ApoE-/-) whether spinal cord injury (SCI) hastens the native trajectory of, and established component risks for, atherosclerotic disease (AD), and whether Salsalate anti-inflammatory pharmacotherapy attenuates the impact of SCI. METHODS: ApoE-/- mice were anesthetized and underwent a T9 laminectomy. Exposed spinal cords were given a contusion injury (70 k-dynes). Sham animals underwent all surgical procedures, excluding injury. Injured animals were randomized to 2 groups: SCI or SCI+Salsalate [120 mg/Kg/day i.p.]. Mice were serially sacrificed at 20-, 24-, and 28-weeks post-SCI, and body mass was recorded. At sacrifice, heart and aorta were harvested intact, fixed in 10% buffered formalin, cleaned and cut longitudinally for en face preparation. The aortic tree was stained with oil-red-O (ORO). AD lesion histomorphometry was calculated from the proportional area of ORO. Plasma total cholesterol, triglycerides and proatherogenic inflammatory cytokines (PAIC's) were analyzed. RESULTS: AD lesion in the aortic arch progressively increased in ApoE-/-, significant at 24- and 28-weeks. AD in SCI is significantly greater at 24- and 28-weeks compared to time-controlled ApoE-/-. Salsalate treatment attenuates the SCI-induced increase at these time points. Body mass in all SCI groups are significantly reduced compared to time-controlled ApoE-/-. Cholesterol and triglycerides are significantly higher with SCI by 24- and 28-weeks, compared to ApoE-/-, and Salsalate reduces the SCI-induced effect on cholesterol. PAIC's interleukin-1ß (IL-1ß), interleukin-6 (IL-6), tumor necrosis factor α (TNFα), monocyte chemoattractant protein-1 (MCP-1), and chemokine (C-C motif) ligand 5 (CCL-5) are significantly greater with SCI compared to ApoE-/- at varying timepoints. Salsalate confers a marginal reducing effect on PAIC's by 28-weeks compared to SCI. Regression models determine that each PAIC is a significant and positive predictor of lesion. (p's <0.05). CONCLUSIONS: SCI accelerates aortic AD and associated risk factors, and anti-inflammatory treatment may attenuate the impact of SCI on AD outcomes. PAIC's IL-1ß, IL-6, TNFα, MCP-1, and CCL-5 may be effective predictors of AD.

DroughtCast: A Machine Learning Forecast of the United States Drought Monitor.

Drought is one of the most ecologically and economically devastating natural phenomena affecting the United States, causing the U.S. economy billions of dollars in damage, and driving widespread degradation of ecosystem health. Many drought indices are implemented to monitor the current extent and status of drought so stakeholders such as farmers and local governments can appropriately respond. Methods to forecast drought conditions weeks to months in advance are less common but would provide a more effective early warning system to enhance drought response, mitigation, and adaptation planning. To resolve this issue, we introduce DroughtCast, a machine learning framework for forecasting the United States Drought Monitor (USDM). DroughtCast operates on the knowledge that recent anomalies in hydrology and meteorology drive future changes in drought conditions. We use simulated meteorology and satellite observed soil moisture as inputs into a recurrent neural network to accurately forecast the USDM between 1 and 12 weeks into the future. Our analysis shows that precipitation, soil moisture, and temperature are the most important input variables when forecasting future drought conditions. Additionally, a case study of the 2017 Northern Plains Flash Drought shows that DroughtCast was able to forecast a very extreme drought event up to 12 weeks before its onset. Given the favorable forecasting skill of the model, DroughtCast may provide a promising tool for land managers and local governments in preparing for and mitigating the effects of drought.

Interannual variability of ecosystem iso/anisohydry is regulated by environmental dryness.

●Plants are characterized by the iso/anisohydry continuum depending on how they regulate leaf water potential (ΨL ). However, how iso/anisohydry changes over time in response to year-to-year variations in environmental dryness and how such responses vary across different regions remains poorly characterized. ●We investigated how dryness, represented by aridity index, affects the interannual variability of ecosystem iso/anisohydry at the regional scale, estimated using satellite microwave vegetation optical depth (VOD) observations. This ecosystem-level analysis was further complemented with published field observations of species-level ΨL . ●We found different behaviors in the directionality and sensitivity of isohydricity (σ) with respect to the interannual variation of dryness in different ecosystems. These behaviors can largely be differentiated by the average dryness of the ecosystem itself: in mesic ecosystems, σ decreases in drier years with a higher sensitivity to dryness; in xeric ecosystems, σ increases in drier years with a lower sensitivity to dryness. These results were supported by the species-level synthesis. ●Our study suggests that how plants adjust their water use across years - as revealed by their interannual variability in isohydricity - depends on the dryness of plants' living environment. This finding advances our understanding of plant responses to drought at regional scales.

Increasing riverine heat influx triggers Arctic sea ice decline and oceanic and atmospheric warming.

Arctic river discharge increased over the last several decades, conveying heat and freshwater into the Arctic Ocean and likely affecting regional sea ice and the ocean heat budget. However, until now, there have been only limited assessments of riverine heat impacts. Here, we adopted a synthesis of a pan-Arctic sea ice-ocean model and a land surface model to quantify impacts of river heat on the Arctic sea ice and ocean heat budget. We show that river heat contributed up to 10% of the regional sea ice reduction over the Arctic shelves from 1980 to 2015. Particularly notable, this effect occurs as earlier sea ice breakup in late spring and early summer. The increasing ice-free area in the shelf seas results in a warmer ocean in summer, enhancing ocean-atmosphere energy exchange and atmospheric warming. Our findings suggest that a positive river heat-sea ice feedback nearly doubles the river heat effect.

Monitoring Crop Status in the Continental United States Using the SMAP Level-4 Carbon Product.

Accurate monitoring of crop condition is critical to detect anomalies that may threaten the economic viability of agriculture and to understand how crops respond to climatic variability. Retrievals of soil moisture and vegetation information from satellite-based remote-sensing products offer an opportunity for continuous and affordable crop condition monitoring. This study compared weekly anomalies in accumulated gross primary production (GPP) from the SMAP Level-4 Carbon (L4C) product to anomalies calculated from a state-scale weekly crop condition index (CCI) and also to crop yield anomalies calculated from county-level yield data reported at the end of the season. We focused on barley, spring wheat, corn, and soybeans cultivated in the continental United States from 2000 to 2018. We found that consistencies between SMAP L4C GPP anomalies and both crop condition and yield anomalies increased as crops developed from the emergence stage (r: 0.4-0.7) and matured (r: 0.6-0.9) and that the agreement was better in drier regions (r: 0.4-0.9) than in wetter regions (r: -0.8-0.4). The L4C provides weekly GPP estimates at a 1-km scale, permitting the evaluation and tracking of anomalies in crop status at higher spatial detail than metrics based on the state-level CCI or county-level crop yields. We demonstrate that the L4C GPP product can be used operationally to monitor crop condition with the potential to become an important tool to inform decision-making and research.

Prolonged Heightened Blood Pressure Following Mechanical Thrombectomy for Acute Stroke is Associated with Worse Outcomes.

BACKGROUND: Most data evaluating the relationship of post-mechanical thrombectomy (MT) blood pressure (BP) management and outcomes of patients with large vessel occlusion (LVO) focus on early BP control within the first 24 h. We investigated the correlation of daily BP trends up to the third day following MT with patient outcomes. METHODS: We retrospectively reviewed our prospectively maintained database for LVO patients treated with MT from February 2015 to December 2017. Recorded BP values for 72 h post-reperfusion were reviewed. Daily peak systolic and diastolic blood pressures (SBP, DBP) were extracted for each day post-procedure. The association and importance between BP increments of 10 mmHg and mortality, hemorrhage, and functional independence (FI = mRS ≤ 2) was analyzed in a multivariable logistic regression and random forest (RF) analyses modeling. RESULTS: A total of 212 thrombectomies were included. An increase in peak 24-h SBP was independently associated with higher likelihood of symptomatic hemorrhage (OR 1.2, p = 0.048) and decreased functional independence (OR 0.85, p = 0.03). Higher day 2 and day 3 peak SBP was strongly correlated with decreased functional independence and higher mortality. Third day SBP < 140 was independently associated with higher likelihood of functional independence (OR 4.3, p = 0.0004). Post-MT patients with and without functional independence demonstrated a similar relative decrease in peak SBP between the first 2 days following thrombectomy (p = 0.26); however, those without functional independence experienced a significant rebound increase in peak SBP on the third day following MT (mean change from day 2 to 3: FI - 3.5 mmHg, non-FI + 3.9 mmHg; p = 0.005). CONCLUSION: High daily maximum SBP and a rebound SBP on the third day following MT is independently associated with increased likelihood of functional dependence.

Increased high-latitude photosynthetic carbon gain offset by respiration carbon loss during an anomalous warm winter to spring transition.

Arctic and boreal ecosystems play an important role in the global carbon (C) budget, and whether they act as a future net C sink or source depends on climate and environmental change. Here, we used complementary in situ measurements, model simulations, and satellite observations to investigate the net carbon dioxide (CO2 ) seasonal cycle and its climatic and environmental controls across Alaska and northwestern Canada during the anomalously warm winter to spring conditions of 2015 and 2016 (relative to 2010-2014). In the warm spring, we found that photosynthesis was enhanced more than respiration, leading to greater CO2 uptake. However, photosynthetic enhancement from spring warming was partially offset by greater ecosystem respiration during the preceding anomalously warm winter, resulting in nearly neutral effects on the annual net CO2 balance. Eddy covariance CO2 flux measurements showed that air temperature has a primary influence on net CO2 exchange in winter and spring, while soil moisture has a primary control on net CO2 exchange in the fall. The net CO2 exchange was generally more moisture limited in the boreal region than in the Arctic tundra. Our analysis indicates complex seasonal interactions of underlying C cycle processes in response to changing climate and hydrology that may not manifest in changes in net annual CO2 exchange. Therefore, a better understanding of the seasonal response of C cycle processes may provide important insights for predicting future carbon-climate feedbacks and their consequences on atmospheric CO2 dynamics in the northern high latitudes.

Readmission and reinjury patterns in pediatric assault victims.

INTRODUCTION: Repeated pediatric assault should be a never event. The purpose of this study was to evaluate the readmission and reinjury patterns in pediatric victims of assault including readmissions to different hospitals across the US. METHODS: The 2010-2014 Nationwide Readmissions Database was queried for all nonelective admissions for patients under the age of 18 years. Primary outcomes were readmission or reinjury within 1 year. Results were weighted for national estimates. RESULTS: Assault-related injury occurred in 46,294 pediatric patients with 11.4% of patients being readmitted within 1 year. Of those readmitted, 35.2% presented to a different hospital. Reinjury within 1 year occurred in about 1% of patients, with 14.8% of those presenting to a different hospital. Age < 13 years, firearm-injury, ISS > 15, female gender, and leaving AMA were found to be independent prognostic indicators of readmission within 1 year among pediatric assault patients. CONCLUSION: Care of children who are admitted and discharged for assault injuries is more fragmented that previously thought. Quality metrics fail to capture this previously hidden population. Our results identify treatable factors which could improve the care of children after assault.

Large loss of CO2 in winter observed across the northern permafrost region.

Recent warming in the Arctic, which has been amplified during the winter1-3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is highly uncertain and has not been well represented by ecosystem models or by empirically-based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1662 Tg C yr-1 from the permafrost region during the winter season (October through April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1032 Tg C yr-1). Extending model predictions to warmer conditions in 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway (RCP) 4.5-and 41% under business-as-usual emissions scenario-RCP 8.5. Our results provide a new baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.

Global Satellite Retrievals of the Near-Surface Atmospheric Vapor Pressure Deficit from AMSR-E and AMSR2.

Near-surface atmospheric Vapor Pressure Deficit (VPD) is a key environmental variable affecting vegetation water stress, evapotranspiration, and atmospheric moisture demand. Although VPD is readily derived from in situ standard weather station measurements, more spatially continuous global observations for regional monitoring of VPD are lacking. Here, we document a new method to estimate daily (both a.m. and p.m.) global land surface VPD at a 25-km resolution using a satellite passive microwave remotely sensed Land Parameter Data Record (LPDR) derived from the Advanced Microwave Scanning Radiometer (AMSR) sensors. The AMSR-derived VPD record shows strong correspondence (correlation coefficient ≥ 0.80, p-value < 0.001) and overall good performance (0.48 kPa ≤ Root Mean Square Error ≤ 0.69 kPa) against independent VPD observations from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data. The estimated AMSR VPD retrieval uncertainties vary with land cover type, satellite observation time, and underlying LPDR data quality. These results provide new satellite capabilities for global mapping and monitoring of land surface VPD dynamics from ongoing AMSR2 operations. Overall good accuracy and similar observations from both AMSR2 and AMSR-E allow for the development of climate data records documenting recent (from 2002) VPD trends and potential impacts on vegetation, land surface evaporation, and energy budgets.

Assessing global surface water inundation dynamics using combined satellite information from SMAP, AMSR2 and Landsat.

A method to assess global land surface water (fw) inundation dynamics was developed by exploiting the enhanced fw sensitivity of L-band (1.4 GHz) passive microwave observations from the Soil Moisture Active Passive (SMAP) mission. The L-band fw (fwLBand ) retrievals were derived using SMAP H-polarization brightness temperature (Tb ) observations and predefined L-band reference microwave emissivities for water and land endmembers. Potential soil moisture and vegetation contributions to the microwave signal were represented from overlapping higher frequency Tb observations from AMSR2. The resulting fwLBand global record has high temporal sampling (1-3 days) and 36-km spatial resolution. The fwLBand annual averages corresponded favourably (R=0.85, p-value<0.001) with a 250-m resolution static global water map (MOD44W) aggregated at the same spatial scale, while capturing significant inundation variations worldwide. The monthly fwLBand averages also showed seasonal inundation changes consistent with river discharge records within six major US river basins. An uncertainty analysis indicated generally reliable fwLBand performance for major land cover areas and under low to moderate vegetation cover, but with lower accuracy for detecting water bodies covered by dense vegetation. Finer resolution (30-m) fwLBand results were obtained for three sub-regions in North America using an empirical downscaling approach and ancillary global Water Occurrence Dataset (WOD) derived from the historical Landsat record. The resulting 30-m fwLBand retrievals showed favourable spatial accuracy for water (commission error 31.46%, omission error 30.20%) and land (commission error 0.87%, omission error 0.96%) classifications and seasonal wet and dry periods when compared to independent water maps derived from Landsat-8 imagery. The new fwLBand algorithms and continuing SMAP and AMSR2 operations provide for near real-time, multi-scale monitoring of global surface water inundation dynamics and potential flood risk.