We present simulations of an Earth system model in which launch vehicles inject gaseous and particulate combustion products into the stratosphere. We considered two plausible scenarios representative for the year 2050, one with 1000 launches per year and another with 10 times more, all of which assuming heavy lift (80 tons to low Earth orbit; LEO) launches using methane as a proxy for liquefied natural gas (LNG) fuel. An industry-standard plume flowfield model was used to predict emission of gaseous species including carbon monoxide, nitrogen oxides, and water vapor. Black carbon was introduced assuming vacuum emission equal 25% of equivalent kerosene engine. The gas emissions showed marginal or insignificant changes in atmospheric composition, while the black carbon emission was found to be the most influential component. Feedbacks involve tropopause and stratospheric warming, followed by a moistening of the stratosphere via tropospheric water vapor intrusions, together with a reduction in global albedo. The fact that LNG-fueled rockets could be a concern from aerosol emissions in our simulations, despite burning more efficiently than conventional fuels, underscores the need to better understand actual black carbon emissions from rocket engines in order to accurately predict the global impacts of launch vehicles on future climate.

In eastern Canada, Black spruce ( Picea mariana Mill. B.S.P.) grows in a wide variety of climates, from maritime-oceanic conditions near the Labrador Sea, to more continental climates, inland. Along this gradient, timing and provenance of heat and moisture that support growth are uncertain, weakening our capacity to predict the response of boreal ecosystems to climate variability. Here, we measured the stable oxygen isotopic composition of black spruce tree-ring cellulose at three sites in eastern Canada and provide evidence of a rapid decrease of Labrador Sea’s influence on adjacent ecosystems. Our results report a landwards decrease in the oxygen isotope composition of both tree-ring cellulose ( δ 18 O T R C ) and precipitation water ( δ 18 O p ). We also reveal a rapid landwards decoupling between δ 18 O T R C variability (1950-2013), maximum temperature and Sea Surface Temperature variations over the Northwest Atlantic. Thus, despite their apparent ecological homogeneity, eastern Canada’s black spruce ecosystems rely on heterogeneous sources of heat and moisture.

In August 2017, a smoke plume from wildfires in British Columbia and the Northwest Territories recirculated and persisted over northern Canada for over two weeks. We compared a full-factorial set of NASA Goddard Institute for Space Studies ModelE simulations of the plume to satellite retrievals of aerosol optical depth and carbon monoxide, finding that ModelE performance was dependent on the model configuration, and more so on the choice of injection height approach, aerosol scheme and biomass burning emissions estimates than to the choice of horizontal winds for nudging. In particular, ModelE simulations with free-tropospheric smoke injection, a mass-based aerosol scheme and high fire NOx emissions led to unrealistically high aerosol optical depth. Using paired simulations with fire emissions excluded, we estimated that for 16 days over an 850 000 km2 region, the smoke decreased planetary boundary layer heights by between 253 m and 547 m, decreased downward shortwave radiation by between 52 Wm-2 and 172 Wm-2, and decreased surface temperature by between 1.5 oC and 4.9 oC, the latter spanning an independent estimate from operational weather forecasts of a 3.7 oC cooling. The strongest surface climate effects were for ModelE configurations with more detailed aerosol microphysics that led to a stronger first indirect effect.

The Canadian Fire Weather Index (FWI) system, even though originally developed and calibrated for an upland Jack pine forest, is used globally to estimate fire danger for any fire environment. However, for some environments, such as peatlands, the applicability of the FWI in its current form, is often questioned. In this study, we replaced the original moisture codes of the FWI with hydrological estimates resulting from the assimilation of satellite-based L-band passive microwave observations into a peatland-specific land surface model. In a conservative approach that maintains the integrity of the original FWI structure, the distributions of the hydrological estimates were first matched to those of the corresponding original moisture codes before replacement. The resulting adapted FWI, hereafter called FWIpeat, was evaluated using satellite-based information on fire presence over boreal peatlands from 2010 through 2018. Adapting the FWI with model- and satellite-based hydrological information was found to be beneficial in estimating fire danger, especially when replacing the deeper moisture codes of the FWI. For late-season fires, further adaptations of the fine fuel moisture code show even more improvement due to the fact that late-season fires are more hydrologically driven. The proposed FWIpeat should enable improved monitoring of fire risk in boreal peatlands.

The new TROPESS (TRopospheric Ozone and its Precursors from Earth System Sounding) profile retrievals of carbon monoxide (CO) from the Cross-track Infrared Sounder (CrIS) are evaluated against Measurement of Pollution in the Troposphere (MOPITT) CO version 9 data. Comparison results that were adjusted to common a priori constraints in the retrieval processes have improved agreement between the two data sets over direct comparisons. TROPESS-CrIS CO profiles are within 5 % of MOPITT but have higher concentrations in the lower troposphere and lower concentrations in the upper troposphere. For the intense western US wildfire events in September 2020, we compare CO fields simulated by the GISS climate model to the two satellite CO observations. We show intermediate steps of the comparison process to illustrate the evaluation of model simulations by deriving the “retrieved” model CO profiles as they would be observed by the satellite. This includes the application of satellite level-2 data along with their corresponding diagnostic operators provided in the TROPESS-CrIS and MOPITT products. The process allows a diagnosis of potential model improvements in modeling fire emissions and pollution transport.

Abstract. The Canadian Fire Weather Index (FWI) system, even though originally developed and calibrated for an upland jack pine forest, is used globally to estimate fire danger for any fire environment. However, for some environments, such as peatlands, the applicability of the FWI in its current form, is often questioned. In this study, we replaced the original moisture codes of the FWI with hydrological estimates resulting from the assimilation of satellite-based L-band passive microwave observations into a peatland-specific land surface model. In a conservative approach that maintains the integrity of the original FWI structure, the distributions of the hydrological estimates were first matched to those of the corresponding original moisture codes before replacement. The resulting adapted FWI, hereafter called PEAT-FWI, was evaluated using fire occurrences over boreal peatlands from 2010 through 2018. Adapting the FWI with model- and satellite-based hydrological information was found to be beneficial to estimate fire danger, especially when replacing the deeper moisture codes of the FWI. For late-season fires, further adaptations of the fine fuel moisture code show even more improvement due to the fact that late-season fires are more hydrologically driven. The proposed PEAT-FWI should enable improved monitoring of fire risk in boreal peatlands.

Purpose As stated in the United Nations Global Assessment Report 2022 Concept Note, decision-makers everywhere need data and statistics that are accurate, timely, sufficiently disaggregated, relevant, accessible and easy to use. The purpose of this paper is to demonstrate scalable and replicable methods to advance and integrate the use of earth observation (EO), specifically ongoing efforts within the Group on Earth Observations (GEO) Work Programme and the Committee on Earth Observation Satellites (CEOS) Work Plan, to support risk-informed decision-making, based on documented national and subnational needs and requirements. Design/methodology/approach Promotion of open data sharing and geospatial technology solutions at national and subnational scales encourages the accelerated implementation of successful EO applications. These solutions may also be linked to specific Sendai Framework for Disaster Risk Reduction (DRR) 2015–2030 Global Targets that provide trusted answers to risk-oriented decision frameworks, as well as critical synergies between the Sendai Framework and the 2030 Agenda for Sustainable Development. This paper provides examples of these efforts in the form of platforms and knowledge hubs that leverage latest developments in analysis ready data and support evidence-based DRR measures. Findings The climate crisis is forcing countries to face unprecedented frequency and severity of disasters. At the same time, there are growing demands to respond to policy at the national and international level. EOs offer insights and intelligence for evidence-based policy development and decision-making to support key aspects of the Sendai Framework. The GEO DRR Working Group and CEOS Working Group Disasters are ideally placed to help national government agencies, particularly national Sendai focal points to learn more about EOs and understand their role in supporting DRR. Originality/value The unique perspective of EOs provide unrealized value to decision-makers addressing DRR. This paper highlights tangible methods and practices that leverage free and open source EO insights that can benefit all DRR practitioners.

Abstract Black spruce (Picea mariana Mill. B.S.P.), is a dominant species emblematic of eastern Canada's boreal forests. It grows in a vast array of climatic conditions ranging from cold maritime-oceanic climates near the Labrador Sea shore to cold continental conditions in the central portions of Quebec-Labrador. However, along the continentality gradient, timing and provenance of heat and moisture that support growth are uncertain, weakening our capacity to describe and predict the response of boreal ecosystems to climate variability. Here, we measured oxygen isotope composition in tree-ring cellulose of black spruces from three sites, and provide evidence of a direct influence of the Labrador Sea on adjacent continental ecosystems. Our results report a landwards decrease in δ18Otrc, a pattern that is also visible in the simulated oxygen isotope composition of precipitation water (δ18Op). We also reveal a landwards decoupling between δ18Otrc variability (1950-2013) and maximum temperature (Tmax) variations over the Northwest Atlantic. Our results imply that tree-ring oxygen isotopes may be of great help to circumscribe the spatial extent of Labrador Sea's influence on surrounding boreal ecosystems. Moreover, our study reveals that despite of their apparent ecological homogeneity, eastern Canada’s black spruce forests clearly rely on heterogeneous sources of heat and moisture.

The Fire Weather Index (FWI) is used worldwide to estimate the danger of wildfires. The FWI system integrates meteorological parameters and empirically combines them into several moisture codes, each representing a different fuel type. These moisture codes are then used in combination with wind speed to estimate a fire danger. Originally, the FWI system was developed for a standard jack pine forest, however, it is widely used by fire managers to assess the fire danger in different environments as well. Furthermore, it is often also used to assess the vulnerability of organic soils, such as peatlands, to ignition and depth of burn. The utility of which is often questioned. This research aims at improving the original FWI for northern peatlands by replacing parts of the original, purely weather-based FWI system with satellite-informed model estimates of peat moisture and water level. These come from a data assimilation output combining the NASA catchment model, including the peat modules PEATCLSM, and Soil Moisture and Ocean Salinity (SMOS) L-band brightness temperature observations. The predictive power of the new, peat-specific FWI (PEAT-FWI) is evaluated against the original FWI against fire data of the global fire atlas from 2010 through 2018 over the major northern peatlands areas. For the evaluation, the fires are split up in early and late season fires, as it is hypothesized that late fires are more hydrological driven, and the predictive power of the PEAT-FWI will thus differ between the two types of fires. Our results indeed indicate that the PEAT-FWI improves the predictive capability of estimating fire risk over northern peatlands in particular for late fires. By using a receiver operating characteristics (ROC) curve to evaluate the predictive power of the FWI against a random estimate, the area under the curve increases by up to 10% for the PEAT-FWI compared to the original FWI. The recent version 7 release of the operational Soil Moisture Active Passive (SMAP) Level-4 Soil Moisture Data Assimilation Product now includes PEATCLSM, thus, the proposed PEAT-FWI is straightforward to include in operational FWI products.

About half of the anthropogenic CO2 emissions remain in the atmosphere and half are taken up by the land and ocean1. If the carbon uptake by land and ocean sinks becomes less efficient, for example, owing to warming oceans2 or thawing permafrost3, a larger fraction of anthropogenic emissions will remain in the atmosphere, accelerating climate change. Changes in the efficiency of the carbon sinks can be estimated indirectly by analysing trends in the airborne fraction, that is, the ratio between the atmospheric growth rate and anthropogenic emissions of CO2 (refs. 4–10). However, current studies yield conflicting results about trends in the airborne fraction, with emissions related to land use and land cover change (LULCC) contributing the largest source of uncertainty7,11,12. Here we construct a LULCC emissions dataset using visibility data in key deforestation zones. These visibility observations are a proxy for fire emissions13,14, which are — in turn — related to LULCC15,16. Although indirect, this provides a long-term consistent dataset of LULCC emissions, showing that tropical deforestation emissions increased substantially (0.16 Pg C decade−1) since the start of CO2 concentration measurements in 1958. So far, these emissions were thought to be relatively stable, leading to an increasing airborne fraction4,5. Our results, however, indicate that the CO2 airborne fraction has decreased by 0.014 ± 0.010 decade−1 since 1959. This suggests that the combined land–ocean sink has been able to grow at least as fast as anthropogenic emissions. By generating a land use and land cover change emissions dataset using visibility data from two key deforestation regions, analysis of the data suggests a decrease in the CO2 airborne fraction since 1959.

Recent studies have shown that temperature and precipitation in the Mediterranean are expected to change, contributing to longer and more intense summer droughts that even extend out of season. In connection to this, the frequency of forest fire occurrence and intensity will likely increase. In the present study, the changes in future fire danger conditions are assessed for the different regions of Greece using the Canadian fire weather index (FWI). Gridded future climate output as estimated from three regional climate models from the Coordinated Regional Downscaling Experiment are utilized. We use three representative concentration pathways (RCPs) consisting of an optimistic emissions scenario where emissions peak and decline beyond 2020 (RCP2.6), a middle-of-the-road scenario (RCP4.5) and a pessimistic scenario, in terms of mitigation where emissions continue to rise throughout the century (RCP8.5). Based on established critical fire FWI threshold values for Greece, the future change in days with critical fire danger were calculated for different areas of Greece domains. The results show that fire danger is expected to progressively increase in the future especially in the high-end climate change scenario with southern and eastern regions of Greece expected to have up to 40 additional days of high fire danger relative to the late 20th century, on average. Crete, the Aegean Islands, the Attica region, as well as parts of Peloponnese are predicted to experience a stronger increase in fire danger.

<p>Wildfires are integral parts of ecosystems but at the same time they consist a threat for manmade and natural environments. Variability in the area burned by wildfires has been largely attributed to weather and climate drivers, hence fire danger indices such as the Canadian Fire Weather Index (FWI) uses solely climate variables. The FWI uses four climate variables (precipitation, temperature, wind and relative humidity), to estimate two sub-indices, one for the wildfire initial spread danger - the initial spread index, and one that accounts for the longer-term drought effects on the fire danger - the buildup index, from which the FWI is finally assessed. Here, we establish correlations between the individual climate variables, FWI and its subindices, with observed GFED monthly burned area, for each one of the 14 GFED pyrographic region, at a global scale. The correlations are established on aggregated by the size of burned area data, to reduce the effect of other smaller scale climate effects, as well as other socioeconomic factors such as fire suppression activities, etc. The established correlations are then used to estimate the relative sensitivity of the area burned, to each climate variable and FWI component. The analysis is repeated for different burned area land use types, i.e. forest areas, non-forest areas as well as their combination. Our results indicate the relative importance of the four climate variables, as well as the two sub-indices of FWI index, for each GFED region. The results highlight the significance of temperature and relative humidity to the variability of area burned, in many regions, globally. This work contributes to a better understanding of the climate drivers of global wildfire activity.</p><p> </p><p>This work is supported by CLIMPACT - National Research Network on Climate Change and its Impacts project, financed by the Public Investment Program of Greece and supervised by General Secretariat for Research and Technology (GSRT); and by the Leverhulme Centre for Wildfires, Environment, and Society through the Leverhulme Trust, grant number RC-2018-023.</p>

The representation of snow processes in forest growth models is necessary to accurately predict the hydrological cycle in boreal ecosystems and the isotopic signature of soil water extracted by trees, photosynthates and tree-ring cellulose. Yet, most process-based models do not include a snow module; consequently, their simulations may be biased in cold environments. Here, we modified the MAIDENiso model to incorporate a new snow module that simulates snow accumulation, melting and sublimation, as well as thermal exchanges driving freezing and thawing of the snow and the soil. We tested these implementations in two sites in eastern and western Canada for black spruce (Picea mariana (Mill.) B.S.P.) and white spruce (Picea glauca (Moench) Voss) forests, respectively. The new snow module improves the skills of the model to predict components of the hydrological cycle. The MAIDENiso model is now able to reproduce the spring discharge peak and to simulate stable oxygen isotopes in tree-ring cellulose more realistically than in the original snow-free version of the model. The new implementation also results in simulations with a higher contribution from the source water on the oxygen isotopic composition of the simulated cellulose, leading to more accurate estimates of cellulose isotopic composition. Future work may include the development of inverse modelling with this new version of MAIDENiso to produce robust reconstructions of the hydrological cycle and isotope processes in cold environments.

Wildfire is an integral part of the Earth system, but at the same time it can pose serious threats to human society and to certain types of terrestrial ecosystems. Meteorological conditions are a key driver of wildfire activity and extent, which led to the emergence of the use of fire danger indices that depend solely on weather conditions. The Canadian Fire Weather Index (FWI) is a widely used fire danger index of this kind. Here, we evaluate how well the FWI, its components, and the climate variables from which it is derived, correlate with observation-based burned area (BA) for a variety of world regions. We use a novel technique, according to which monthly BA are grouped by size for each Global Fire Emissions Database (GFED) pyrographic region. We find strong correlations of BA anomalies with the FWI anomalies, as well as with the underlying deviations from their climatologies for the four climate variables from which FWI is estimated, namely, temperature, relative humidity, precipitation, and wind. We quantify the relative sensitivity of the observed BA to each of the four climate variables, finding that this relationship strongly depends on the pyrographic region and land type. Our results indicate that the BA anomalies strongly correlate with FWI anomalies at a GFED region scale, compared to the strength of the correlation with individual climate variables. Additionally, among the individual climate variables that comprise the FWI, relative humidity and temperature are the most influential factors that affect the observed BA. Our results support the use of the composite fire danger index FWI, as well as its sub-indices, the Build-Up Index (BUI) and the Initial Spread Index (ISI), comparing to single climate variables, since they are found to correlate better with the observed forest or non-forest BA, for the most regions across the globe.

Stable oxygen isotopes measured in tree rings are useful for reconstructing climate variability and explaining changes in physiological processes occurring in forests, complementing other tree-ring parameters such as ring width. Here, we analyzed the relationships between different climate parameters and annually resolved tree-ring δ18O records (δ18OTR) from white spruce (Picea glauca [Moench]Voss) trees located near Tungsten (Northwest Territories, Canada) and used the NASA GISS ModelE2 isotopically-equipped general circulation model (GCM) to better interpret the observed relationships. We found that the δ18OTR series were primarily related to temperature variations in spring and summer, likely through temperature effects on the precipitation δ18O in spring, and evaporative enrichment at leaf level in summer. The GCM simulations showed significant positive relationships between modelled precipitation δ18O over the study region and surface temperature and geopotential height over northwestern North America, but of stronger magnitudes during fall-winter than during spring–summer. The modelled precipitation δ18O was only significantly associated with moisture transport during the fall-winter season. The δ18OTR showed similar correlation patterns to modelled precipitation δ18O only during spring–summer when water matters more for trees, with significant positive correlations with surface temperature and geopotential height, but no correlations with moisture transport. Overall, the δ18OTR records for northwestern Canada reflect the same significant large-scale climate patterns as precipitation δ18O for spring–summer, and therefore have potential for reconstructing past atmospheric dynamics in addition to temperature variability in the region.

In the absence of preventive therapies or effective treatment for most cases of coronavirus disease 2019 (COVID-19), governments worldwide have sought to minimize person-to-person severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission through a variety of lock-down measures and social distancing policies. Extreme events like the COVID-19 pandemic present a tremendous opportunity to make quantitative connections between changes in anthropogenic forcing, social and economic activity, and the related Earth system response. In this paper, we examine the air quality impacts associated with the pandemic response measures in the Northeastern United States.

In 2019, Syria experienced its largest outbreak of fires since 2003, when fire occurrence began to be monitored via the MODIS satellite instruments. Here, we combine remotely sensed data on fire, local climatic conditions, and vegetation with spatial data on violence, territorial control, and return of internally displaced persons (IDPs) to explore the underlying causes of Syria's fires at the sub-district, or ADM-3, level. We find evidence for a nuanced story: precipitation and stabilization in Kurdish-controlled territory fueled a bountiful wheat-growing year in 2019. This agricultural resurgence coincided with high fire activity, possibly revealing that people were attempting to jump-start agricultural livelihoods that were lost during the civil war. Restoration of labor forces from IDP returns was not a significant factor in this agricultural recovery. Meanwhile, most sub-districts outside Kurdish-controlled territory were free of fires, which explains the absence of a relationship between vegetation and fire. Thus, Syrian fire patterns in 2019 may be a signal of uneven stabilization, rather than destabilization.

We examined daily level-3 satellite retrievals of Atmospheric Infrared Sounder (AIRS) CO, Ozone Monitoring Instrument (OMI) SO2 and NO2, and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) over eastern China to understand how COVID-19 lockdowns affected atmospheric composition. Changes in 2020 were strongly dependent on the choice of background period since 2005 and whether trends in atmospheric composition were accounted for. Over central east China during the 23 January–8 April lockdown window, CO in 2020 was between 3 % and 12 % lower than average depending on the background period. The 2020 CO was not consistently less than expected from trends beginning between 2005 and 2016 and ending in 2019 but was 3 %–4 % lower than the background mean during the 2017–2019 period when CO changes had flattened. Similarly for AOD, 2020 was between 14 % and 30 % lower than averages beginning in 2005 and 14 %–17 % lower compared to different background means beginning in 2016. NO2 in 2020 was between 30 % and 43 % lower than the mean over different background periods and between 17 % and 33 % lower than what would be expected for trends beginning later than 2011. Relative to the 2016–2019 period when NO2 had flattened, 2020 was 30 %–33 % lower. Over southern China, 2020 NO2 was between 23 % and 27 % lower than different background means beginning in 2013, the beginning of a period of persistently lower NO2. CO over southern China was significantly higher in 2020 than what would be expected, which we suggest was partly because of an active fire season in neighboring countries. Over central east and southern China, 2020 SO2 was higher than expected, but this depended strongly on how daily regional values were calculated from individual retrievals and reflects background values approaching the retrieval detection limit. Future work over China, or other regions, needs to take into account the sensitivity of differences in 2020 to different background periods and trends in order to separate the effects of COVID-19 on air quality from previously occurring changes or from variability in other sources.