Earth System Science Interdisciplinary Center

Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. Such changes in land use have enabled humans to appropriate an increasing share of the planet's resources, but they also potentially undermine the capacity of ecosystems to sustain food production, maintain freshwater and forest resources, regulate climate and air quality, and ameliorate infectious diseases. We face the challenge of managing trade-offs between immediate human needs and maintaining the capacity of the biosphere to provide goods and services in the long term.

The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) is the latest atmospheric reanalysis of the modern satellite era produced by NASA's Global Modeling and Assimilation Office (GMAO). MERRA-2 assimilates observation types not available to its predecessor, MERRA, and includes updates to the Goddard Earth Observing System (GEOS) model and analysis scheme so as to provide a viable ongoing climate analysis beyond MERRA's terminus. While addressing known limitations of MERRA, MERRA-2 is also intended to be a development milestone for a future integrated Earth system analysis (IESA) currently under development at GMAO. This paper provides an overview of the MERRA-2 system and various performance metrics. Among the advances in MERRA-2 relevant to IESA are the assimilation of aerosol observations, several improvements to the representation of the stratosphere including ozone, and improved representations of cryospheric processes. Other improvements in the quality of MERRA-2 compared with MERRA include the reduction of some spurious trends and jumps related to changes in the observing system, and reduced biases and imbalances in aspects of the water cycle. Remaining deficiencies are also identified. Production of MERRA-2 began in June 2014 in four processing streams, and converged to a single near-real time stream in mid 2015. MERRA-2 products are accessible online through the NASA Goddard Earth Sciences Data Information Services Center (GES DISC).

Abstract The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. Focusing on the satellite era, from 1979 to the present, MERRA has achieved its goals with significant improvements in precipitation and water vapor climatology. Here, a brief overview of the system and some aspects of its performance, including quality assessment diagnostics from innovation and residual statistics, is given. By comparing MERRA with other updated reanalyses [the interim version of the next ECMWF Re-Analysis (ERA-Interim) and the Climate Forecast System Reanalysis (CFSR)], advances made in this new generation of reanalyses, as well as remaining deficiencies, are identified. Although there is little difference between the new reanalyses in many aspects of climate variability, substantial differences remain in poorly constrained quantities such as precipitation and surface fluxes. These differences, due to variations both in the models and in the analysis techniques, are an important measure of the uncertainty in reanalysis products. It is also found that all reanalyses are still quite sensitive to observing system changes. Dealing with this sensitivity remains the most pressing challenge for the next generation of reanalyses. Production has now caught up to the current period and MERRA is being continued as a near-real-time climate analysis. The output is available online through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC).

Abstract Two new high-resolution sea surface temperature (SST) analysis products have been developed using optimum interpolation (OI). The analyses have a spatial grid resolution of 0.25° and a temporal resolution of 1 day. One product uses the Advanced Very High Resolution Radiometer (AVHRR) infrared satellite SST data. The other uses AVHRR and Advanced Microwave Scanning Radiometer (AMSR) on the NASA Earth Observing System satellite SST data. Both products also use in situ data from ships and buoys and include a large-scale adjustment of satellite biases with respect to the in situ data. Because of AMSR’s near-all-weather coverage, there is an increase in OI signal variance when AMSR is added to AVHRR. Thus, two products are needed to avoid an analysis variance jump when AMSR became available in June 2002. For both products, the results show improved spatial and temporal resolution compared to previous weekly 1° OI analyses. The AVHRR-only product uses Pathfinder AVHRR data (currently available from January 1985 to December 2005) and operational AVHRR data for 2006 onward. Pathfinder AVHRR was chosen over operational AVHRR, when available, because Pathfinder agrees better with the in situ data. The AMSR–AVHRR product begins with the start of AMSR data in June 2002. In this product, the primary AVHRR contribution is in regions near land where AMSR is not available. However, in cloud-free regions, use of both infrared and microwave instruments can reduce systematic biases because their error characteristics are independent.

Abstract The monthly global 2° × 2° Extended Reconstructed Sea Surface Temperature (ERSST) has been revised and updated from version 4 to version 5. This update incorporates a new release of ICOADS release 3.0 (R3.0), a decade of near-surface data from Argo floats, and a new estimate of centennial sea ice from HadISST2. A number of choices in aspects of quality control, bias adjustment, and interpolation have been substantively revised. The resulting ERSST estimates have more realistic spatiotemporal variations, better representation of high-latitude SSTs, and ship SST biases are now calculated relative to more accurate buoy measurements, while the global long-term trend remains about the same. Progressive experiments have been undertaken to highlight the effects of each change in data source and analysis technique upon the final product. The reconstructed SST is systematically decreased by 0.077°C, as the reference data source is switched from ship SST in ERSSTv4 to modern buoy SST in ERSSTv5. Furthermore, high-latitude SSTs are decreased by 0.1°–0.2°C by using sea ice concentration from HadISST2 over HadISST1. Changes arising from remaining innovations are mostly important at small space and time scales, primarily having an impact where and when input observations are sparse. Cross validations and verifications with independent modern observations show that the updates incorporated in ERSSTv5 have improved the representation of spatial variability over the global oceans, the magnitude of El Niño and La Niña events, and the decadal nature of SST changes over 1930s–40s when observation instruments changed rapidly. Both long- (1900–2015) and short-term (2000–15) SST trends in ERSSTv5 remain significant as in ERSSTv4.

A new technique is presented in which half-hourly global precipitation estimates derived from passive microwave satellite scans are propagated by motion vectors derived from geostationary satellite infrared data. The Climate Prediction Center morphing method (CMORPH) uses motion vectors derived from half-hourly interval geostationary satellite IR imagery to propagate the relatively high quality precipitation estimates derived from passive microwave data. In addition, the shape and intensity of the precipitation features are modified (morphed) during the time between microwave sensor scans by performing a time-weighted linear interpolation. This process yields spatially and temporally complete microwave-derived precipitation analyses, independent of the infrared temperature field. CMORPH showed substantial improvements over both simple averaging of the microwave estimates and over techniques that blend microwave and infrared information but that derive estimates of precipitation from infrared data when passive microwave information is unavailable. In particular, CMORPH outperforms these blended techniques in terms of daily spatial correlation with a validating rain gauge analysis over Australia by an average of 0.14, 0.27, 0.26, 0.22, and 0.20 for April, May, June–August, September, and October 2003, respectively. CMORPH also yields higher equitable threat scores over Australia for the same periods by an average of 0.11, 0.14, 0.13, 0.14, and 0.13. Over the United States for June–August, September, and October 2003, spatial correlation was higher for CMORPH relative to the average of the same techniques by an average of 0.10, 0.13, and 0.13, respectively, and equitable threat scores were higher by an average of 0.06, 0.09, and 0.10, respectively.

Abstract Observations of sea surface and land–near-surface merged temperature anomalies are used to monitor climate variations and to evaluate climate simulations; therefore, it is important to make analyses of these data as accurate as possible. Analysis uncertainty occurs because of data errors and incomplete sampling over the historical period. This manuscript documents recent improvements in NOAA’s merged global surface temperature anomaly analysis, monthly, in spatial 5° grid boxes. These improvements allow better analysis of temperatures throughout the record, with the greatest improvements in the late nineteenth century and since 1985. Improvements in the late nineteenth century are due to improved tuning of the analysis methods. Beginning in 1985, improvements are due to the inclusion of bias-adjusted satellite data. The old analysis (version 2) was documented in 2005, and this improved analysis is called version 3.

The growth rate of atmospheric carbon dioxide (CO2) concentrations since industrialization is characterized by large interannual variability, mostly resulting from variability in CO2 uptake by terrestrial ecosystems (typically termed carbon sink). However, the contributions of regional ecosystems to that variability are not well known. Using an ensemble of ecosystem and land-surface models and an empirical observation-based product of global gross primary production, we show that the mean sink, trend, and interannual variability in CO2 uptake by terrestrial ecosystems are dominated by distinct biogeographic regions. Whereas the mean sink is dominated by highly productive lands (mainly tropical forests), the trend and interannual variability of the sink are dominated by semi-arid ecosystems whose carbon balance is strongly associated with circulation-driven variations in both precipitation and temperature.

Abstract Aim To analyse the conservation status of tropical dry forests at the global scale, by combining a newly developed global distribution map with spatial data describing different threats, and to identify the relative exposure of different forest areas to such threats. Location Global assessment. Methods We present a new global distribution map of tropical dry forest derived from the recently developed MODIS Vegetation Continuous Fields (VCF) product, which depicts percentage tree cover at a resolution of 500 m, combined with previously defined maps of biomes. This distribution map was overlaid with spatial data to estimate the exposure of tropical dry forests to a number of different threats: climate change, habitat fragmentation, fire, human population density and conversion to cropland. The extent of tropical dry forest currently protected was estimated by overlaying the forest map with a global data set of the distribution of protected areas. Results It is estimated that 1,048,700 km 2 of tropical dry forest remains, distributed throughout the three tropical regions. More than half of the forest area (54.2%) is located within South America, the remaining area being almost equally divided between North and Central America, Africa and Eurasia, with a relatively small proportion (3.8%) occurring within Australasia and Southeast Asia. Overall, c. 97% of the remaining area of tropical dry forest is at risk from one or more of the threats considered, with highest percentages recorded for Eurasia. The relative exposure to different threats differed between regions: while climate change is relatively significant in the Americas, habitat fragmentation and fire affect a higher proportion of African forests, whereas agricultural conversion and human population density are most influential in Eurasia. Evidence suggests that c. 300,000 km 2 of tropical dry forest now coincide with some form of protected area, with 71.8% of this total being located within South America. Main conclusions Virtually all of the tropical dry forests that remain are currently exposed to a variety of different threats, largely resulting from human activity. Taking their high biodiversity value into consideration, this indicates that tropical dry forests should be accorded high conservation priority. The results presented here could be used to identify which forest areas should be accorded highest priority for conservation action. In particular, the expansion of the global protected area network, particularly in Mesoamerica, should be given urgent consideration.

Abstract We present Multi-Source Weighted-Ensemble Precipitation, version 2 (MSWEP V2), a gridded precipitation P dataset spanning 1979–2017. MSWEP V2 is unique in several aspects: i) full global coverage (all land and oceans); ii) high spatial (0.1°) and temporal (3 hourly) resolution; iii) optimal merging of P estimates based on gauges [WorldClim, Global Historical Climatology Network-Daily (GHCN-D), Global Summary of the Day (GSOD), Global Precipitation Climatology Centre (GPCC), and others], satellites [Climate Prediction Center morphing technique (CMORPH), Gridded Satellite (GridSat), Global Satellite Mapping of Precipitation (GSMaP), and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT)], and reanalyses [European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) and Japanese 55-year Reanalysis (JRA-55)]; iv) distributional bias corrections, mainly to improve the P frequency; v) correction of systematic terrestrial P biases using river discharge Q observations from 13,762 stations across the globe; vi) incorporation of daily observations from 76,747 gauges worldwide; and vii) correction for regional differences in gauge reporting times. MSWEP V2 compares substantially better with Stage IV gauge–radar P data than other state-of-the-art P datasets for the United States, demonstrating the effectiveness of the MSWEP V2 methodology. Global comparisons suggest that MSWEP V2 exhibits more realistic spatial patterns in mean, magnitude, and frequency. Long-term mean P estimates for the global, land, and ocean domains based on MSWEP V2 are 955, 781, and 1,025 mm yr −1 , respectively. Other P datasets consistently underestimate P amounts in mountainous regions. Using MSWEP V2, P was estimated to occur 15.5%, 12.3%, and 16.9% of the time on average for the global, land, and ocean domains, respectively. MSWEP V2 provides unique opportunities to explore spatiotemporal variations in P , improve our understanding of hydrological processes and their parameterization, and enhance hydrological model performance.

Diverse bilaterian clades emerged apparently within a few million years during the early Cambrian, and various environmental, developmental, and ecological causes have been proposed to explain this abrupt appearance. A compilation of the patterns of fossil and molecular diversification, comparative developmental data, and information on ecological feeding strategies indicate that the major animal clades diverged many tens of millions of years before their first appearance in the fossil record, demonstrating a macroevolutionary lag between the establishment of their developmental toolkits during the Cryogenian [(850 to 635 million years ago (Ma)], and the later ecological success of metazoans during the Ediacaran (635 to 541 Ma) and Cambrian (541 to 488 Ma) periods. We argue that this diversification involved new forms of developmental regulation, as well as innovations in networks of ecological interaction within the context of permissive environmental circumstances.

The aerosol products retrieved using the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright‐reflecting land surfaces, such as desert, semiarid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and nonvegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of precalculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semiarid regions to the entire land areas. In this paper, the changes made in the enhanced Deep Blue algorithm regarding the surface reflectance estimation, aerosol model selection, and cloud screening schemes for producing the MODIS collection 6 aerosol products are discussed. A similar approach has also been applied to the algorithm that generates the Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) Deep Blue products. Based upon our preliminary results of comparing the enhanced Deep Blue aerosol products with the Aerosol Robotic Network (AERONET) measurements, the expected error of the Deep Blue aerosol optical thickness (AOT) is estimated to be better than 0.05 + 20%. Using 10 AERONET sites with long‐term time series, 79% of the best quality Deep Blue AOT values are found to fall within this expected error.

We are at a key juncture in history where biodiversity loss is occurring daily and accelerating in the face of population growth, climate change, and rampant development. Simultaneously, we are just beginning to appreciate the wealth of human health benefits that stem from experiencing nature and biodiversity. Here we assessed the state of knowledge on relationships between human health and nature and biodiversity, and prepared a comprehensive listing of reported health effects. We found strong evidence linking biodiversity with production of ecosystem services and between nature exposure and human health, but many of these studies were limited in rigor and often only correlative. Much less information is available to link biodiversity and health. However, some robust studies indicate that exposure to microbial biodiversity can improve health, specifically in reducing certain allergic and respiratory diseases. Overall, much more research is needed on mechanisms of causation. Also needed are a re-envisioning of land-use planning that places human well-being at the center and a new coalition of ecologists, health and social scientists and planners to conduct research and develop policies that promote human interaction with nature and biodiversity. Improvements in these areas should enhance human health and ecosystem, community, as well as human resilience.

Climate change is a pervasive and growing global threat to biodiversity and ecosystems. Here, we present the most up-to-date assessment of climate change impacts on biodiversity, ecosystems, and ecosystem services in the U.S. and implications for natural resource management. We draw from the 4th National Climate Assessment to summarize observed and projected changes to ecosystems and biodiversity, explore linkages to important ecosystem services, and discuss associated challenges and opportunities for natural resource management. We find that species are responding to climate change through changes in morphology and behavior, phenology, and geographic range shifts, and these changes are mediated by plastic and evolutionary responses. Responses by species and populations, combined with direct effects of climate change on ecosystems (including more extreme events), are resulting in widespread changes in productivity, species interactions, vulnerability to biological invasions, and other emergent properties. Collectively, these impacts alter the benefits and services that natural ecosystems can provide to society. Although not all impacts are negative, even positive changes can require costly societal adjustments. Natural resource managers need proactive, flexible adaptation strategies that consider historical and future outlooks to minimize costs over the long term. Many organizations are beginning to explore these approaches, but implementation is not yet prevalent or systematic across the nation.

Abstract The Third Pole (TP) is experiencing rapid warming and is currently in its warmest period in the past 2,000 years. This paper reviews the latest development in multidisciplinary TP research associated with this warming. The rapid warming facilitates intense and broad glacier melt over most of the TP, although some glaciers in the northwest are advancing. By heating the atmosphere and reducing snow/ice albedo, aerosols also contribute to the glaciers melting. Glacier melt is accompanied by lake expansion and intensification of the water cycle over the TP. Precipitation has increased over the eastern and northwestern TP. Meanwhile, the TP is greening and most regions are experiencing advancing phenological trends, although over the southwest there is a spring phenological delay mainly in response to the recent decline in spring precipitation. Atmospheric and terrestrial thermal and dynamical processes over the TP affect the Asian monsoon at different scales. Recent evidence indicates substantial roles that mesoscale convective systems play in the TP’s precipitation as well as an association between soil moisture anomalies in the TP and the Indian monsoon. Moreover, an increase in geohazard events has been associated with recent environmental changes, some of which have had catastrophic consequences caused by glacial lake outbursts and landslides. Active debris flows are growing in both frequency of occurrences and spatial scale. Meanwhile, new types of disasters, such as the twin ice avalanches in Ali in 2016, are now appearing in the region. Adaptation and mitigation measures should be taken to help societies’ preparation for future environmental challenges. Some key issues for future TP studies are also discussed.

Intensive mechanized agriculture in the Brazilian Amazon grew by >3.6 million hectares (ha) during 2001-2004. Whether this cropland expansion resulted from intensified use of land previously cleared for cattle ranching or new deforestation has not been quantified and has major implications for future deforestation dynamics, carbon fluxes, forest fragmentation, and other ecosystem services. We combine deforestation maps, field surveys, and satellite-based information on vegetation phenology to characterize the fate of large (>25-ha) clearings as cropland, cattle pasture, or regrowing forest in the years after initial clearing in Mato Grosso, the Brazilian state with the highest deforestation rate and soybean production since 2001. Statewide, direct conversion of forest to cropland totaled >540,000 ha during 2001-2004, peaking at 23% of 2003 annual deforestation. Cropland deforestation averaged twice the size of clearings for pasture (mean sizes, 333 and 143 ha, respectively), and conversion occurred rapidly; >90% of clearings for cropland were planted in the first year after deforestation. Area deforested for cropland and mean annual soybean price in the year of forest clearing were directly correlated (R(2) = 0.72), suggesting that deforestation rates could return to higher levels seen in 2003-2004 with a rebound of crop prices in international markets. Pasture remains the dominant land use after forest clearing in Mato Grosso, but the growing importance of larger and faster conversion of forest to cropland defines a new paradigm of forest loss in Amazonia and refutes the claim that agricultural intensification does not lead to new deforestation.

The GPCP has developed Version 2.1 of its long‐term (1979–present) global Satellite‐Gauge (SG) data sets to take advantage of the improved GPCC gauge analysis, which is one key input. As well, the OPI estimates used in the pre‐SSM/I era have been rescaled to 20 years of the SSM/I‐era SG. The monthly, pentad, and daily GPCP products have been entirely reprocessed, continuing to require that the submonthly estimates sum to the monthly. Version 2.1 is close to Version 2, with the global ocean, land, and total values about 0%, 6%, and 2% higher, respectively. The revised long‐term global precipitation rate is 2.68 mm/d. The corresponding tropical (25°N‐S) increases are 0%, 7%, and 3%. Long‐term linear changes in the data tend to be smaller in Version 2.1, but the statistics are sensitive to the threshold for land/ocean separation and use of the pre‐SSM/I part of the record.

Abstract. We report on the AeroCom Phase II direct aerosol effect (DAE) experiment where 16 detailed global aerosol models have been used to simulate the changes in the aerosol distribution over the industrial era. All 16 models have estimated the radiative forcing (RF) of the anthropogenic DAE, and have taken into account anthropogenic sulphate, black carbon (BC) and organic aerosols (OA) from fossil fuel, biofuel, and biomass burning emissions. In addition several models have simulated the DAE of anthropogenic nitrate and anthropogenic influenced secondary organic aerosols (SOA). The model simulated all-sky RF of the DAE from total anthropogenic aerosols has a range from −0.58 to −0.02 Wm−2, with a mean of −0.27 Wm−2 for the 16 models. Several models did not include nitrate or SOA and modifying the estimate by accounting for this with information from the other AeroCom models reduces the range and slightly strengthens the mean. Modifying the model estimates for missing aerosol components and for the time period 1750 to 2010 results in a mean RF for the DAE of −0.35 Wm−2. Compared to AeroCom Phase I (Schulz et al., 2006) we find very similar spreads in both total DAE and aerosol component RF. However, the RF of the total DAE is stronger negative and RF from BC from fossil fuel and biofuel emissions are stronger positive in the present study than in the previous AeroCom study. We find a tendency for models having a strong (positive) BC RF to also have strong (negative) sulphate or OA RF. This relationship leads to smaller uncertainty in the total RF of the DAE compared to the RF of the sum of the individual aerosol components. The spread in results for the individual aerosol components is substantial, and can be divided into diversities in burden, mass extinction coefficient (MEC), and normalized RF with respect to AOD. We find that these three factors give similar contributions to the spread in results.

Aerosols are a critical factor in the atmospheric hydrological cycle and radiation budget. As a major agent for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosol effects on clouds could further extend to precipitation, both through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics. However, the various mechanisms behind these effects, in particular, the ones connected to precipitation, are not yet well understood. The atmospheric and climate communities have long been working to gain a better grasp of these critical effects and hence to reduce the significant uncertainties in climate prediction resulting from such a lack of adequate knowledge. Here we review past efforts and summarize our current understanding of the effect of aerosols on convective precipitation processes from theoretical analysis of microphysics, observational evidence, and a range of numerical model simulations. In addition, the discrepancies between results simulated by models, as well as those between simulations and observations, are presented. Specifically, this paper addresses the following topics: (1) fundamental theories of aerosol effects on microphysics and precipitation processes, (2) observational evidence of the effect of aerosols on precipitation processes, (3) signatures of the aerosol impact on precipitation from large‐scale analyses, (4) results from cloud‐resolving model simulations, and (5) results from large‐scale numerical model simulations. Finally, several future research directions for gaining a better understanding of aerosol‐cloud‐precipitation interactions are suggested.

The new Version 2.3 of the GPCP Monthly analysis is described in terms of changes made to improve the homogeneity of the product, especially after 2002. These changes include corrections to cross calibration of satellite data inputs and updates to the gauge analysis. Over ocean, changes starting in 2003 result in an overall precipitation increase of 1.8% after 2009. Updating the gauge analysis to its final, high quality version increases the global land total by 1.8% for the post-2002 period. These changes correct a small, incorrect dip in the estimated global precipitation over the last decade in the earlier Version 2.2. The GPCP analysis is also used to describe global precipitation for 2017. The general La Nina pattern for 2017 is noted and the evolution from the early 2016 El Nino pattern is described. The 2017 global value is one of the highest for the 19792017 period, exceeded only by 2016 and 1998 (both El Nino years) and reinforces the small positive trend. Results for 2017 also reinforce significant trends in precipitation intensity (on a monthly scale) in the tropics. These results for 2017 indicate the value of the GPCP analysis for climate monitoring in addition to research.