Global soil moisture bimodality in satellite observations and climate models

A new diagnostic metric based on soil moisture bimodality is developed in order to examine and compare soil moisture from satellite observations and Earth System Models. The methodology to derive this diagnostic is based on maximum likelihood estimator encoded into an iterative algorithm, which is applied to the soil moisture probability density function. This metric is applied to satellite data from the Advanced Microwave Scanning Radiometer for the Earth Observing System and global climate models data from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Results show high soil moisture bimodality in transitional climate areas and high latitudes, potentially associated with land-atmosphere feedback processes. When comparing satellite versus climate models, a clear difference in their soil moisture bimodality is observed, with systematically higher values in the case of CMIP5 models. These differences appear related to areas where land-atmospheric feedback may be overestimated in current climate models

State of the climate in 2017

In 2017, the dominant greenhouse gases released into Earth's atmosphere-carbon dioxide, methane, and nitrous oxide-reached new record highs. The annual global average carbon dioxide concentration at Earth's surface for 2017 was 405.0 ± 0.1 ppm, 2.2 ppm greater than for 2016 and the highest in the modern atmospheric measurement record and in ice core records dating back as far as 800 000 years. The global growth rate of CO2 has nearly quadrupled since the early 1960s. With ENSO-neutral conditions present in the central and eastern equatorial Pacific Ocean during most of the year and weak La Niña conditions notable at the start and end, the global temperature across land and ocean surfaces ranked as the second or third highest, depending on the dataset, since records began in the mid-to-late 1800s. Notably, it was the warmest non-El Niño year in the instrumental record. Above Earth's surface, the annual lower tropospheric temperature was also either second or third highest according to all datasets analyzed. The lower stratospheric temperature was about 0.2°C higher than the record cold temperature of 2016 according to most of the in situ and satellite datasets. Several countries, including Argentina, Uruguay, Spain, and Bulgaria, reported record high annual temperatures. Mexico broke its annual record for the fourth consecutive year. On 27 January, the temperature reached 43.4°C at Puerto Madryn, Argentina-the highest temperature recorded so far south (43°S) anywhere in the world. On 28 May in Turbat, western Pakistan, the high of 53.5°C tied Pakistan's all-time highest temperature and became the world-record highest temperature for May. In the Arctic, the 2017 land surface temperature was 1.6°C above the 1981-2010 average, the second highest since the record began in 1900, behind only 2016. The five highest annual Arctic temperatures have all occurred since 2007. Exceptionally high temperatures were observed in the permafrost across the Arctic, with record values reported in much of Alaska and northwestern Canada. In August, high sea surface temperature (SST) records were broken for the Chukchi Sea, with some regions as warm as +11°C, or 3° to 4°C warmer than the longterm mean (1982-present). According to paleoclimate studies, today's abnormally warm Arctic air and SSTs have not been observed in the last 2000 years. The increasing temperatures have led to decreasing Arctic sea ice extent and thickness. On 7 March, sea ice extent at the end of the growth season saw its lowest maximum in the 37-year satellite record, covering 8% less area than the 1981-2010 average. The Arctic sea ice minimum on 13 September was the eighth lowest on record and covered 25% less area than the long-term mean. Preliminary data indicate that glaciers across the world lost mass for the 38th consecutive year on record; the declines are remarkably consistent from region to region. Cumulatively since 1980, this loss is equivalent to slicing 22 meters off the top of the average glacier. Antarctic sea ice extent remained below average for all of 2017, with record lows during the first four months. Over the continent, the austral summer seasonal melt extent and melt index were the second highest since 2005, mostly due to strong positive anomalies of air temperature over most of the West Antarctic coast. In contrast, the East Antarctic Plateau saw record low mean temperatures in March. The year was also distinguished by the second smallest Antarctic ozone hole observed since 1988. Across the global oceans, the overall long-term SST warming trend remained strong. Although SST cooled slightly from 2016 to 2017, the last three years produced the three highest annual values observed; these high anomalies have been associated with widespread coral bleaching. The most recent global coral bleaching lasted three full years, June 2014 to May 2017, and was the longest, most widespread, and almost certainly most destructive such event on record. Global integrals of 0-700-m and 0-2000-m ocean heat content reached record highs in 2017, and global mean sea level during the year became the highest annual average in the 25-year satellite altimetry record, rising to 77 mm above the 1993 average. In the tropics, 2017 saw 85 named tropical storms, slightly above the 1981-2010 average of 82. The North Atlantic basin was the only basin that featured an above-normal season, its seventh most active in the 164-year record. Three hurricanes in the basin were especially notable. Harvey produced record rainfall totals in areas of Texas and Louisiana, including a storm total of 1538.7 mm near Beaumont, Texas, which far exceeds the previous known U.S. tropical cyclone record of 1320.8 mm. Irma was the strongest tropical cyclone globally in 2017 and the strongest Atlantic hurricane outside of the Gulf of Mexico and Caribbean on record with maximum winds of 295 km h-1. Maria caused catastrophic destruction across the Caribbean Islands, including devastating wind damage and flooding across Puerto Rico. Elsewhere, the western North Pacific, South Indian, and Australian basins were all particularly quiet. Precipitation over global land areas in 2017 was clearly above the long-term average. Among noteworthy regional precipitation records in 2017, Russia reported its second wettest year on record (after 2013) and Norway experienced its sixth wettest year since records began in 1900. Across India, heavy rain and flood-related incidents during the monsoon season claimed around 800 lives. In August and September, above-normal precipitation triggered the most devastating floods in more than a decade in the Venezuelan states of Bolívar and Delta Amacuro. In Nigeria, heavy rain during August and September caused the Niger and Benue Rivers to overflow, bringing floods that displaced more than 100 000 people. Global fire activity was the lowest since at least 2003; however, high activity occurred in parts of North America, South America, and Europe, with an unusually long season in Spain and Portugal, which had their second and third driest years on record, respectively. Devastating fires impacted British Columbia, destroying 1.2 million hectares of timber, bush, and grassland, due in part to the region's driest summer on record. In the United States, an extreme western wildfire season burned over 4 million hectares; the total costs of $18 billion tripled the previous U.S. annual wildfire cost record set in 1991

Global Soil Moisture Patterns Observed by Space Borne Microwave Radiometers and Scatterometers

Within the scope of the upcoming launch of a new water related satellite mission (SMOS) a global evaluation study was performed on two available global soil moisture products. ERS scatterometer surface wetness data was compared to AMSR-E soil moisture data. This study pointed out a strong similarity between both products in sparse to moderate vegetated regions with an average correlation coefficient of 0.83. Low correlations were found in densely vegetated areas and deserts. The low values in the vegetated regions can be explained by the limited soil moisture retrieval capabilities over dense vegetation covers. Soil emission is attenuated by the canopy and tends to saturate the microwave signal with increasing vegetation density, resulting in a decreased sensor sensitivity to soil moisture variations. It is expected that the new low frequency satellite mission (SMOS) will obtain soil moisture products with a higher quality in these regions. The low correlations in the desert regions are likely due to volume scattering or to the dielectric dynamics within the soil. The volume scattering in dry soils causes a higher backscatter under very dry conditions than under conditions when the sub-surface soil layers are somewhat wet. In addition, at low moisture levels the dielectric constant has a reduced sensitivity in response to changes in the soil moisture content. At a global scale the spatial correspondence of both products is high and both products clearly distinguish similar regions with high seasonal and inter annual variations. Based on the global analyses we concluded that the quality of both products was comparable and in the sparse to moderate vegetated regions both products may be beneficial for large scale validation of SMOS soil moisture. Some limitations of the studied products are different, pointing to significant potential for combining both products into one superior soil moisture data set. © The Author(s) 2008

The evaluation of single-sensor surface soil moisture anomalies over the mainland of the People's Republic of China

© 2017 by the authors. In recent years, different space agencies have launched satellite missions that carry passive microwave instruments on-board that can measure surface soil moisture. Three currently operational missions are the Soil Moisture and Ocean Salinity (SMOS) mission developed by the European Space Agency (ESA), the Advanced Microwave Scanning Radiometer 2 (AMSR2) developed by the Japan Aerospace Exploration Agency (JAXA), and the Microwave Radiation Imager (MWRI) from China's National Satellite Meteorological Centre (NSMC). In this study, the quality of surface soil moisture anomalies derived from these passive microwave instruments was sequentially assessed over the mainland of the People's Republic of China. First, the impact of a recent update in the Land Parameter Retrieval Model (LPRM) was assessed for MWRI observations. Then, the soil moisture measurements retrieved from the X-band observations of MWRI were compared with those of AMSR2, followed by an internal comparison of the multiple frequencies of AMSR2. Finally, SMOS retrievals from two different algorithms were also included in the comparison. For each sequential step, processing and verification chains were specifically designed to isolate the impact of algorithm (version), observation frequency or instrument characteristics. Two verification techniques are used: the statistical Triple Collocation technique is used as the primary verification tool, while the precipitation-based Rvalue technique is used to confirm key results. Our results indicate a consistently better performance throughout the entire study area after the implementation of an update of the LPRM.We also find that passive microwave observations in the AMSR2 C-band frequency (6.9 GHz) have an advantage over the AMSR2 X-band frequency (10.7 GHz) over moderate to densely vegetated regions. This finding is in line with theoretical expectations as emitted soil radiation will become masked under a dense canopy with stricter thresholds for higher passive microwave frequencies. Both AMSR2 and MWRI make X-band observations; a direct comparison between them reveals a consistently higher quality obtained by AMSR2, specifically over semi-arid climate regimes. Unfortunately, Radio Frequency Interference hampers the usefulness of soil moisture products for the SMOS L-band mission, leading to a significantly reduced revisit time over the densely populated eastern part of the country. Nevertheless, our analysis demonstrates that soil moisture products from a number of multi-frequency microwave sensors are credible alternatives for this dedicated L-band mission over the mainland of the People's Republic of China

Enhanced canopy growth precedes senescence in 2005 and 2010 Amazonian droughts

© 2018 Unprecedented droughts hit southern Amazonia in 2005 and 2010, causing a sharp increase in tree mortality and carbon loss. To better predict the rainforest's response to future droughts, it is necessary to understand its behavior during past events. Satellite observations provide a practical source of continuous observations of Amazonian forest. Here we used a passive microwave-based vegetation water content record (i.e., vegetation optical depth, VOD), together with multiple hydrometeorological observations as well as conventional satellite vegetation measures, to investigate the rainforest canopy dynamics during the 2005 and 2010 droughts. During the onset of droughts in the wet-to-dry season (May–July) of both years, we found large-scale positive anomalies in VOD, leaf area index (LAI) and enhanced vegetation index (EVI) over the southern Amazonia. These observations are very likely caused by enhanced canopy growth. Concurrent below-average rainfall and above-average radiation during the wet-to-dry season can be interpreted as an early arrival of normal dry season conditions, leading to enhanced new leaf development and ecosystem photosynthesis, as supported by field observations. Our results suggest that further rainfall deficit into the subsequent dry season caused water and heat stress during the peak of 2005 and 2010 droughts (August–October) that exceeded the tolerance limits of the rainforest, leading to widespread negative VOD anomalies over the southern Amazonia. Significant VOD anomalies were observed mainly over the western part in 2005 and mainly over central and eastern parts in 2010. The total area with significant negative VOD anomalies was comparable between these two drought years, though the average magnitude of significant negative VOD anomalies was greater in 2005. This finding broadly agrees with the field observations indicating that the reduction in biomass carbon uptake was stronger in 2005 than 2010. The enhanced canopy growth preceding drought-induced senescence should be taken into account when interpreting the ecological impacts of Amazonian droughts

Comparison of remotely sensed and modelled soil moisture data sets across Australia

This study compared surface soil moisture from 11 separate remote sensing and modelled products across Australia in a common framework. The comparison was based on a correlation analysis between soil moisture products and in situ data collated from three separate ground-based networks: OzFlux, OzNet and CosmOz. The correlation analysis was performed using both original data sets and temporal anomalies, and was supported by examination of the time series plots. The interrelationships between the products were also explored using cluster analyses. The products considered in this study include: Soil Moisture Ocean Salinity (SMOS; both Land Parameter Retrieval Model (LPRM) and L-band Microwave Emission of the Biosphere (LMEB) algorithms), Advanced Microwave Scanning Radiometer 2 (AMSR2; both LPRM and Japan Aerospace Exploration Agency (JAXA) algorithms) and Advanced Scatterometer (ASCAT) satellite-based products, and WaterDyn, Australian Water Resource Assessment Landscape (AWRA-L), Antecedent Precipitation Index (API), Keetch-Byram Drought Index (KBDI), Mount's Soil Dryness Index (MSDI) and CABLE/BIOS2 model-based products. The comparison of the satellite and model data sets showed variation in their ability to reflect in situ soil moisture conditions across Australia owing to individual product characteristics. The comparison showed the satellite products yielded similar ranges of correlation coefficients, with the possible exception of AMSR2_JAXA. SMOS (both algorithms) achieved slightly better agreement with in situ measurements than the alternative satellite products overall. Among the models, WaterDyn yielded the highest correlation most consistently across the different locations and climate zones considered. All products displayed a weaker performance in estimating soil moisture anomalies than the original data sets (i.e. the absolute values), showing all products to be more effective in detecting interannual and seasonal soil moisture dynamics rather than individual events. Using cluster analysis we found satellite products generally grouped together, whereas models were more similar to other models. SMOS (based on LMEB algorithm and ascending overpass) and ASCAT (descending overpass) were found to be very similar to each other in terms of their temporal soil moisture dynamics, whereas AMSR2 (based on LPRM algorithm and descending overpass) and AMSR2 (based on JAXA algorithm and ascending overpass) were dissimilar. Of the model products, WaterDyn and CABLE were similar to each other, as were the API/AWRA-L and KBDI/MSDI pairs. The clustering suggests systematic commonalities in error structure and duplication of information may exist between products. This evaluation has highlighted relative strengths, weaknesses, and complementarities between products, so the drawbacks of each may be minimised through a more informed assessment of fitness for purpose by end users