Potential of satellite-based land emissivity estimates for the detection of high-latitude freeze and thaw states

Reliable detection of freeze and thaw (FT) states is crucial for the terrestrial water cycle, biogeochemical transitions, carbon and methane feedback to the atmosphere, and for the surface energy budget and its associated impacts on the global climate system. This paper is novel in that for the first time a unique approach to examine the potential of passive microwave remotely sensed land emissivity and its added-values of being free from the atmospheric effects and being sensitive to surface characteristics is being applied to the detection of FT states for latitudes north of 35°N. Since accurate characterizations of the soil state are highly dependent on land cover types, a novel threshold-based approach specific to different land cover types is proposed for daily FT detection from the use of three years (August 2012 – July 2015) of the Advanced Microwave Scanning Radiometer – 2 land emissivity estimates. Ground-based soil temperature observations are used as reference to develop threshold values for FT states. Preliminary evaluation of the proposed approach with independent ground observations over Alaska for the year 2015 shows that the use of land emissivity estimates for high-latitude FT detection is promising

Estimation of Consistent Global Microwave Land Surface Emissivity from AMSR-E and AMSR2 Observations

Accurate estimation of passive microwave land surface emissivity (LSE) is crucial for numerical weather prediction model data assimilation, for microwave retrievals of land precipitation and atmospheric profiles, and for better understanding of land surface and sub-surface characteristics. In this study, global instantaneous LSE is estimated for the 9-year period from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and for the 5-year period from the Advanced Microwave Scanning Radiometer - 2 (AMSR2) sensors. Estimates of LSE from both sensors were obtained by using an updated algorithm that minimizes the discrepancy between the differences in penetration depths from microwave and infrared remote sensing observations. Concurrent ancillary data sets such as skin temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) and profiles of air temperature and humidity from the Atmospheric Infrared Sounder (AIRS) are used. The latest collection 6 of MODIS skin temperature is used for the LSE estimation, and the differences between collections 6 and 5 are also comprehensively assessed. Our analyses reveal that the differences between these two versions of infrared-based skin temperatures could lead up to 0.015 differences in passive microwave LSE values especially in arid regions. The comparison of global mean LSE features from the combined use of AMSR-E and AMSR2 against an independent product - Tool to Estimate Land-Surface Emissivities at Microwave frequencies (TELSEM2) shows spatial pattern correlations of the order 0.92 at all the frequencies. However, there are considerable differences in magnitude between these two LSE estimates possibly due to differences in incidence angles, frequencies, observation times, and ancillary data sets

Climate-informed environmental inflows to revive a drying lake facing meteorological and anthropogenic droughts

The rapid shrinkage of Lake Urmia, one of the world\u27s largest saline lakes located in northwestern Iran, is a tragic wake-up call to revisit the principles of water resources management based on the socio-economic and environmental dimensions of sustainable development. The overarching goal of this paper is to set a framework for deriving dynamic, climate-informed environmental inflows for drying lakes considering both meteorological/climatic and anthropogenic conditions. We report on the compounding effects of meteorological drought and unsustainable water resource management that contributed to Lake Urmia\u27s contemporary environmental catastrophe. Using rich datasets of hydrologic attributes, water demands and withdrawals, as well as water management infrastructure (i.e. reservoir capacity and operating policies), we provide a quantitative assessment of the basin\u27s water resources, demonstrating that Lake Urmia reached a tipping point in the early 2000s. The lake level failed to rebound to its designated ecological threshold (1274 m above sea level) during a relatively normal hydro-period immediately after the drought of record (1998–2002). The collapse was caused by a marked overshoot of the basin\u27s hydrologic capacity due to growing anthropogenic drought in the face of extreme climatological stressors. We offer a dynamic environmental inflow plan for different climate conditions (dry, wet and near normal), combined with three representative water withdrawal scenarios. Assuming effective implementation of the proposed 40% reduction in the current water withdrawals, the required environmental inflows range from 2900 million cubic meters per year (mcm yr−1) during dry conditions to 5400 mcm yr−1 during wet periods with the average being 4100 mcm yr−1. Finally, for different environmental inflow scenarios, we estimate the expected recovery time for re-establishing the ecological level of Lake Urmia

What makes a cyanobacterial bloom disappear? A review of the abiotic and biotic cyanobacterial bloom loss factors

Cyanobacterial blooms present substantial challenges to managers and threaten ecological and public health. Although the majority of cyanobacterial bloom research and management focuses on factors that control bloom initiation, duration, toxicity, and geographical extent, relatively little research focuses on the role of loss processes in blooms and how these processes are regulated. Here, we define a loss process in terms of population dynamics as any process that removes cells from a population, thereby decelerating or reducing the development and extent of blooms. We review abiotic (e.g., hydraulic flushing and oxidative stress/UV light) and biotic factors (e.g., allelopathic compounds, infections, grazing, and resting cells/programmed cell death) known to govern bloom loss. We found that the dominant loss processes depend on several system specific factors including cyanobacterial genera-specific traits, in situ physicochemical conditions, and the microbial, phytoplankton, and consumer community composition. We also address loss processes in the context of bloom management and discuss perspectives and challenges in predicting how a changing climate may directly and indirectly affect loss processes on blooms. A deeper understanding of bloom loss processes and their underlying mechanisms may help to mitigate the negative consequences of cyanobacterial blooms and improve current management strategies

THE HIGH TEMPORAL DETECTION OF LAND SURFACE FREEZE AND THAW STATES VIA A COMBINATION OF PASSIVE MICROWAVE ESTIMATES

The states of the Earth surface in terms of high-latitude freeze and thaw (FT) cycles significantly impact many physical applications that include biogeochemical transitions, hydrological phenomena, and ecosystem evolution. We have shown that land surface emissivity estimates have great potential for use in the detection of FT states since that parameter primarily depends on surface characteristics instead of on direct use of brightness temperatures. This study aims to investigate the potential of merging passive microwave sensors and their land surface emissivity estimates from Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), Special Sensor Microwave Imager (SSM/I), AMSR2, and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) to provide high temporal resolution (sub-daily) FT states. This factor is of critical importance and usage, primarily during the transitions between freeze and thaw that frequently occur at sub-daily time-frames in spring seasons. Data fusion techinques were used to construct diurnal estimates in order to accurately predicting the exact time of the freeze-thaw transition for a variety of land cover types and geographical regions. The results revealed that emissivity difference values between low and high frequencies (such as 10.7 GHz and 89GHz) at horizontal polarization from multiple platforms have a strong correlation with ground-based soil temperature diurnal values at 5-cm depth. Evaluation of the proposed approach with independent ground observations from year 2015 to 2017 showed that the data fusion of land surface emissivities in high-latitudes was able to notably capture the frequent FT transitions

Estimation of Consistent Global Microwave Land Surface Emissivity from AMSR-E and AMSR2 Observations

International audienceAccurate estimation of passive microwave land surface emissivity (LSE)is crucial for numerical weather prediction model data assimilation, formicrowave retrievals of land precipitation and atmospheric profiles, andfor a better understanding of land surface and subsurfacecharacteristics. In this study, global instantaneous LSE is estimatedfor a 9-yr period from the Advanced Microwave Scanning Radiometer forEarth Observing System (AMSR-E) and for a 5-yr period from the AdvancedMicrowave Scanning Radiometer 2 (AMSR2) sensors. Estimates of LSE fromboth sensors were obtained by using an updated algorithm that minimizesthe discrepancy between the differences in penetration depths frommicrowave and infrared remote sensing observations. Concurrent ancillarydatasets such as skin temperature from the Moderate Resolution ImagingSpectroradiometer (MODIS) and profiles of air temperature and humidityfrom the Atmospheric Infrared Sounder are used. The latest collection 6of MODIS skin temperature is used for the LSE estimation, and thedifferences between collections 6 and 5 are also comprehensivelyassessed. Analyses reveal that the differences between these twoversions of infrared-based skin temperatures could lead to approximatelya 0.015 difference in passive microwave LSE values, especially in aridregions. The comparison of global mean LSE features from the combineduse of AMSR-E and AMSR2 with an independent product?Tool to EstimateLand Surface Emissivity from Microwave to Submillimeter Waves(TELSEM2)?shows spatial pattern correlations of order 0.92 atall frequencies. However, there are considerable differences inmagnitude between these two LSE estimates, possibly because ofdifferences in incidence angles, frequencies, observation times, andancillary datasets

Aral Sea syndrome desiccates Lake Urmia: Call for action

© 2014 International Association for Great Lakes Research. Lake Urmia, one of the largest saltwater lakes on earth and a highly endangered ecosystem, is on the brink of a major environmental disaster similar to the catastrophic death of the Aral Sea. With a new composite of multi-spectral high resolution satellite observations, we show that the area of this Iranian lake has decreased by around 88% in the past decades, far more than previously reported (~ 25% to 50%). The lake\u27s shoreline has been receding severely with no sign of recovery, which has been partly blamed on prolonged droughts. We use the lake basin\u27s satellite-based gauge-adjusted climate record of the Standardized Precipitation Index data to demonstrate that the on-going shoreline retreat is not solely an artifact of prolonged droughts alone. Drastic changes to lake health are primarily consequences of aggressive regional water resources development plans, intensive agricultural activities, anthropogenic changes to the system, and upstream competition over water. This commentary is a call for action to both develop sustainable restoration ideas and to put new visions and strategies into practice before Lake Urmia falls victim to the Aral Sea syndrome

Anthropogenic Drought: Definition, Challenges, and Opportunities

Traditional, mainstream definitions of drought describe it as deficit in water-related variables or water-dependent activities (e.g., precipitation, soil moisture, surface and groundwater storage, and irrigation) due to natural variabilities that are out of the control of local decision-makers. Here, we argue that within coupled human-water systems, drought must be defined and understood as a process as opposed to a product to help better frame and describe the complex and interrelated dynamics of both natural and human-induced changes that define anthropogenic drought as a compound multidimensional and multiscale phenomenon, governed by the combination of natural water variability, climate change, human decisions and activities, and altered micro-climate conditions due to changes in land and water management. This definition considers the full spectrum of dynamic feedbacks and processes (e.g., land-atmosphere interactions and water and energy balance) within human-nature systems that drive the development of anthropogenic drought. This process magnifies the water supply demand gap and can lead to water bankruptcy, which will become more rampant around the globe in the coming decades due to continuously growing water demands under compounding effects of climate change and global environmental degradation. This challenge has de facto implications for both short-term and long-term water resources planning and management, water governance, and policymaking. Herein, after a brief overview of the anthropogenic drought concept and its examples, we discuss existing research gaps and opportunities for better understanding, modeling, and management of this phenomenon