The observed state of the water cycle in the early twenty-first century

Author Posting. © American Meteorological Society, 2015. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 28 (2015): 8289–8318, doi:10.1175/JCLI-D-14-00555.1.This study quantifies mean annual and monthly fluxes of Earth’s water cycle over continents and ocean basins during the first decade of the millennium. To the extent possible, the flux estimates are based on satellite measurements first and data-integrating models second. A careful accounting of uncertainty in the estimates is included. It is applied within a routine that enforces multiple water and energy budget constraints simultaneously in a variational framework in order to produce objectively determined optimized flux estimates. In the majority of cases, the observed annual surface and atmospheric water budgets over the continents and oceans close with much less than 10% residual. Observed residuals and optimized uncertainty estimates are considerably larger for monthly surface and atmospheric water budget closure, often nearing or exceeding 20% in North America, Eurasia, Australia and neighboring islands, and the Arctic and South Atlantic Oceans. The residuals in South America and Africa tend to be smaller, possibly because cold land processes are negligible. Fluxes were poorly observed over the Arctic Ocean, certain seas, Antarctica, and the Australasian and Indonesian islands, leading to reliance on atmospheric analysis estimates. Many of the satellite systems that contributed data have been or will soon be lost or replaced. Models that integrate ground-based and remote observations will be critical for ameliorating gaps and discontinuities in the data records caused by these transitions. Continued development of such models is essential for maximizing the value of the observations. Next-generation observing systems are the best hope for significantly improving global water budget accounting.This research was funded by multiple grants from NASA’s Energy and Water Cycle Study (NEWS) program.2016-05-0

Improving the Physical Processes and Model Integration Functionality of an Energy Balance Model for Snow and Glacier Melt

The Hindu-Kush Himalayan region possesses a large resource of snow and ice, which acts as a freshwater reservoir for irrigation, domestic water consumption or hydroelectric power for billions of people in South Asia. Monitoring hydrologic resources in this region is challenging because of the difficulty of installing and maintaining a climate and hydrologic monitoring network, limited transportation and communication infrastructure and difficult access to glaciers. As a result of the high, rugged topographic relief, ground observations in the region are extremely sparse. Reanalysis data offer the potential to compensate for the data scarcity, which is a barrier in hydrological modeling and analysis for improving water resources management. Reanalysis weather data products integrate observations with atmospheric model physics to produce a spatially and temporally complete weather record in the post-satellite era. This dissertation creates an integrated hydrologic modeling system that tests whether streamflow prediction can be improved by taking advantage of the National Aeronautics and Space Administration (NASA) remote sensing and reanalysis weather data products in physically based energy balance snow melt and hydrologic models. This study also enhances the energy balance snowmelt model by adding capability to quantify glacier melt. The novelty of this integrated modeling tool resides in allowing the user to isolate various components of surface water inputs (rainfall, snow and glacier ice melt) in a cost-free, open source graphical-user interface-based system that can be used for government and institutional decision-making. Direct, physically based validation of this system is challenging due to the data scarcity in this region, but, to the extent possible, the model was validated through comparison to observed streamflow and to point measurements at locations in the United States having available dat

Consistency in the AMSR-E snow products: groundwork for a coupled snowfall and SWE algorithm

2019 Fall.Includes bibliographical references.Snow is an important wintertime property because it is a source of freshwater, regulates land-atmosphere exchanges, and increases the surface albedo of snow-covered regions. Unfortunately, in-situ observations of both snowfall and snow water equivalent (SWE) are globally sparse and point measurements are not representative of the surrounding area, especially in mountainous regions. The total amount of land covered by snow, which is climatologically important, is fairly straightforward to measure using satellite remote sensing. The total SWE is hydrologically more useful, but significantly more difficult to measure. Accurately measuring snowfall and SWE is an important first step toward a better understanding of the impacts snow has for hydrological and climatological purposes. Satellite passive microwave retrievals of snow offer potential due to consistent overpasses and the capability to make measurements during the day, night, and cloudy conditions. However, passive microwave snow retrievals are less mature than precipitation retrievals and have been an ongoing area of research. Exacerbating the problem, communities that remotely sense snowfall and SWE from passive microwave sensors have historically operated independently while the accuracy of the products has suffered because of the physical and radiometric dependency between the two. In this study, we assessed the relationship between the Northern Hemisphere snowfall and SWE products from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). This assessment provides insight into regimes that can be used as a starting point for future improvements using coupled snowfall and SWE algorithm. SnowModel, a physically-based snow evolution modeling system driven by the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis, was employed to consistently compare snowfall and SWE by accounting for snow evolution. SnowModel has the ability to assimilate observed SWE values to scale the amount of snow that must have fallen to match the observed SWE. Assimilation was performed using AMSR-E, Canadian Meteorological Centre (CMC) Snow Analysis, and Snow Data Assimilation System (SNODAS) SWE to infer the required snowfall for each dataset. Observed AMSR-E snowfall and SWE were then compared to the MERRA-2 snowfall and SnowModel-produced SWE as well as SNODAS and CMC inferred snowfall and observed SWE. Results from the study showed significantly different snowfall and SWE bias patterns observed by AMSR-E. Specifically, snowfall was underestimated nearly globally and SWE had pronounced regions of over and underestimation. Snowfall and SWE biases were found to differ as a function of surface temperature, snow class, and elevation

Spatial and temporal characteristics of historical surface climate over the Northwest Territories, Canada

Climate change is putting many of the Northwest Territories (NWT) ecosystems, its people and animal populations at risk due to accelerated warming, permafrost thaw, and changing precipitation regimes. As the NWT continues to warm, at disproportionately higher rates when compared to the rest of Canada, threats to the stability of NWT’s ecosystems are expected to increase. Consequently, understanding how climate warming has changed historically and its implications on natural ecosystems requires point-to-region-specific, long-term climatic data to elucidate important drivers of observed changes relevant to decision makers at community, Indigenous, Territorial and Federal government levels. However, in situ climate data are limited temporally and spatially across the NWT. Hence, the overarching goal of this research is to enhance and improve the understanding of historical surface climate variables trends and patterns (air temperature, precipitation, and shortwave radiation) and its implications at local and regional scales in the continental NWT by using interpolated, reanalysis and remote sensing climate data. Gridded climate datasets such as interpolated and reanalysis data, can provide reliable estimates for in situ observations to compensate for data scarcity, but it is critical that researchers understand how biases in these datasets can impact runoff simulation in the NWT. Thus, the objective of this dissertation was to assess the similarity between daily in situ station observations and three gridded datasets (ANUSPLIN, ERA-Interim and MERRA-2) from 1980 to 2013 to support hydrological modelling in the NWT subarctic. The ANUSPLIN maximum and minimum temperature at eight locations aligned closely to the corresponding in situ observations and had mean daily biases of less than 0.58°C and 1.33°C, respectively. Precipitation estimates showed that the alternative datasets captured year-to-year variability, but large seasonal biases mainly during spring and summer were evident when precipitation magnitudes were estimated. In addition, this study used gridded data as a substitute for in situ observations in the Cold Regions Hydrological Model (CRHM) to simulate runoff. Simulated runoff generated when using ANUSPLIN and ERA-Interim data as inputs in CRHM captures the timing and magnitude of freshet and baseflow generally well at Scotty Creek. This study suggests that gridded datasets can provide reasonable estimates of in situ climate data in data sparse regions and reinforced that the accuracy in representing in situ observations over the NWT improves as the spatial resolution of interpolated dataset increases. This research also highlighted that when comparing datasets, it is important use multiple metrics and graphical methods to discern systematic biases. The presence of oceanic-atmospheric teleconnections patterns can influence weather patterns in northern regions which may lead to an increase in climate related wildland fires. The impact of the Arctic Dipole (AD) anomaly, a northern atmospheric teleconnection, on NWT’s surface climate has not been explored. Hence, the second objective of this dissertation used the ANUSPLIN dataset to assess the effects of the AD anomaly on local climate (air temperature, precipitation, and snowmelt) during a 66-year period (1950-2015). For all seasons, from 1950 to 2015, the occurrence of 64 strong positive and 56 strong negative AD modes were identified. The AD pattern revealed significant year-to-year fluctuation, with more frequent strong negative modes observed in the 2000s. In summer, when AD is in its strong negative mode, there is increased variance in the range of local air temperature, which is amplified in the southern, lake and foothill regions of the Taiga Plains. During strong positive AD modes, local air temperature anomalies increased (\u3e0.8°C) when compared to long-term mean temperature during summer months. Positive AD modes also lead to earlier commencement of snowmelt by an average of 3 to 5 days. The air temperature/snowmelt onset north–south amplification to the AD is linked to the position and intensity of the geopotential heights ridge axis over the continental NWT. A weak correlation was found between the AD and seasonal precipitation despite high correlation association between the AD and local air temperature in summer. Finally, the spatiotemporal patterns of incoming surface shortwave radiation (SSR) were analysed and quantified for the continental NWT to enhance understanding of northern ecosystems energy balance that are undergoing environmental changes. The third objective of this dissertation addressed this knowledge gap by assessing annual and seasonal trends in SSR receipt and to explore relationship between SSR and lake surface water temperature (LSWT) during the warm season. Consequently, the quantity of SSR that reaches Earth’s surface may vary. In this study, it is observed that SSR trends display a significant temporal and spatial dependency on NWT’s ecozones between 1980 and 2020. The annual mean SSR since 1980 decreased by ~0.8 Wm-2decade-1 in the Taiga Plains and Northern Arctic ecozones, with mixture of increasing and decreasing trends in both Taiga Shield and Southern Arctic ecozones. Seasonally, SSR decreased significantly in the summer since 1980 over the majority of the Taiga Plains ecozone, with a reduction rate that ranged between 0.6 and 14.6 Wm-2decade-1. The LSWT in small lakes was positively associated with SSR, while the LSWT in medium and large lakes showed a mix of positive and negative correlation coefficients. The linkage between total cloud cover and SSR in the NWT was largely negative for spring, summer and autumn seasons, with the Taiga Plains ecozone displaying the largest negative correlation. Long-term changes in SSR in the NWT will have an impact on the seasonal and annual energy balance of the region\u27s lakes. The impact of SSR changes on lake energy balances will have a wide range of consequences, particularly for NWT communities that rely on lakes for their transportation networks. These networks are already being adversely impacted by climate change-driven alterations in warming lake ice phenology. The collective findings of this study demonstrate the feasibility of using gridded and remote sensing datasets to characterize historical changes in local and regional weather and climate, building an understanding of northern climatology and providing best estimates of long-term trends with implications for ecosystem change in the future, such as increased rates of shrubification and frequency of wildland fires. In the absence of consistent in situ climate data, these gridded and remote sensing datasets aid our understanding of the physical links between climate change and northern ecosystems, which must be accounted for in forecast models used to predict future hydroclimate scenarios and to provide enhance climate services in northern regions. Improved understanding of how local and regional climate has changed in the NWT will inform policymakers in their efforts to develop and improve climate adaptation and mitigation policies in local communities across the territory

Multi-scale Spatial Analysis of the Water-Food-Climate Nexus in the Nile Basin using Earth Observation Data

Securing enough water and food for everyone is a great challenge that the humanity faces today. This challenge is aggravated by many external drivers such as population growth, climate variability, and degradation of natural resources. Solutions for weak water and food securities require holistic knowledge of the different involved drivers through a nexus approach that looks at the interlinkages and the multi-directional synergies to be promoted and increased and trade-offs to be reduced or eliminated. In particular, the interlinkages between water, food, and climate, the so-called Water-Food-Climate Nexus (WFC Nexus) is critical for the given challenge in many regions around the world such as the Nile Basin (NB). Studying the WFC Nexus synergies and trade-offs might provide entry points for the required interventions that are potential to induce positive impacts on water and food securities. However, these synergies and trade-offs are not well known due to factors such as the complexity of the interactions which involve many dimensions within and across spatial and temporal domains and unavailability of reliable ground observations that could be used for such analysis. Therefore, multidisciplinary research that encompasses different methodologies and employs datasets with adequate spatial and temporal resolutions is required. The recent advancement in Earth Observation (EO) sensors and data processing algorithms have resulted in the accumulation of big data that are produced in rates faster than their usage in solving real challenges such as the one that is in the focus of the current research. The availability of public-domain datasets for several parameters with spatial and temporal coverage offers an excellent opportunity to discover the WFC Nexus interlinkages. To this end, the main goal of the current research is to employ EO data derived from public-domain datasets and supplemented with other primary and secondary data to identify WFC Nexus synergies and trade-offs in the NB region, taking the agricultural systems in Sudan as a central focus of this assessment. By concentrating mainly on the agricultural systems in Sudan, which are characterized by low performance and efficiency despite the huge potentials for food production, the current research provides a representative case study that could deliver helpful and transferrable knowledge to many areas within and outside the NB region. In the current research, multi-scale analysis of the WFC Nexus synergies and trade-offs was conducted. The assessment involved investigations on a country scale as a strategic level, and on river basin, agricultural scheme (both irrigated and rainfed systems) and field scales as operational levels. On a country scale, a general analysis of the vegetation’s Net Primary Productivity (NPP) and Water and Carbon Use Efficiencies (WUE and CUE, respectively) in different land cover types was carried out. A comparison between the land cover types in Sudan and Ethiopia was conducted to understand and compare the impact of inter-annual climate variability on the NPP, WUE and CUE indicators of these different land cover types under relatively different climate regimes. The results of this analysis indicate low magnitude of the three indicators in the land cover types that are in Sudan compared to their counterparts in Ethiopia. Moreover, the response of these indicators to climate variability varies widely among the land cover types. In addition, land cover types such as forests and woody savannah represent important natural sinks for the atmospheric CO2 that need to be protected. These observations suggest the need for effective policies that enhance crop productivity, especially in Sudan, and at the same time ensure preserving the land cover types that are important for climate change mitigation. On a river basin scale, which represented by the Blue Nile Basin (BNB), precipitation estimation is of utmost importance, as it is not only the main source of water in the basin but also because precipitation variability is controlling food production in the agricultural systems, especially in the rainfed schemes. The high spatial and temporal variation in precipitation within the BNB suggests the need for water storage and water harvesting be promoted and practiced. This would ensure water transfer spatially from wet to dry areas and temporally from wet to dry seasons. As a major staple cereal crop in Sudan, the performance of sorghum production in irrigated and rainfed schemes was investigated on agriculture schemes and field scales. A noticeable low and unstable sorghum yield is detected under both agricultural systems. This low performance represents a serious challenge, not only for food production but also for water availability. The current low performance was found to be controlled by many factors of physical, socio-economic and management nature. As many of these factors are closely linked, effectively addressing some of them might induce positive impacts on the other controlling factors. To conclude, the identified synergies and trade-offs of the WFC Nexus could be used as entry points to increase the efficiency of water use and bridge the crop yield gap. Even simple interventions in the field might induce positive effects to the total crop production of the agricultural schemes and water use efficiency. The increase of water availability in the river basin and improved production in the schemes would enhance the overall water and food security in the country and would minimize the need to convert land covers that are important for climate change mitigation into croplands. This paradigm shift needs to be done through a comprehensive sustainable intensification (SI) framework that is not only aimed at increasing crop yield but also targets promoting a healthy environment, improved livelihood, and a growing economy

The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part I: System Description and Data Assimilation Evaluation

The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) updates NASA's previous satellite era (1980 - onward) reanalysis system to include additional observations and improvements to the Goddard Earth Observing System, Version 5 (GEOS-5) Earth system model. As a major step towards a full Integrated Earth Systems Analysis (IESA), in addition to meteorological observations, MERRA-2 now includes assimilation of aerosol optical depth (AOD) from various ground- and space-based remote sensing platforms. Here, in the first of a pair of studies, we document the MERRA-2 aerosol assimilation, including a description of the prognostic model (GEOS-5 coupled to the GOCART aerosol module), aerosol emissions, and the quality control of ingested observations. We provide initial validation and evaluation of the analyzed AOD fields using independent observations from ground, aircraft, and shipborne instruments. We demonstrate the positive impact of the AOD assimilation on simulated aerosols by comparing MERRA-2 aerosol fields to an identical control simulation that does not include AOD assimilation. Having shown the AOD evaluation, we take a first look at aerosol-climate interactions by examining the shortwave, clear-sky aerosol direct radiative effect. In our companion paper, we evaluate and validate available MERRA-2 aerosol properties not directly impacted by the AOD assimilation (e.g. aerosol vertical distribution and absorption). Importantly, while highlighting the skill of the MERRA-2 aerosol assimilation products, both studies point out caveats that must be considered when using this new reanalysis product for future studies of aerosols and their interactions with weather and climate

THE TIBETAN PLATEAU SURFACE ENERGY BUDGET AND ITS TELECONNECTION WITH THE EAST ASIAN SUMMER MONSOON: EVIDENCE FROM GROUND OBSERVATIONS, REMOTE SENSING, AND REANALYSIS DATASETS

Estimations from meteorological stations indicate that the surface sensible heat flux over the Tibetan Plateau has been decreasing continuously since the 1980s. Modeling studies suggest that such change is physically linked to the weakening of the East Asian summer monsoon through Rossby wave trains. However, the relationship between the surface energy budget over the entire Tibetan Plateau and the East Asian summer monsoon rainfall has rarely been examined. The objective of this study is to quantify the relationship between the surface energy budget over the Tibetan Plateau and the East Asian summer monsoon, using ground observations, remote sensing, and reanalysis datasets with three specific questions: What are the spatiotemporal characteristics of the surface radiation and energy budgets over the Tibetan Plateau in recent decades? How does the interannual variation of the surface radiation and energy budgets correlate to, respond to, and impact the observed regional surface and atmospheric anomalies? And can the changes of the surface energy budget component over the Tibetan Plateau explain the weakening of the East Asian summer monsoon and associated precipitation changes in China? To address those questions, I 1) develop a fused monthly surface radiation and energy budgets dataset over the Tibetan Plateau using ground and satellite observations and reanalysis datasets; 2) analyze the spatial distribution of the fused surface radiation and energy budgets, and assess its correlations with the observed surface and atmospheric conditions over the Tibetan Plateau; and 3) test the hypothesis of whether the Asian summer monsoon rainfall is under the impact of the spring sensible heat flux over the Tibetan Plateau through correlation analysis, regression analysis, Granger causality test, and composite analysis. The root mean square errors from cross validation are 18.9 Wm-2, 10.3 Wm-2, 14.3 Wm-2 for the fused monthly surface net radiation, latent heat flux, and sensible heat flux. The fused downward shortwave irradiance, sensible heat flux, and latent heat flux anomalies are consistent with those estimated from meteorological stations. The associations among the fused surface radiation and energy budgets and the related surface anomalies such as mean temperature, temperature range, snow cover, and Normalized Difference Vegetation Index in addition to the atmospheric anomalies such as cloud cover and water vapor show seasonal dependence over the Tibetan Plateau. The decreased late spring sensible heat flux, which is sustained throughout the summer, has been associated with suppressed summer rainfall in the north of China and the north of Indian and enhanced rainfall in the west of India. The mechanism of those associations is found through a lower-level Rossby wave train as a result of anomalous sensible heating over the Tibetan Plateau. The decreased late spring sensible heat flux has also been associated with dry weather in the Yangtze River basin through a descending motion to the east of the Tibetan Plateau. This dissertation is the first synthesized analysis of the surface radiation and energy budgets at a spatial scale covering the entire Tibetan Plateau over a temporal period of two decades. The results of this study could contribute to a better understanding of the land-atmosphere interactions over the Tibetan Plateau, and the role of the Tibetan Plateau sensible heating in regulating the strength of the Asian summer monsoon. This study demonstrates a linkage between the spring sensible heat over the Tibetan Plateau and the Asian summer monsoon rainfall that affect about one fourth of the world's population, which has implications that will benefit local agriculture practices, disaster management, and climate change mitigation