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At least 235 records · Page 13

The Geostationary Fourier Transform Spectrometer

The Geostationary Fourier Transform Spectrometer (GeoFTS) is an imaging spectrometer designed for a geostationary orbit (GEO) earth science mission to measure key atmospheric trace gases and process tracers related to climate change and human activity. GEO allows GeoFTS to continuously stare at a region of the earth for frequent sampling to capture the variability of biogenic fluxes and anthropogenic emissions from city to continental spatial scales and temporal scales from diurnal, synoptic, seasonal to interannual. The measurement strategy provides a process based understanding of the carbon cycle from contiguous maps of carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), and chlorophyll fluorescence (CF) collected many times per day at high spatial resolution (~2.7kmx2.7km at nadir). The CO2/CH4/CO/CF measurement suite in the near infrared spectral region provides the information needed to disentangle natural and anthropogenic contributions to atmospheric carbon concentrations and to minimize uncertainties in the flow of carbon between the atmosphere and surface. The half meter cube size GeoFTS instrument is based on a Michelson interferometer design that uses all high TRL components in a modular configuration to reduce complexity and cost. It is self-contained and as independent of the spacecraft as possible with simple spacecraft interfaces, making it ideal to be a "hosted" payload on a commercial communications satellite mission. The hosted payload approach for measuring the major carbon-containing gases in the atmosphere from the geostationary vantage point will affordably advance the scientific understating of carbon cycle processes and climate change.

atmospheric trace gases↗

The Spatiotemporal Structure of 20th Century Climate Variations in Observations and Reanalyses: Long-term Trend - Part 1

The dominant interannual El Nino-Southern Oscillation phenomenon (ENSO) and the short length of climate observation records make it difficult to study long-term climate variations in the spatiotemporal domain. Based on the fact that the ENS0 signal spreads to remote regions and induces delayed climate variation through atmospheric teleconnections, we develop an ENSO-removal method through which the ENS0 signal can be approximately removed at the grid box level from the spatiotemporal field of a climate parameter. After this signal is removed, long-term climate variations, namely, the global warming trend (GW) and the Pacific pan-decadal variability (PDV), are isolated at middle and low latitudes in the climate parameter fields from observed and reanalyses datasets. Except for known GW characteristics, the warming that occurs in the Pacific basin (approximately 0.4K in the 2oth century) is much weaker than in surrounding regions and the other two ocean basins (approximately 0.8K). The modest warming in the Pacific basin is likely due to its dynamic nature on the interannual and decadal time scales and/or the leakage of upper ocean water through the Indonesian Throughflow. Based on NCEP/NCAR and ERA-40 reanalyses, a comprehensive atmospheric structure associated with GW is given. Significant discrepancies exist between the two datasets, especially in the tightly coupled dynamic and water vapor fields. The dynamic field based on NCEP/NCAR reanalysis, which shows a change in the Walker Circulation, is consistent with the GW change in the surface temperature field. However, intensification in the Hadley Circulation is associated with GW trend in the ERA-40 reanalysis.

Chen, Junye↗

Recent Progress on Deep Blue Aerosol Algorithm as Applied TO MODIS, SEA WIFS, and VIIRS, and Their Intercomparisons with Ground Based and Other Satellite Measurements

The impact of natural and anthropogenic sources of aerosols has gained increasing attention from scientific communities in recent years. Indeed, tropospheric aerosols not only perturb radiative energy balance by interacting with solar and terrestrial radiation, but also by changing cloud properties and lifetime. Furthermore, these anthropogenic and natural air particles, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across oceans and continents resulting in important biogeochemical impacts on the ecosystem. With the launch of SeaWiFS in 1997, Terra/MODIS in 1999, and Aqua/MODIS in 2002, high quality comprehensive aerosol climatology is becoming feasible for the first time. As a result of these unprecedented data records, studies of the radiative and biogeochemical effects due to tropospheric aerosols are now possible. In this talk, we will demonstrate how this newly available SeaWiFS/MODIS aerosol climatology can provide an important piece of puzzles in reducing the uncertainty of estimated climatic forcing due to aerosols. We will start with the global distribution of aerosol loading and their variabilities over both land and ocean on short- and long-term temporal scales observed over the last decade. The recent progress made in Deep Blue aerosol algorithm on improving accuracy of these Sea WiFS / MODIS aerosol products in particular over land will be discussed. The impacts on quantifying physical and optical processes of aerosols over source regions of adding the Deep Blue products of aerosol properties over bright-reflecting surfaces into Sea WiFS / MODIS as well as VIIRS data suite will also be addressed. We will also show the intercomparison results of SeaWiFS/MODIS retrieved aerosol optical thickness with data from ground based AERONET sunphotometers over land and ocean as well as with other satellite measurements. The trends observed in global aerosol loadings of both natural and anthropogenic sources based upon more than a decade of combined MODIS/SeaWiFS data (1997-2011) will be discussed. We will also address the importance of various key issues such as differences in spatial-temporal sampling rates and observation time between different satellite measurements could potentially impact these intercomparisons results, especially for using the monthly mean data, and thus on estimates of long-term aerosol trends.

Hsu, N. Christina↗

Variability of Surface Temperature and Melt on the Greenland Ice Sheet, 2000-2011

Enhanced melting along with surface-temperature increases measured using infrared satellite data, have been documented for the Greenland Ice Sheet. Recently we developed a climate-quality data record of ice-surface temperature (IST) of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) 1ST product -- http://modis-snow-ice.gsfc.nasa.gov. Using daily and mean monthly MODIS 1ST maps from the data record we show maximum extent of melt for the ice sheet and its six major drainage basins for a 12-year period extending from March of 2000 through December of 2011. The duration of the melt season on the ice sheet varies in different drainage basins with some basins melting progressively earlier over the study period. Some (but not all) of the basins also show a progressively-longer duration of melt. The short time of the study period (approximately 12 years) precludes an evaluation of statistically-significant trends. However the dataset provides valuable information on natural variability of IST, and on the ability of the MODIS instrument to capture changes in IST and melt conditions indifferent drainage basins of the ice sheet.

Hall, Dorothy K.↗

A Multi-Satellite Assimilation and Modeling Platform to Construct a Global and Complete view of the Hydrologic Cycle

What captivates me about the research field of satellite remote sensing of the earth system science is the opportunity to help human beings by addressing challenging questions related to the current and future availability of natural resources for domestic, agricultural, and industrial needs. For example, a continuously varying climate poses a threat to the water resource, not only in developing countries, but also in economically well-developed regions, creating the urgent need to characterize and predict its spatial and temporal availability. Specifically, my curiosity is driven by the challenge of merging cutting-edge space technology and earth observations (i.e., remote sensing) with state-of-the-art models for the purpose of improving our scientific knowledge about the variability and the change of the hydrologic cycle.The only practical way to observe the land surface processes (e.g., hydrologic cycle) on continental to global scales is via satellite remote sensing. Though remote sensing can make spatially comprehensive measurements of various components of the land surface system, it cannot provide direct information on the entire system, and the measurements represent only a snapshot in time. Physical based models may be used to continuously predict the temporal and spatial earth processes, but these predictions are often poor, due to model initialization, parameter and meteorological forcing errors, and inadequate model physics and/or resolution. Thus, an attractive prospect is to combine the strengths of land surface models and observations (and minimize the weaknesses of both) to provide a superior land surface state estimate. This is the goal of land surface data assimilation. Data assimilation provides a better estimate of the environmental states than either models or observations could individually do. The broad concept of data assimilation can be applied to various disciplines such as hydrology, ecology, environmental hazards, agriculture and economy.My research is targeted to integrating multiple satellite information having multi-sensor and multi-resolution assimilation within today's state-of-the-art hydrologic models. Multi-sensor and multi-resolution assimilation techniques represent a necessary milestone in future earth science applications because they offer the capability of comprehensively integrating disparate types of earth observations via deep-learning techniques. A multi-satellite assimilation and modeling platform will ultimately provide a robust and complete dataset to more fully understand earth's dynamics. In fact, the multi-satellite assimilation platforms build a comprehensive description of the earth processes that is geared toward accurately representing the complexity of natural and anthropogenic interactions in land surface processes. Most importantly, these platforms are suitable as decision support tools for applications across different aspects of earth system science.My recent work has focused on recent multi-sensor data assimilation techniques targeted at improving snow, soil moisture, groundwater, and terrestrial water storage hydrological states.

Girotto, Manuela↗

Orbiting Carbon Observatory

Human impact on the environment has produced measurable changes in the geological record since the late 1700s. Anthropogenic emissions of CO2 today may cause the global climate to depart for its natural behavior for many millenia. CO2 is the primary anthropogenic driver of climate change. The Orbiting Carbon Observatory goals are to help collect measurements of atmospheric CO2, answering questions such as why the atmospheric CO2 buildup varies annually, the roles of the oceans and land ecosystems in absorbing CO2, the roles of North American and Eurasian sinks and how these carbon sinks respond to climate change. The present carbon cycle, CO2 variability, and climate uncertainties due atmospheric CO2 uncertainties are highlighted in this presentation.

orbiting carbon observatory (OCO)↗

Reducing the Uncertainties in Direct Aerosol Radiative Forcing

Airborne particles, which include desert and soil dust, wildfire smoke, sea salt, volcanic ash, black carbon, natural and anthropogenic sulfate, nitrate, and organic aerosol, affect Earth's climate, in part by reflecting and absorbing sunlight. This paper reviews current status, and evaluates future prospects for reducing the uncertainty aerosols contribute to the energy budget of Earth, which at present represents a leading factor limiting the quality of climate predictions. Information from satellites is critical for this work, because they provide frequent, global coverage of the diverse and variable atmospheric aerosol load. Both aerosol amount and type must be determined. Satellites are very close to measuring aerosol amount at the level-of-accuracy needed, but aerosol type, especially how bright the airborne particles are, cannot be constrained adequately by current techniques. However, satellite instruments can map out aerosol air mass type, which is a qualitative classification rather than a quantitative measurement, and targeted suborbital measurements can provide the required particle property detail. So combining satellite and suborbital measurements, and then using this combination to constrain climate models, will produce a major advance in climate prediction.

Kahn, Ralph A.↗

The challenge of identifying greenhouse gas-induced climatic change

Meeting the challenge of identifying greenhouse gas-induced climatic change involves three steps. First, observations of critical variables must be assembled, evaluated, and analyzed to determine that there has been a statistically significant change. Second, reliable theoretical (model) calculations must be conducted to provide a definitive set of changes for which to search. Third, a quantitative and statistically significant association must be made between the projected and observed changes to exclude the possibility that the changes are due to natural variability or other factors. This paper provides a qualitative overview of scientific progress in successfully fulfilling these three steps.

Maccracken, Michael C.↗

Usefulness of AIRS-Derived OLR, Temperature, Water Vapor and Cloudiness Anomaly Time-series for GCM Validation

The ROBUST nature (biases are not as important as previous GCM-evaluations suggest) of the AIRS-observations-generated ARC-maps and ATs as well as their interrelations suggest that they could be a useful tool to select CGCMs which may be considered the reliable, i.e., to be trusted even for longer-term climate drift/change predictions (even on the regional scale). Get monthly gridded CGCM time-series of atmospheric variables coinciding with the timeframe of the AIRS analyses for at least 5-6 years and do the actual evaluations of ARC-maps and ATs for the coinciding time periods.

Molnar, Gyula↗

The Dynamics of a Semi-Arid Region in Response to Climate and Water - Use Policy

The objectives of this project were to determine the response of semi-arid ecosystems to the combined forcings of climate variability and anthropogenic stress. Arid and semi-arid systems encompass close to 40% of the worlds land surface. The ecology of these regions are principally limited by water, and as the water resources wax and wane, so should the health and vigor of the ecosystems. Water, however, is a necessary and critical resource for humans living in these same regions. Thus for many and and semi-arid regions the natural systems and human systems are in direct competition for a limited resource. Increasing competition through development of and and semi-arid regions, export of water resources, as well as potential persistent changes in weather patterns are likely to lead to fundamental changes in carrying capacity, resilience, and ecology of these regions. A detailed understanding of these systems respond to forcing on a regional and local scale is required in order to better prepare for and manage future changes in the availability of water. In the Owens Valley CA, decadal changes in rainfall and increased use of groundwater resources by Los Angles (which derives 60-70% of its water from this region) have resulted in a large-scale experiment on the impacts of these changes in semi-arid ecosystems. This project works directly with the Inyo County Water Department (local water authority) and the Los Angles Department of Water and Power (regional demand on water resources) to understand changes, their causes, and impacts. Very detailed records have been kept for a number of selected sites in the valley which provide essential ground truth. These results are then scaled up through remote sensed data to regions scale to assess large scale patterns and link them to the fundamental decisions regarding the water resources of this region. A fundamental goal is to understand how resilient the native ecosystems are to large changes in water resources. Are they are on a spring (remove and return resources, do the systems return to the original state) or a vector (when water returns have the systems fundamentally changed).

Mustard, John F.↗

Future Lightning Instruments for Weather and Climate Monitoring From LEO

Lightning is not only a natural hazard, but it also holds information about physical processes at work in deep convection and influences atmospheric oxidants that modulate ozone and methane. Hence, spaceborne lightning observations are essential for monitoring extreme events and feedbacks in Earth’s climate system. Low-Earth orbiting (LEO) lightning mapping instruments established a 25-year record of global lightning activity and resulted in a wealth of studies that motivated its designation as an Essential Climate Variable by the World Meteorological Organization. Although geostationary observations of lightning have become increasingly available since 2017, LEO lightning mappers continue to serve critical needs given their unique vantage point and acceptance as a unifying reference for geostationary lightning mapper and ground-based global lightning datasets. At the close of 2023, the Lightning Imaging Sensor (LIS) will cease operations on the International Space Station, which introduces a critical gap in LEO-based monitoring of global lightning activity. To address this need, NASA is developing new lightning mapping technology that enables future LEO-based satellite missions. Existing LEO-based lightning mappers rely on narrowband optical emissions centered on 777.4-nm and detectors that capture 500 images per second to detect lightning both day and night. Lightning can also produce optical emissions in a narrowband centered on 337-nm without any corresponding emissions at the traditionally used near-infrared (NIR) wavelength. These near-ultraviolet (UV) emissions are associated with earlier stage electrical breakdown (e.g., streamers), may frequent intense regions of deep convective storms, and may be a significant source of nitrogen oxide production in the upper atmosphere. A new lightning mapping instrument called the CubeSat Lightning Imaging and Detection Experiment (CLIDE) is being designed at NASA Marshall Space Flight Center to use high-speed, scientific CMOS image sensors capable of detecting lightning’s transient optical emissions in the near-UV and NIR during both daylit and nighttime scenes. This will extend the record of global lightning activity and help pave the way for future small satellite missions that combine radio and optical lightning detectors to obtain novel three-dimensional maps of lightning on a global scale, which can revolutionize the way lightning is used to monitor weather and understand changes in climate.

lightning↗

InVEST Urban Development: Incorporating Earth Observation Data into the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model Python API

Urban flooding poses as one of the biggest issues for cities today, as its impacts are amplified by both climate change and urbanization. The Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation (UFRM) model, which benefits from its simplicity and robustness, is commonly used in NASA DEVELOP projects for disaster mitigation, urban planning, and environmental justice issues. While InVEST UFRM model was able to produce the surface water runoff and retention map sufficient for the scopes of past projects, the model accuracy and spatial variability need improvement. Since the current InVEST UFRM model employs constant rainfall depth for all pixels in the area of interest (AOI), the model suffers from inaccurately estimating rainfall depth, runoff volume, and flood depth. Therefore, we adapted the model so that satellite-based precipitation raster datasets (i.e., Integrated Multi-satellitE Retrievals for Global Precipitation Measurement [GPM IMERG]) can be used instead of a single constant value. We simulated the flood events on August 21st and August 22nd, 2017 in Wyandotte County, Kansas using both our modified and the original InVEST UFRM model and then compared the results after incorporating the rainfall raster into the model. Areas with developed land on the land use map predicted moderate to high flood volume in the original volume regardless of the actual amount of precipitation. The modified model considered the rainfall depth’s spatial variation achieving less overestimation of flood runoff and volume at low-to-moderate rainfall area.

Son Do↗

Aerosol-Cloud-Precipitation Interactions over Indo-Gangetic Basin

About 60% of world population reside in Asia, in term of which sheer population density presents a major environmental stress. Economic expansion in this region is, in fact, accompanied by increases in bio-fuel burning, industrial pollution, and land cover and land use changes. With a growth rate of approx. 8%/yr for Indian economy, more than 600 million people from Lahore, Pakistan to Calcutta, India over the Indo-Gangetic Basin have particularly witnessed increased frequencies of floods and droughts as well as a dramatic increase in atmospheric loading of aerosols (i.e., anthropogenic and natural aerosol) in recent decades. This regional change (e.g., aerosol, cloud, precipitation, etc.) will constitute a vital part of the global change in the 21st century. Better understanding of the impacts of aerosols in affecting monsoon climate and water cycles is crucial in providing the physical basis to improve monsoon climate prediction and for disaster mitigation. Based on climate model simulations, absorbing aerosols (dust and black carbon) play a critical role in affecting interannual and intraseasonal variability of the Indian monsoon. An initiative on the integrated (aerosols, clouds, and precipitation) measurements approach over the Indo-Gangetic Basin will be discussed. An array of ground-based (e.g., AERONET, MPLNET, SMART-COMMIT, etc.) and satellite (e.g., Terra, A-Train, etc.) sensors will be utilized to acquire aerosol characteristics, sources/sinks, and transport processes during the pre-monsoon (April-May, aerosol forcing) season, and to obtain cloud and precipitation properties during the monsoon (May-June, water cycle response) season. Close collaboration with other international programs, such as ABC, CLIVAR, GEWEX, and CEOP in the region is anticipated.

Tsay, S.-C.↗

Near Real-Time Flood Monitoring and Impact Assessment Systems

Floods are the costliest natural disaster (United Nations 2004), causing approximately6.8 million deaths in the twentieth century alone (Doocy et al. 2013).Worldwide economic flood damage estimates in 2012 exceed $19 Billion USD(Munich Re 2013). Extended duration floods also pose longer term threats to food security, water, sanitation, hygiene, and community livelihoods, particularly in developing countries (Davies et al. 2014).Projections by the Intergovernmental Panel on Climate Change (IPCC) suggest that precipitation extremes, rainfall intensity, storm intensity, and variability are increasing due to climate change (IPCC 2007). Increasing hydrologic uncertainty will likely lead to unprecedented extreme flood events. As such, there is a vital need to enhance and further develop traditional techniques used to rapidly assessflooding and extend analytical methods to estimate impacted population and infrastructure.

flood↗

InVEST Urban Development: Incorporating Earth Observation Data into the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model Python API

Urban flooding poses as one of the biggest issues for cities today as its impacts are amplified by both climate change and urbanization. The Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation (UFRM) model, which benefits from its simplicity and robustness, is commonly used in NASA DEVELOP projects for disaster mitigation, urban planning, and environmental justice issues. While the InVEST UFRM model was able to produce the surface water runoff and retention map sufficient for the scopes of past projects, the model’s accuracy and spatial variability need improvement. Since the current InVEST UFRM model employs constant rainfall depth for all pixels in the area of interest (AOI), the model suffers from inaccurately estimating rainfall depth, runoff volume, and flood depth. Therefore, we adapted the model so that satellite-based precipitation raster datasets (i.e., Integrated Multi-satellitE Retrievals for Global Precipitation Measurement [GPM IMERG]) can be used instead of a single constant value. We simulated the flood events on August 21st and August 22nd, 2017, in Wyandotte County, Kansas using both our modified and the original InVEST UFRM model and then compared the results after incorporating rainfall raster into the model. Areas with developed land on the land use map predicted moderate to high flood volume in the original volume regardless of the actual amount of precipitation. The modified model considered the rainfall depth’s spatial variation achieving less overestimation of flood runoff and volume at low-to-moderate rainfall area.

Urban flooding↗

Evapotranspiration as a Regional Climate Priority: Results from a NASA/USDA Workshop

On April 5 to 7, 2011, the National Aeronautics and Space Administration (NASA) and the United States Department of Agriculture-Agricultural Research Service (USDA-ARS) sponsored a Workshop on Evapotranspiration (ET) in Silver Spring Maryland. The workshop was a response to a recommendation in the 2009-2011 GEO (Group on Earth Observations) Work Plan that a workshop on ET should be held to discuss issues related to ET products and services and the potential for incorporating ET activities into the 2012-2015 GEO Work Plan. The workshop had a regional emphasis, although there were several excellent international and global presentations including one on the GEWEX LANDFLUX project. The different scales of these activities suggests that a framework is needed that can accommodate both regional and global ET activities. Despite limitations with the workshop's scheduling, it attracted 76 experts who contributed informative presentations and insightful discussions. The goals of the workshop involved the exchange of information and ideas and the development of plans for providing more visibility for ET issues. Specific objectives included 1) defining the needs and requirements for evapotranspiration data in weather and climate studies, in natural and agro-ecoystem monitoring, and in water resource management; 2) reviewing the methods used to measure and model evapotranspiration; 3) assessing surface and satellite observation systems required to support ET measurement, modeling and evaluation; 4) assessing the feasibility of developing a proposal for a task on evapotranspiration for the 2012-2015 GEO Work Plan, and 5) exploring the level of support and consensus for developing a strategy for establishing evapotranspiration as an Essential Climate Variable (ECV) within the Global Climate Observing System (GCOS) framework The workshop featured a combination of oral presentations and breakout group sessions focused on the above objectives. There were also poster presentations providing opportunities for one-on-one discussions of ET modeling and measurement techniques. Presentations by users of ET data set the tone for the workshop. In the USA at the national and regional levels water rights issues represent a major opportunity for ET applications. ET data play a major role in estimating water loss due to irrigation, the largest cause of consumptive water loss in the USA, particularly in the West. Irrigation requirements are relatively specific since the needs are clearly defined by the geometry and number of the irrigation systems and can be monitored with high resolution satellite data. There was a strong consensus that land surface temperature (LST) at high resolution is critical for monitoring irrigation. State governments have made commitments to more efficient water management in the western US, but they need full access to improved and more timely ET data and applications to implement this plan. Water managers also reported that in spite of the recent development of. new techniques, the procedures used in some of the water balance calculations in some states are out of date and do not take advantage of new observational and data assimilation systems. The development of ET forecasts for water management is also seen as a priority. Although ET forecasts are currently being produced on an experimental basis these predictions could be improved by considering ET as a dynamic prediction variable in models and by increasing the time resolution of these ET predictions.

Lawford, Richard↗

An Assessment of the Potential Predictability of Interannual and Decadal Variability Based on Climate Model Simulations with Specified SST

The USCLIVAR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. The runs were done with several global atmospheric models including NASA/NSIPP-1, NCEP/GFS, GFDL/AM2, and NCAR CCM3 and CAM3.5. Here we focus on the potential predictability associated with the leading patterns of inter-annual and decadal Pacific SST variability. Specific issues addressed include the nature of the seasonality and regionality of the signal, the noise, and the signal-to-noise ratios, as well as the dependence of the results on the models.

Schubert, Siegfried↗

Identifying and Evaluating the Relationships that Control a Land Surface Model's Hydrological Behavior

The inherent soil moisture-evaporation relationships used in today 's land surface models (LSMs) arguably reflect a lot of guesswork given the lack of contemporaneous evaporation and soil moisture observations at the spatial scales represented by regional and global models. The inherent soil moisture-runoff relationships used in the LSMs are also of uncertain accuracy. Evaluating these relationships is difficult but crucial given that they have a major impact on how the land component contributes to hydrological and meteorological variability within the climate system. The relationships, it turns out, can be examined efficiently and effectively with a simple water balance model framework. The simple water balance model, driven with multi-decadal observations covering the conterminous United States, shows how different prescribed relationships lead to different manifestations of hydrological variability, some of which can be compared directly to observations. Through the testing of a wide suite of relationships, the simple model provides estimates for the underlying relationships that operate in nature and that should be operating in LSMs. We examine the relationships currently used in a number of different LSMs in the context of the simple water balance model results and make recommendations for potential first-order improvements to these LSMs.

Koster, Randal D.↗