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NASA NTRS1991

Satellite estimation of incident photosynthetically active radiation using ultraviolet reflectance

A new satellite remote sensing method for estimating the amount of photosynthetically active radiation (PAR, 400-700 nm) incident at the earth's surface is described and tested. Potential incident PAR for clear sky conditions is computed from an existing spectral model. A major advantage of the UV approach over existing visible band approaches to estimating insolation is the improved ability to discriminate clouds from high-albedo background surfaces. UV spectral reflectance data from the Total Ozone Mapping Spectrometer (TOMS) were used to test the approach for three climatically distinct, midlatitude locations. Estimates of monthly total incident PAR from the satellite technique differed from values computed from ground-based pyranometer measurements by less than 6 percent. This UV remote sensing method can be applied to estimate PAR insolation over ocean and land surfaces which are free of ice and snow.

Eck, Thomas F.↗
NASA NTRS2008

Climate Quality Broadband and Narrowband Solar Reflected Radiance Calibration Between Sensors in Orbit

vAs the potential impacts of global climate change become more clear [1], the need to determine the accuracy of climate prediction over decade-to-century time scales has become an urgent and critical challenge. The most critical tests of climate model predictions will occur using observations of decadal changes in climate forcing, response, and feedback variables. Many of these key climate variables are observed by remotely sensing the global distribution of reflected solar spectral and broadband radiance. These "reflected solar" variables include aerosols, clouds, radiative fluxes, snow, ice, vegetation, ocean color, and land cover. Achieving sufficient satellite instrument accuracy, stability, and overlap to rigorously observe decadal change signals has proven very difficult in most cases and has not yet been achieved in others [2]. One of the earliest efforts to make climate quality observations was for Earth Radiation Budget: Nimbus 6/7 in the late 1970s, ERBE in the 1980s/90s, and CERES in 2000s are examples of the most complete global records. The recent CERES data products have carried out the most extensive intercomparisons because if the need to merge data from up to 11 instruments (CERES, MODIS, geostationary imagers) on 7 spacecraft (Terra, Aqua, and 5 geostationary) for any given month. In order to achieve climate calibration for cloud feedbacks, the radiative effect of clear-sky, all-sky, and cloud radiative effect must all be made with very high stability and accuracy. For shortwave solar reflected flux, even the 1% CERES broadband absolute accuracy (1-sigma confidence bound) is not sufficient to allow gaps in the radiation record for decadal climate change. Typical absolute accuracy for the best narrowband sensors like SeaWiFS, MISR, and MODIS range from 2 to 4% (1-sigma). IPCC greenhouse gas radiative forcing is approx. 0.6 W/sq m per decade or 0.6% of the global mean shortwave reflected flux, so that a 50% cloud feedback would change the global reflected flux by approx. 0.3 W/sq m or 0.3% per decade in broadband SW calibration change. Recent results comparing CERES reflected flux changes with MODIS, MISR, and SeaWiFS narrowband changes concluded that only SeaWiFS and CERES were approaching sufficient stability in calibration for decadal climate change [3]. Results using deep convective clouds in the optically thick limit as a stability target may prove very effective for improving past data sets like ISCCP. Results for intercalibration of geostationary imagers to CERES using an entire month of regional nearly coincident data demonstrates new approaches to constraining the calibration of current geostationary imagers. The new Decadal Survey Mission CLARREO is examining future approaches to a "NIST-in-Orbit" approach of very high absolute accuracy reference radiometers that cover the full solar and infrared spectrum at high spectral resolution but at low spatial resolution. Sampling studies have shown that a precessing CLARREO mission could calibrate other geo and leo reflected solar radiation and thermal infrared sensors.

Wielicki, Bruce A.↗
NASA NTRS2022

Chapter 10 - Remote Sensing Measurements of Aerosol Properties

Satellite instruments have proven especially capable at monitoring the quantity of airborne particles in columns of atmosphere, globally. This chapter describes the principles of satellite measurements and retrieval algorithms, and surveys current instruments and their capabilities. We outline the issues associated with retrieval algorithms, such as surface characterization and aerosol proximity to clouds, and the challenges with interpretation of the results. The relationship between measured aerosol properties and climate-relevant aerosol properties simulated in models is outlined, as well as how measurements are used to evaluate models. Most space-based aerosol instruments are passive sensors that measure reflected sunlight at multiple wavelengths, some at multiple viewing angles. A few are active sensors that send out their own laser light and measure the returned signal. Except when clouds are present, the excess amount of light scattered back to space, beyond that expected from the surface and atmospheric gas, is attributed to aerosol. Satellite measurements are used in many ways in aerosol research. They often provide the only method for monitoring hazardous phenomena such as major wildfire and volcanic eruption plumes, especially in remote areas. Stable, long-term, near-global-scale satellite data records make it possible to identify regional and global aerosol trends. Aerosol radiative effects on climate can be quantified on a near-global scale and used to estimate the strength of aerosol–radiation and aerosol–cloud interactions as well as to evaluate climate model simulations of these interactions. Aerosol-type mapping from satellite imagery is helpful for source attribution, model validation, and to constrain particle light-absorption properties that are essential for radiative forcing calculations. The range of aerosol properties retrieved from satellite observations has grown considerably since the first global estimates of aerosol optical depth (τ a) over ocean were made in the late 1970s. Methods for retrieving particle size and light-absorption properties were explored in the 1990s using multispectral, multi-angle observations, and polarization in visible and near-infrared wavelengths. Sensitivity to particle light absorption, primarily from black or brown carbon content, improved with the inclusion of UV channels, and sensitivity to very thin aerosol layers in the upper troposphere and lower stratosphere was advanced with the use of limb-sounding instruments and active sensors. There are limitations to every measurement technique, including satellite aerosol remote sensing. For wide-swath, passive instruments, aerosol retrievals near clouds can present substantial challenges as far as 15 km away due to cloud-scattered light contaminating the signal. In nearly all cases, retrievals over bright snow and ice surfaces are precluded because surface reflectance uncertainties can overwhelm the aerosol signal. Similarly, meteorological cloud is identified and masked out where possible. Data from passive sensors also lack vertical resolution except those that view toward the limb or where multi-angle imagery is acquired over plumes from wildfires, erupting volcanoes, and wind-blown dust. Yet, passive sensors provide vastly more coverage than the active instruments that mitigate these issues. Particle microphysical information is qualitative from all remote sensing techniques, relying on proxies to infer particle composition, hygroscopicity, and the amount of light-absorbing material. Further, particles smaller than about 200 nm diameter cannot be distinguished from atmospheric gas molecules with remote sensing, which hinders studies of cloud condensation nuclei and their effects on clouds. Most satellite instruments dedicated to aerosol observations are in low-Earth, near-polar, sun-synchronous orbits, which means they cross the equator at the same local time each day. Most are set on cycles that repeat approximately every 16 days, which makes it difficult to monitor aerosol evolution locally. Geostationary satellites make it possible to observe changes occurring from minutes to hours over regions up to 8000 km in size, but lack coverage of high latitudes, and often provide more limited constraints on aerosol properties. Ground-truth data are vital for satellite aerosol-retrieval validation. The AErosol RObotic NETwork (AERONET) of sun photometers was created in 1993 and has become an established global network of over 350 instruments for validating satellite measurements. The network, as well as global networks of ground-based lidars, solar flux radiometers and other sun photometers, are widely used for evaluating global satellite retrievals and model simulations. NASA's Earth Observing System (EOS) program beginning in 1999 led to improvements in reliability, spatial resolution, and spectral resolution (and hence, to improved particle size discrimination and light absorption properties). Satellite payloads include advanced broad-swath and multi-angle imagers, along with the first space-based active sensor focused largely on long-term aerosol monitoring. Since about 2002, Europe's SENTINEL and operational meteorological satellite fleets are also providing sustained aerosol observations, with planned continuation until at least 2030. Satellite remote sensing instruments offer valuable data for evaluating aerosol representations in global climate models. They have been used to assess aerosol optical and physical properties, trends and distributions, and are applied increasingly as direct model constraints in data assimilation to create global aerosol reanalysis products. Aerosol optical depth is the most common quantity adopted for routine model evaluation, including multiwavelength data to loosely constrain particle-size distributions. These evaluations of multiple models have revealed general biases in their regional aerosol amounts and seasonal patterns of transport and removal. Although satellite measurements have near-global coverage, substantial errors can be introduced into the model observation comparison unless attention is paid to spatial and temporal collocation, cloud screening, subgrid-scale variability, and measurement uncertainties that vary with retrieval conditions.

aerosol properties↗
NASA NTRS2015

IOCCG Report Number 16, 2015 Ocean Colour Remote Sensing in Polar Seas : The Polar Environment: Sun, Clouds, and Ice - Chapter 2

The polar regions are places of extremes. There are months when the regions are enveloped in unending darkness, and months when they are in continuous daylight. During the daylight months the sun is low on the horizon and often obscured by clouds. In the dark winter months temperatures are brutally cold, and high winds and blowing snow are common. Even in summer, temperatures seldom rise above 0degC. The cold winter temperatures cause the ocean to freeze, forming sea ice. This sea ice cover acts as a barrier limiting the transfer of heat, moisture, and momentum between the atmosphere and the ocean. It also greatly complicates the optical signature of the surface. Taken together, these factors make the polar regions a highly challenging environment for optical remote sensing of the ocean.

ocean colour↗
NASA NTRS1977

Multispectral remote observations of hydrologic features on the North Slope of Alaska

Visible and near-infrared Landsat satellite imagery and active and passive aircraft microwave data are used to analyze some hydrologic features in Arctic Alaska. Lake studies using passive microwave imagery reveal that an increase in the microwave brightness temperature correlates with an increase in ice thickness. Synthetic Aperture Radar (SAR) imagery allows determination of lakes that are frozen to the bottom under certain conditions. Landsat imagery of lakes can be used to study summer ice cover dissipation, an indicator of lake depth. River channel morphometry and morphology studies are accomplished using SAR data with good (25 m) resolution. Landsat imagery is shown to be useful for analyzing interannual variations in the extent of river icings (aufeis). Snow depth variations are shown to be potentially discernable using passive microwave data. Finally, the present and potential applications of these remote sensing studies are discussed; these data are useful for locating potable water sources, planning construction in good locations, and for analyzing interannual climate fluctuations.

Hall, D. K.↗
NASA NTRS1985

General Report of the Researches of Snowpack Properties, Snowmelt Runoff and Evapotranspiration in Japan

A method was developed for estimating the distribution of snow and the snow water equivalent in Japan by combining LANDSAT data with the degree day method. A snow runoff model was improved and applied to the Okutadami River basin. The Martinec Rango model from the U.S. was applied to Japanese river basins to verify its applicability. This model was then compared with the Japanese model. Analysis of microwave measurements obtained by a radiometer on a tower over dry snow in Hokkaido indicate a certain correlation between brightness temperature and snowpack properties. A correlation between brightness temperature and depth of dry snow in an inland plain area was revealed in NIMBUS SMMR data obtained from the U.S. Calculation of evaporation using airborne remote sensing data and a Priestley-Taylor type of equation shows that the differentiation of evaporation with vegetation type is not remarkable because of little evapotransportation in winter.

Takeda, K.↗
NASA NTRS1990

Remote sensing contribution to land surface hydrology

Progress that has been made over the past decade in developing technology for hydrological observations from operational aircraft is described. Particular attention is given to research on soil moisture, snow cover, and vegetation. Future missions such as the ESA ERS-1 and Canada's Radarsat mission are considered.

Salomonson, V. V.↗
NASA NTRS2005

[Multi-Scale Convergence of Cold-Land Process Representation in Land-Surface Models, Microwave Remote Sensing, and Field Observations]

The cryosphere is a major component of the hydrosphere and interacts significantly with the global climate system, the geosphere, and the biosphere. Measurement of the amount of water stored in the snow pack and forecasting the rate of melt are thus essential for managing water supply and flood control systems. Snow hydrologists are confronted with the dual problems of estimating both the quantity of water held by seasonal snow packs and time of snow melt. Monitoring these snow parameters is essential for one of the objectives of the Earth Science Enterprise-understanding of the global hydrologic cycle. Measuring spatially distributed snow properties, such as snow water equivalence (SWE) and wetness, from space is a key component for improvement of our understanding of coupled atmosphere-surface processes. Through the GWEC project, we have significantly advanced our understandings and improved modeling capabilities of the microwave signatures in response to snow and underground properties.

Shi, Jiancheng↗
NASA NTRS2013

Using Air Temperature to Quantitatively Predict the MODIS Fractional Snow Cover Retrieval Errors over the Continental US (CONUS)

In the middle to high latitude and alpine regions, the seasonal snow pack can dominate the surface energy and water budgets due to its high albedo, low thermal conductivity, high emissivity, considerable spatial and temporal variability, and ability to store and then later release a winters cumulative snowfall (Cohen, 1994; Hall, 1998). With this in mind, the snow drought across the U.S. has raised questions about impacts on water supply, ski resorts and agriculture. Knowledge of various snow pack properties is crucial for short-term weather forecasts, climate change prediction, and hydrologic forecasting for producing reliable daily to seasonal forecasts. One potential source of this information is the multi-institution North American Land Data Assimilation System (NLDAS) project (Mitchell et al., 2004). Real-time NLDAS products are used for drought monitoring to support the National Integrated Drought Information System (NIDIS) and as initial conditions for a future NCEP drought forecast system. Additionally, efforts are currently underway to assimilate remotely-sensed estimates of land-surface states such as snowpack information into NLDAS. It is believed that this assimilation will not only produce improved snowpack states that better represent snow evolving conditions, but will directly improve the monitoring of drought.

MODIS↗
NASA NTRS2005

Arctic Warming Signals from Satellite Observations

Global warming signals are expected to be amplified in the Arctic primarily because of ice-albedo feedback associated with the high reflectivity of ice and snow that blankets much of the region. The Arctic had been a poorly explored territory basically because of its general inaccessibility on account of extremely harsh weather conditions and the dominant presence of thick perennial ice in the region. The advent of satellite remote sensing systems since the 1960s, however, enabled the acquisition of synoptic data that depict in good spatial detail the temporal changes of many Arctic surface parameters. Among the surface parameters that have been studied using space based systems are surface temperature, sea ice concentration, snow cover, surface albedo and phytoplankton concentration. Associated atmospheric parameters, such as cloud cover, temperature profile, ozone concentration, and aerosol have also been derived. Recent observational and phenomenological studies have indeed revealed progressively changing conditions in the Arctic during the last few decades (e g , Walsh et al. 1996; Serreze et al 2000; Comiso and Parkinson 2004). The changes included declines in the extent and area of surfaces covered by sea ice and snow, increases in melt area over the Greenland ice sheets, thawing of the permafrost, warming in the troposphere, and retreat of the glaciers. These observations are consistent with the observed global warming that has been associated with the increasing concentration of greenhouse gases in the atmosphere (Karl and Trenberth 2003) and confirmed by modeling studies (Holland and Bitz, 2003). The Arctic system, however, is still not well understood complicated by a largely fluctuating wind circulation and atmospheric conditions (Proshutinsky and Johnson 1997) and controlled by what is now known as the Arctic Oscillation (AO) which provides a measure of the strength of atmospheric activities in the region (Thompson and Wallace 1998). Meanwhile, the observed Arctic conditions since the 1970s have been shown to exhibit a linear behavior that directly contradicts what has been expected from the A0 (Overland, 2005). The decade of the 1990s has been regarded as the warmest decade in the last century and current data indicates that the 2000s may be even a warmer decade than the 1990s further supporting the linear variability. In this paper, we use satellite data to gain insights into the warming Arctic and how the abnormally warm conditions during the last few years are reflected in the region.

Comiso, Josefino C.↗
NASA NTRS1979

Active remote sensing of layered random media

Analytical expressions for the backscattering cross sections have been derived for active remote sensing of an arbitrary number of random layers. These results are applicable to the interpretation of radar backscattering from vegetation and snow-ice fields. We illustrate the results by matching experimental data using the model of a three-layer random medium with air above and ground below.

Zuniga, M. A.↗
NASA NTRS1983

Spaceborne SAR and sea ice

A number of remote sensing systems deployed in satellites to view the Earth which are successful in gathering data on the behavior of the world's snow and ice covers are described. Considering sea ice which covers over 10% of the world ocean, systems that have proven capable to collect useful data include those operating in the visible, near-infrared, infrared, and microwave frequency ranges. The microwave systems have the essential advantage in observing the ice under all weather and lighting conditions. Without this capability data are lost during the long polar night and during times of storm passage, periods when ice activity can be intense. The margins of the ice pack, a region of particular interest, is shrouded in cloud between 80 and 90% of the time.

Weeks, W. F.↗
NASA NTRS2019

Definition of a Technology Validation Mission for P-band Reflectometry using Signals of Opportunity

Root-Zone Soil Moisture (RZSM) (moisture profile in the top meter of soil) and Snow Water Equivalent (SWE) (total snow pack water content) are identified as priority target variables in the ESAS 2017 decadal survey [1] with critical roles in hydrology and water management. RZSM estimates are vital for understanding multiple Earth system processes and forecasting (for example, droughts [2]). Simultaneous knowledge of surface and RZSM could enable a breakthrough in estimating key unobserved hydrologic fluxes and reduce uncertainty in net ecosystem exchange (NEE), carbon balance [3] discharge estimates, and crop yield forecasts [4] .With the high albedo and insulating properties of snow, monitoring, SWE accumulation would provide a key constraint on the potential runoff during spring ablation while monitoring SWE disappearance rates would provide a key constraint on SWE partition into runoff vs. infiltration/recharge. [5] demonstrated that knowledge of early-spring SWE generally contributes most to streamflow forecast skill in the Western U.S. SWE is also a source of water storage that provides the water resources during spring snowmelt. Despite such potentially transformative contributions, accurate RZSM and SWE measurements are unattainable with current technology. While active/passive L-band methods (e.g. SMAP, SMOS) can reliably retrieve surface soil moisture in the top 5 cm of soil [6], [7]. RZSM estimates are only available through model assimilation of brightness temperatures with a radiative transfer and land surface models [8]. SWE estimation uses multi-frequency passive microwave techniques (e.g. [9]-[11]), which have significant problems with deeper snow and in forested and mountainous environments [12]. Signals of opportunity (SoOp) in P-band (200-400 MHz) is a new remote sensing technique with the capability of estimating both essential hydrologic variables, RZSM and SWE, circumventing many of the aforementioned limitations under all weather conditions day and night. SoOp is the re-utilization of existing powerful satellite transmissions within bands allocated for communications or navigation. P-band SoOp sensitivity to soil moisture has been demonstrated in an airborne experiment over Oklahoma in 2016 [13]. Recent theory [14] and experiments [15] have also confirmed that the reflection coefficient phase is proportional to SWE.

Garrison, J. L.↗
NASA NTRS1982

Applications of remote sensing technology to U.S. Water resource management

Applications of Landsat data to assessing the available water supply in the U.S. for agricultural puposes as a program of the NASA Office of Space Science and Applications are described. Snow melt runoff predictions are performed with multitemporal Landsat imagery to measure the extent of mountain snow packs in the Rockies in order to produce stream flow forecast models. The data is used for decisions of which crops to plant, based on irrigation water which will be accessible in eleven western U.S. states. Imagery has tracked the growth of irrigated lands watered from the Ogallala aquifer in the central U.S., and is providing a data base for calculating the aquifer depletion rates. Studies are preceeding in temporally mapping the kinds of vegetation growing in the Suwannee Sound in Florida to monitor the intrusion of salt water, which would reduce the River's usefulness for irrigation. Finally, capabilities of the Thematic Mapper are reviewed.

Weber, J. D.↗
NASA NTRS1978

A cloud physics radiometer

The paper describes the design features and capabilities of a seven-channel cloud physics radiometer (CPR) for remote sensing of cloud properties. The CPR channel characteristics and functions are tabulated and diagrammed. Each of the first three channels utilizes a photo-multipler detector, with the high-voltage power supply integrated with the tube into a single unit. In operation a heater is used to keep the optics temperature at or above 273 K and this temperature is constantly monitored. The last four channel detectors and filters are all cooled to the temperature of liquid nitrogen. The inclined scanning mirror rotates at a rate of 3.48 rps. Registration pulses are triggered and recorded as the mirror enters and leaves the + or -45 deg earth observation region. The ice-cloud, water cloud, snow discriminator detector has worked quite well in general. Interesting radiometer data have been obtained and their analysis is under way. The combination of the CPR and the Cloud Lidar System will make possible sophisticated remote sensing cloud studies.

Kyle, H. L.↗
NASA NTRS2011

Evaluating the Application of Multi-Satellite Observations in Hydrologic Modeling

When monitoring local or regional hydrosphere dynamics for applications such as agricultural productivity or drought and flooding events, it is necessary to have accurate, high-resolution estimates of terrestrial water and energy storages. Though in-situ observations provide reliable estimates of hydrologic states and fluxes, they are only capable of accurately capturing the dynamics at relatively discrete points in space and time, which makes them inadequate for characterizing the variability of the water budget across scales. In contrast, satellite-based remote sensing is ideal for providing observations of hydrological states and fluxes because it provides spatially-distributed observations at spatial and temporal scales required for regional land surface process modeling. Due to the continued progress in algorithm development and emerging satellite technology, we now have near-real time monitoring of several components of the water cycle including precipitation, soil moisture, lake and river height, terrestrial water storage, snow cover, and evapotranspiration. As these data become more readily available, their application to hydrologic modeling is becoming more common, however there remains little consensus on the most appropriate method for optimal integration and evaluation in regard to hydrological applications. Here we present two case studies operationally applying several remotely sensed products from AMSR-E, GRACE, and MODIS and discuss assimilation strategies, ease of integration and interpretation, and methods for quantifying the success of the application methodology.

Bolten, John↗
NASA NTRS1971

NOAA's hydrology studies under the Earth Resources Survey Program

Results are presented of investigations of soil moisture, snow cover, and lake temperatures carried out with the support of the Earth Resources Survey Program. Objectives of these studies were: (1) Obtain more data with a multifrequency microwave system so that the range of soil moisture amounts and types can be extended. (2) Establish instrument and data specifications for microwave sensing of soil moisture from satellites and aircraft. (3) Refine the procedures for mapping snow cover that have been developed using satellite and aircraft remote sensor data in the visible spectrum. (4) Evaluation of satellite and aircraft infrared observations for determining their information content with respect to snow cover, ice cover, and water temperature over large lakes.

Mcclain, E. P.↗