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NASA NTRS2023

Global and Zonal-Mean Hydrological Response to Early Eocene Warmth

Earth's hydrological cycle is expected to intensify in response to global warming, with a “wet-gets-wetter, dry-gets-drier” response anticipated over the ocean. Subtropical regions (∼15°–30°N/S) are predicted to become drier, yet proxy evidence from past warm climates suggests these regions may be characterized by wetter conditions. Here we use an integrated data-modeling approach to reconstruct global and zonal-mean rainfall patterns during the early Eocene (∼56–48 million years ago). The Deep-Time Model Intercomparison Project (DeepMIP) model ensemble indicates that the mid- (30°–60°N/S) and high-latitudes (>60°N/S) are characterized by a thermodynamically dominated hydrological response to warming and overall wetter conditions. The tropical band (0°–15°N/S) is also characterized by wetter conditions, with several DeepMIP models simulating narrowing of the Inter-Tropical Convergence Zone. However, the latter is not evident from the proxy data. The subtropics are characterized by negative precipitation-evaporation anomalies (i.e., drier conditions) in the DeepMIP models, but there is surprisingly large inter-model variability in mean annual precipitation (MAP). Intriguingly, we find that models with weaker meridional temperature gradients (e.g., CESM, GFDL) are characterized by a reduction in subtropical moisture divergence, leading to an increase in MAP. These model simulations agree more closely with our new proxy-derived precipitation reconstructions and other key climate metrics and imply that the early Eocene was characterized by reduced subtropical moisture divergence. If the meridional temperature gradient was even weaker than suggested by those DeepMIP models, circulation-induced changes may have outcompeted thermodynamic changes, leading to wetter subtropics. This highlights the importance of accurately reconstructing zonal temperature gradients when reconstructing past rainfall patterns.

Margot J. Cramwinckel↗
NASA NTRS1988

Tropical Rainfall Measurement Mission

It has long been noted that anomalies in the sea surface temperature (SST) in the tropics are strongly correlated with climate in the temperate latitudes on a seasonal time scale. The ability to measure the global SST and the atmospheric pressure/temperature patterns has made great progress. However, rainfall measurement, the putative connection between the two, is poorly accomplished. The Tropical Rainfall Measurement Mission (TRMM) was conceived to fill this gap. The TRMM spacecraft would fly in a low inclination, (about 35 deg), orbit which would concentrate the sampling in the very important tropical latitudes. The precession of such an orbit would enable observations at all times of the day over the span of a month which would permit corrections for the diurnal cycle of precipitation which is quite marked in parts of the tropics. The payload of the TRMM spacecraft is carefully designed to provide accurate measurements of rain. It consists of microwave radiometers, a microwave radar and visible/infrared radiometer. The two types of microwave instruments provide direct measurements of the hydrometeors, each having strengths which compensate for weaknesses of the other. The VIS/IR instrument provides a connection to the long time series of VIS/IR measurements from polar and Geosynchronous spacecraft which are currently the best available source of global rainfall estimates. The TRMM is currently in a phase A (feasibility) study.

Wilheit, T. T.↗
NASA NTRS1999

Regional Climate Simulation with a Variable Resolution Stretched Grid GCM: The Regional Down-Scaling Effects

The results obtained with the variable resolution stretched grid (SG) GEOS GCM (Goddard Earth Observing System General Circulation Models) are discussed, with the emphasis on the regional down-scaling effects and their dependence on the stretched grid design and parameters. A variable resolution SG-GCM and SG-DAS using a global stretched grid with fine resolution over an area of interest, is a viable new approach to REGIONAL and subregional CLIMATE studies and applications. The stretched grid approach is an ideal tool for representing regional to global scale interactions. It is an alternative to the widely used nested grid approach introduced a decade ago as a pioneering step in regional climate modeling. The GEOS SG-GCM is used for simulations of the anomalous U.S. climate events of 1988 drought and 1993 flood, with enhanced regional resolution. The height low level jet, precipitation and other diagnostic patterns are successfully simulated and show the efficient down-scaling over the area of interest the U.S. An imitation of the nested grid approach is performed using the developed SG-DAS (Data Assimilation System) that incorporates the SG-GCM. The SG-DAS is run with withholding data over the area of interest. The design immitates the nested grid framework with boundary conditions provided from analyses. No boundary condition buffer is needed for the case due to the global domain of integration used for the SG-GCM and SG-DAS. The experiments based on the newly developed versions of the GEOS SG-GCM and SG-DAS, with finer 0.5 degree (and higher) regional resolution, are briefly discussed. The major aspects of parallelization of the SG-GCM code are outlined. The KEY OBJECTIVES of the study are: 1) obtaining an efficient DOWN-SCALING over the area of interest with fine and very fine resolution; 2) providing CONSISTENT interactions between regional and global scales including the consistent representation of regional ENERGY and WATER BALANCES; 3) providing a high computational efficiency for future SG-GCM and SG-DAS versions using PARALLEL codes.

Fox-Rabinovitz, Michael S.↗
NASA NTRS2000

Reflected GPS Power for the Detection of Surface Roughness Patterns in Coastal Water

Coastal bays formed by the barrier islands of Delaware, Maryland and Virginia are parts of a coastal region known as a "Coastal Compartment". The coastal compartment between the Chesapeake and Delaware Bays is actually the mosaic of landscapes on the headland of the interfluve that separates these large drainage basins. The coastal compartments form a variety of different-shaped waterways landward of the coastline. Shape differences along the boundaries produce differences in exposure to wind and waves. Different shoreface topographies seaward of the coastline also influence surface roughness by changing wave-refraction patterns. Surface-water roughness (caused by waves) is controlled by a number of parameters, including fetch, shielding, exposure corridors, water-mass boundary conditions, wetland vegetation and water depth in coastal bays. In the coastal ocean, surface roughness patterns are controlled by shoreface shoaling and inlet refraction patterns in the coastal ocean. Knowledge of wave phenomena in the nearshore and backbarrier areas is needed to understand how wave climate influences important ecosystems in estuaries and bays.

Oertel, George, F.↗
NASA NTRS2001

Space-Time Characteristics of Rainfall Diurnal Variations

The space-time features of rainfall diurnal variation of precipitation are systematically investigated by using the Tropical Rainfall Measuring Mission (TRMM) precipitation products retrieved from TRMM microwave imager (TMI), precipitation radar (PR) and TMI/PR combined algorithms. Results demonstrate that diurnal variability of precipitation is obvious over tropical regions. The dominant feature of rainfall diurnal cycle over, ocean is that there is consistent rainfall peak in early morning, while there is a consistent rainfall peak in mid-late afternoon over land. The seasonal variation on intensity of rainfall diurnal cycle is clearly evidenced. Horizontal distributions of rainfall diurnal variations indicate that there is a clearly early-morning peak with a secondary peak in the middle-late afternoon in ocean rainfall at latitudes dominated by large-scale convergence and deep convection. There is also an analogous early-morning peak in land rainfall along with a stronger afternoon peak forced by surface heating. Amplitude analysis shows that the patterns and its evolution of rainfall diurnal cycle are very close to rainfall distribution pattern and its evolution. These results indicate that rainfall diurnal variations are strongly associated with large-scale convective systems and climate weather systems. Phase studies clearly present the regional and seasonal features of rainfall diurnal activities. Further studies on convective and stratiform rainfall show different characteristics of diurnal cycles. Their spatial and temporal variations of convective and stratiform rainfall indicate that mechanisms for rainfall diurnal variations vary with time and space.

Yang, Song↗
NASA NTRS2002

New Insights on Hydro-Climate Feedback Processes over the Tropical Ocean from TRMM

In this paper, we study hydro-climate feedback processes over the tropical oceans, by examining the relationships among large scale circulation and Tropical Rainfall Measuring Mission Microwave Imager-Sea Surface Temperature (TMI-SST), and a range of TRMM rain products including rain rate, cloud liquid water, precipitable water, cloud types and areal coverage, and precipitation efficiency. Results show that for a warm event (1998), the 28C threshold of convective precipitation is quite well defined over the tropical oceans. However, for a cold event (1999), the SST threshold is less well defined, especially over the central and eastern Pacific cold tongue, where stratiform rain occurs at much lower than 28 C. Precipitation rates and cloud liquid water are found to be more closely related to the large scale vertical motion than to the underlying SST. While total columnar water vapor is more strongly dependent on SST. For a large domain, over the eastern Pacific, we find that the areal extent of the cloudy region tends to shrink as the SST increases. Examination of the relationship between cloud liquid water and rain rate suggests that the residence time of cloud liquid water tends to be shorter, associated with higher precipitation efficiency in a warmer climate. It is hypothesized that the reduction in cloudy area may be influenced both by the shift in large scale cloud patterns in response to changes in large scale forcings, and possible increase in the cloud liquid water conversion to rain water in a warmer environment. Results of numerical experiments with the Goddard cloud resolving model to test the hypothesis will be discussed.

Lau, William K. M.↗
NASA NTRS2004

Estimation of Fire Emissions from Satellite-Based Measurements

Biomass burning is a worldwide phenomenon affecting many vegetated parts of the globe regularly. Fires emit large quantities of aerosol and trace gases into the atmosphere, thus influencing the atmospheric chemistry and climate. Traditional methods of fire emissions estimation achieved only limited success, because they were based on peripheral information such as rainfall patterns, vegetation types and changes, agricultural practices, and surface ozone concentrations. During the last several years, rapid developments in satellite remote sensing has allowed more direct estimation of smoke emissions using remotely-sensed fire data. However, current methods use fire pixel counts or burned areas, thereby depending on the accuracy of independent estimations of the biomass fuel loadings, combustion efficiency, and emission factors. With the enhanced radiometric range of its 4-micron fire channel, the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, which flies aboard both of the Earth Observing System EOS) Terra and Aqua Satellites, is able to measure the rate of release of fire radiative energy (FRE) in MJ/s (something that older sensors could not do). MODIS also measures aerosol distribution. Taking advantage of these new resources, we have developed a procedure combining MODIS fire and aerosol products to derive FRE-based smoke emission coefficients (C(e), in kg/MJ) for different regions of the globe. These coefficients are simply used to multiply FRE from MODIS to derive the emitted smoke aerosol mass. Results from this novel methodology are very encouraging. For instance, it was found that the smoke total particulate mass emission coefficient for the Brazilian Cerrado ecosystem (approximately 0.022 kg/MJ) is about twice the value for North America, Western Europe, or Australia, but about 50% lower than the value for southern Africa.

Ichoku, Charles↗
NASA NTRS2013

Siberian Pine Decline and Mortality in Southern Siberian Mountains

The causes and resulting spatial patterns of Siberian pine mortality in eastern Kuznetzky Alatau Mountains, Siberia were analyzed based on satellite (Landsat, MODIS) and dendrochronology data. Climate variables studied included temperature, precipitation and Standardized Precipitation-Evapotranspiration Index (SPEI) drought index. Landsat data analysis showed that stand mortality was first detected in the year 2006 at an elevation of 650 m, and extended up to 900 m by the year 2012. Mortality was accompanied by a decrease in MODIS derived vegetation index (EVI).. The area of dead stands and the upper mortality line were correlated with increased drought. The uphill margin of mortality was limited by elevational precipitation gradients. Dead stands (i.e., >75% tree mortality) were located mainly on southern slopes. With respect to slope, mortality was observed within a 7 deg - 20 deg range with greatest mortality occurring on convex terrain. Tree radial incrementmeasurements correlate and were synchronous with SPEI (r sq = 0.37, r(sub s) = 80). Increasing synchrony between tree ring growth and SPEI indicates that drought has reduced the ecological niche of Siberian pine. The results also showed the primary role of drought stress on Siberian pine mortality. A secondary role may be played by bark beetles and root fungi attacks. The observed Siberian pine mortality is part of a broader phenomenon of "dark needle conifers" (DNC, i.e., Siberian pine, fir and spruce) decline and mortality in European Russia, Siberia, and the Russian Far East. All locations of DNC decline coincided with areas of observed drought increase. The results obtained are one of the first observations of drought-induced decline and mortality of DNC at the southern border of boreal forests. Meanwhile if model projections of increased aridity are correct DNC, within the southern part of its range may be replaced by drought-resistant Pinus silvestris and Larix sibirica.

tree die-off↗
NASA NTRS2000

A Variable Resolution Stretched Grid General Circulation Model: Regional Climate Simulation

The development of and results obtained with a variable resolution stretched-grid GCM for the regional climate simulation mode, are presented. A global variable resolution stretched- grid used in the study has enhanced horizontal resolution over the U.S. as the area of interest The stretched-grid approach is an ideal tool for representing regional to global scale interaction& It is an alternative to the widely used nested grid approach introduced over a decade ago as a pioneering step in regional climate modeling. The major results of the study are presented for the successful stretched-grid GCM simulation of the anomalous climate event of the 1988 U.S. summer drought- The straightforward (with no updates) two month simulation is performed with 60 km regional resolution- The major drought fields, patterns and characteristics such as the time averaged 500 hPa heights precipitation and the low level jet over the drought area. appear to be close to the verifying analyses for the stretched-grid simulation- In other words, the stretched-grid GCM provides an efficient down-scaling over the area of interest with enhanced horizontal resolution. It is also shown that the GCM skill is sustained throughout the simulation extended to one year. The developed and tested in a simulation mode stretched-grid GCM is a viable tool for regional and subregional climate studies and applications.

Fox-Rabinovitz, Michael S.↗
NASA NTRS1993

Transmantle flux tectonics

Venus, Earth, and Mars have surfaces that display topographic domes and depressions with quasi-circular planimetric shapes, relief of 0 to several km, and large spatial scales (10(exp 2) to 10(exp 4) km). Our morphostructural mapping reveals hierarchical arrangements of these features. They are explained by a model of long-acting mantle convection, as a particular case of convection in a stratified and random inhomogeneous medium, which develops the form of a hierarchy of different convective pattern scales, each arising from different levels in the mantle. The hypothesis of transmantle flux tectonics parsimoniously explains a diversity of seemingly unrelated terrestrial planetary phenomena, including Earth megaplumes, global resurfacing epochs on Venus, and cyclic ocean formation and global climate change for Mars. All these phenomenon are hypothesized to be parsimoniously explained by a process of transmantle flux tectonics in which long-acting mantle convection generates stresses in blocks of planetary lithosphere to produce distinctive quasi-circular global-hierarchical morphostructure (QGM) patterns. Transmantle flux tectonics differs from plume tectonics in that individual plumes are not considered in isolation. Rather, a wholly interactive process is envisioned in which various spatial and temporal scales of convection operate contemporaneously and hierarchically within other scales. This process of continual change by hierarchical convective cells affects the surface at varying temporal and spatial scales, and its effects are discernable through their relic geological manifestations, the QGM patterns.

Finn, V. J.↗
NASA NTRS2021

Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6

The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 °C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 °C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 °C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 °C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.d-2090s.

Scenario Model Intercomparison Project (ScenarioMI↗
NASA NTRS2018

Winter Precipitation in North America and the Pacific-North America Pattern in GEOS-S2Sv2 Seasonal Hindcast

Reliable prediction of precipitation remains one of the most pivotal and complex challenges in seasonal forecasting. Previous studies show that various large-scale climate modes, such as ENSO, PNA and NAO play significant role in winter precipitation variability over the Northern America. The influences are most pronounced in years of strong indices of such climate modes. This study evaluates model bias, predictability and forecast skills of monthly winter precipitation in GEOS5-S2S 2.0 retrospective forecast from 1981 to 2016, with emphasis on the forecast skill of precipitation over North America during the extreme events of ENSO, PNA and NAO by applying EOF and composite analysis.

Li, Zhao↗
NASA NTRS2012

Human Settlements in the South-Central U.S., Viewed at Night from the International Space Station

A recent innovation of astronauts observing Earth from the International Space Station (ISS) is documenting human footprints by photographing city lights at night time. One of the earliest night-time images from the ISS was the US-Mexico border at El Paso-Ciudad Juarez. The colors, patterns and density of city lights document the differences in the cultural settlement patterns across the border region, as well as within the urban areas themselves. City lights help outline the most populated areas in settlements around the world, and can be used to explore relative population densities, changing patterns of urban/suburban development, transportation networks, spatial relationship to geographic features, and more. The data also provides insight into parameters such as surface roughness for input into local and regional climate modeling and studies of light pollution. The ground resolution of night-time astronaut photography from the ISS is typically an order of magnitude greater than current Defense Meteorological Satellite Program (DMSP) data, and therefore can serve as a "zoom lens" for selected urban areas. Current handheld digital cameras in use on the ISS, optimized for greater light sensitivity, provide opportunities to obtain new detailed imagery of atmospheric phenomena such as airglow, aurora, and noctilucent clouds in addition to documenting urban patterns. ISS astronauts have taken advantage of increasingly sensitive digital cameras to document the world at night in unprecedented detail. In addition, the capability to obtain time-lapse imagery from fixed cameras has been exploited to produce dynamic videos of both changing surface patterns around the world and atmospheric phenomena. We will profile some spectacular images of human settlements over the South-Central U.S., and contrast with other images from around the world. More data can be viewed at http://eol.jsc.nasa.gov/Videos/CrewEarthObservationsVideos/. US-Mexico border is obvious by the different lighting pattern. Not surprisingly, the densely illuminated city of Juarez indicates a higher population; El Paso's smaller population is spread out over a larger area.

Dawson, Melissa↗
NASA NTRS2011

Accessing Recent Trend of Land Surface Temperature from Satellite Observations

Land surface temperature (Ts) is an important element to measure the state of terrestrial ecosystems and to study surface energy budgets. In support of the land cover/land use change-related international program MAIRS (Monsoon Asia Integrated Regional Study), we have collected global monthly Ts measured by MODIS since the beginning of the missions. The MODIS Ts time series have approximately 11 years of data from Terra since 2000 and approximately 9 years of data from Aqua since 2002, which makes possible to study the recent climate, such as trend. In this study, monthly climatology from two platforms are calculated and compared with that from AIRS. The spatial patterns of Ts trends are accessed, focusing on the Eurasia region. Furthermore, MODIS Ts trends are compared with those from AIRS and NASA's atmospheric assimilation model, MERRA (Modern Era Retrospective-analysis for Research and Applications). The preliminary results indicate that the recent 8-year Ts trend shows an oscillation-type spatial variation over Eurasia. The pattern is consistent for data from MODIS, AIRS, and MERRA, with the positive center over Eastern Europe, and the negative center over Central Siberia. The calculated climatology and anomaly of MODIS Ts will be integrated into the online visualization system, Giovanni, at NASA GES DISC for easy use by scientists and general public.

Shen, Suhung↗
NASA NTRS2013

From BASE-ASIA Toward 7-SEAS: A Satellite-Surface Perspective of Boreal Spring Biomass-Burning Aerosols and Clouds in Southeast Asia

In this paper, we present recent field studies conducted by NASA's SMART-COMMIT (and ACHIEVE, to be operated in 2013) mobile laboratories, jointly with distributed ground-based networks (e.g., AERONET, http://aeronet.gsfc.nasa.gov/ and MPLNET, http://mplnet.gsfc.nasa.gov/) and other contributing instruments over northern Southeast Asia. These three mobile laboratories, collectively called SMARTLabs (cf. http://smartlabs.gsfc.nasa.gov/, Surface-based Mobile Atmospheric Research & Testbed Laboratories) comprise a suite of surface remote sensing and in-situ instruments that are pivotal in providing high spectral and temporal measurements, complementing the collocated spatial observations from various Earth Observing System (EOS) satellites. A satellite-surface perspective and scientific findings, drawn from the BASE-ASIA (2006) field deployment as well as a series of ongoing 7-SEAS (2010-13) field activities over northern Southeast Asia are summarized, concerning (i) regional properties of aerosols from satellite and in situ measurements, (ii) cloud properties from remote sensing and surface observations, (iii) vertical distribution of aerosols and clouds, and (iv) regional aerosol radiative effects and impact assessment. The aerosol burden over Southeast Asia in boreal spring, attributed to biomass burning, exhibits highly consistent spatial and temporal distribution patterns, with major variability arising from changes in the magnitude of the aerosol loading mediated by processes ranging from large-scale climate factors to diurnal meteorological events. Downwind from the source regions, the tightly coupled-aerosolecloud system provides a unique, natural laboratory for further exploring the micro- and macro-scale relationships of the complex interactions. The climatic significance is presented through large-scale anti-correlations between aerosol and precipitation anomalies, showing spatial and seasonal variability, but their precise cause-and-effect relationships remain an open-ended question. To facilitate an improved understanding of the regional aerosol radiative effects, which continue to be one of the largest uncertainties in climate forcing, a joint international effort is required and anticipated to commence in springtime 2013 in northern Southeast Asia.

biomass burning aerosols↗
NASA NTRSDate not supplied

Development of Carbon Flux Model Using ABI Data Over the Conterminous US

The satellite-driven carbon flux estimation has been playing important role to estimate continental-scale carbon budget. One of the biggest recent advances in the satellite-driven carbon flux modeling is utilization of high-frequent geostationary satellites to estimate diurnal cycle in carbon fluxes. The satellite based carbon flux estimation used the polar orbiting satellite sensors (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)), which allow us to observe target regions only once during the day. The new generation of geostationary satellite sensors provide frequent observations, often less than every 10 minutes. Here, we use GOES Advanced Baseline Imager (ABI) data to estimate hourly NEE over the conterminous US. We used the Terrestrial Observation Prediction System (TOPS) model for estimating hourly NEE. TOPS is a diagnostic ecosystem process model that simulates the fluxes of carbon and water through vegetation in response to climate variability. For the climate input, we developed hourly climate data using the same algorithm with NASA Earth Exchange Gridded Daily Meteorology (NEX-GDM) datasets based on machine learning techniques. The hourly climate data includes precipitation, maximum temperature, minimum temperature, dew point temperature, and solar radiation were derived from the Geostationary observations. The spatial patterns of ecosystem parameters used in TOPS are optimized using satellite Solar Induced Fluorescence (SIF) data. The high frequency GPP estimations from geostationary satellite sensors make it comparable to the instantaneous SIF data than daily GPP. We also used Ameriflux data for optimization of model parameters and the validation of the output. The derived data addresses the diurnal dynamics of carbon cycling at large scales and should help in reducing the uncertainties in carbon budget studies.

geostationary satellite↗
NASA NTRS2020

How Satellite Soil Moisture Data Can Help to Monitor the Impacts of Climate Change: SMAP Case Studies

Socially and economically costly extreme weather events have become more prevalent in the last decade. Monitoring and early warning systems could help mitigate the impact of such events by allowing people to better prepare themselves to manage their responses to these events. One significant element of an effective warning system is soil moisture because it is a key determinant of the exchange of water and heat energy between the land and atmosphere, the partitioning of precipitation between infiltration and runoff, and therefore has an influence on weather patterns and streamflow. In addition, soil moisture governs plant water availability – the key to crop yield forecasting. For these reasons, a wide range of organizations use soil moisture information to better predict and monitor climate and weather phenomena such as floods and droughts. By improving soil moisture estimates, it may be possible to improve the monitoring and early warning systems upon which these organizations rely, and hence better mitigate the impacts of extreme weather events. Through case studies, this article discusses several uses of soil moisture data products from NASA’s Soil Moisture Active Passive (SMAP) mission to help improve soil moisture-related monitoring and early warning systems.

Drought monitoring↗
NASA NTRS2020

How Satellite Soil Moisture Data Can Help to Monitor the Impacts of Climate Change: SMAP Case Studies

Socially and economically costly extreme weather events have become more prevalent in the last decade. Monitoring and early warning systems could help mitigate the impact of such events by allowing people to better prepare themselves to manage their responses to these events. One significant element of an effective warning system is soil moisture because it is a key determinant of the exchange of water and heat energy between the land and atmosphere, the partitioning of precipitation between infiltration and runoff, and therefore has an influence on weather patterns and streamflow. In addition, soil moisture governs plant water availability - the key to crop yield forecasting. For these reasons, a wide range of organizations use soil moisture information to better predict and monitor climate and weather phenomena such as floods and droughts. By improving soil moisture estimates, it may be possible to improve the monitoring and early warning systems upon which these organizations rely, and hence better mitigate the impacts of extreme weather events. Through case studies, this article discusses several uses of soil moisture data products from NASA's Soil Moisture Active Passive (SMAP) mission to help improve soil moisture-related monitoring and early warning systems.

agriculture↗