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NASA NTRS2017

TPSAS-NF1676L-21094-DND

Advanced knowledge in atmospheric CO 2 distributions is critical in predicting the Earth's future climate. Large uncertainties in the prediction persist due to limited observations. This study focuses on the development and demonstration of the Intensity-Modulated Continuous-Wave (IM-CW) lidar for atmospheric CO 2 measurements. Simulations show that IM-CW lidar systems operating at 1.57 um will provide precise atmospheric column CO 2 measurements from space. Airborne systems have demonstrated the feasibility of the technology and instrumentation for space active atmospheric CO 2 missions. In this presentation, the atmospheric CO 2 column measurements from airborne flight campaigns and lidar system simulations for space missions will be discussed. Data analysis shows that airborne lidar CO 2 column measurements over desert and vegetated surfaces agree well with in-situ measurements. A measurement precision of 0.08% or ~0.3 ppmv for a 10-s average over these surfaces has also been achieved. Generally, airborne flight campaigns have demonstrated that the column CO 2 measurements of the current IM-CW lidar systems meet the accuracy and precision requirements of atmospheric CO 2 measurements. Furthermore, analyses of space CO 2 measurements shows that the current IM-CW lidar technology and approach will enable space missions to achieve their science goals.

Bing Lin↗

NASA NTRSDate not supplied

TPSAS-NF1676L-10735-DND

The Clouds and the Earth's Radiant Energy System (CERES) project has now surpassed the 10-year mark, has combined rigorous calibration, improved scene identification, and multi-satellite data fusion to produce a climate-accuracy data set of global 1° gridded radiative surface and TOA fluxes, and cloud properties. CERES provides the climate community with four observed TOA flux products. The ERBE-like product uses the same algorithms as ERBE in order to be compared with the ERBE time period. The SSF product uses the improved scene identification and radiance to flux conversion. The SYN product uses GEO derived clouds and fluxes to provide diurnally complete TOA fluxes. The EBAF product provides net balanced fluxes tied to the ocean heat storage term. This product is suited for climate modelers estimating the global mean energy budget. Each successive CERES flux product applies the improvements over the previous product. This presentation will focus on the diurnal averaging improvements by the inclusion of imager radiances from 5 geostationary (GEO) satellites at 3-hourly intervals to estimate the flux in between CERES observations. The regional monthly mean flux differences based on SYN (CERES/GEO) and SSF (CERES-only) can exceed 20 Wm^-2. CERES shortwave and longwave fluxes have been rigorously validated and are key elements in evaluating the ability of climate models to predict both past and future climate states. The CERES normalization of GEO derived fluxes in order to maintain the CERES instrument calibration and are consistent globally within 0.1 Wm^-2, even if the GEO calibration is artificially altered by ±5%, twice the anticipated calibration error. The predicted GEO TOA fluxes normalized to Terra have been compared at Aqua times to Aqua flux observations, as well as with GERB hourly fluxes over the METEOSAT domain. Similarly ground based radiometers have been used to validate the CERES radiative transfer computed surface fluxes and have confirmed that the CERES/GEO fluxes have improved the computed surface flux product. Although the GEO based fluxes are of inferior quality then the CERES observed fluxes, they capture the diurnal signal more effectively than using constant meteorology between CERES measurements. The validation of the GEO derived fluxes and clouds will be shown.

D. R. Doelling↗

NASA NTRS2015

Monitoring Atmospheric CO2 From Space: Challenge & Approach

Atmospheric CO2 is the key radiative forcing for the Earth's climate and may contribute a major part of the Earth's warming during the past 150 years. Advanced knowledge on the CO2 distributions and changes can lead considerable model improvements in predictions of the Earth's future climate. Large uncertainties in the predictions have been found for decades owing to limited CO2 observations. To obtain precise measurements of atmospheric CO2, certain challenges have to be overcome. For an example, global annual means of the CO2 are rather stable, but, have a very small increasing trend that is significant for multi-decadal long-term climate. At short time scales (a second to a few hours), regional and subcontinental gradients in the CO2 concentration are very small and only in an order of a few parts per million (ppm) compared to the mean atmospheric CO2 concentration of about 400 ppm, which requires atmospheric CO2 space monitoring systems with extremely high accuracy and precision (about 0.5 ppm or 0.125%) in spatiotemporal scales around 75 km and 10-s. It also requires a decadal-scale system stability. Furthermore, rapid changes in high latitude environments such as melting ice, snow and frozen soil, persistent thin cirrus clouds in Amazon and other tropical areas, and harsh weather conditions over Southern Ocean all increase difficulties in satellite atmospheric CO2 observations. Space lidar approaches using Integrated Path Differential Absorption (IPDA) technique are considered to be capable of obtaining precise CO2 measurements and, thus, have been proposed by various studies including the 2007 Decadal Survey (DS) of the U.S. National Research Council. This study considers to use the Intensity-Modulated Continuous-Wave (IM-CW) lidar to monitor global atmospheric CO2 distribution and variability from space. Development and demonstration of space lidar for atmospheric CO2 measurements have been made through joint adventure of NASA Langley Research Center and Exelis, Inc. As prototype space IPDA lidars, airborne laser absorption lidar systems operating in 1.57 CO2 absorption band have been developed and tested through lab, ground-based range, and flight campaigns. Very encouraging results have been obtained. The signal-to-noise ratio (SNR) for clear sky IPDA measurements of CO2 differential absorption optical depth (DAOD) for a 10-s integration over vegetated areas with about 10 km range was found to be as high as 1300, resulting in an error 0.077% or equivalent CO2 mixing ratio (XCO2) column precision of ~0.3 ppm. Precise range measurements using the IM-CW lidar approach were also achieved, and the uncertainties have been shown to be at sub meter level. Based on the airborne lidar development, space lidar and atmospheric CO2 observations are simulated. It shows that with the IM-CW approach, accurate atmospheric CO2 measurements can be achieved from space, and a space mission such as that proposed by the DS will meet science goals of atmospheric CO2 monitoring.

Lin, Bing↗

NASA NTRS2014

Interannual Variations and Trends in Global Land Surface Phenology Derived from Enhanced Vegetation Index During 1982-2010

Land swiace phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstmted to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This srudy detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examIned across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and OSL varied considerably during 1982-2010 across the globe. Generally, the interarmual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative OSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3 decades. OGI mainly showed late trends in the Southern Hemisphere of Africa while GSL was reversed from reduced GSL trends (1982-1999) to prolonged trends (2000-2010). In Australia, GSL exhibited considerable interannual variation, but the consistent trend lacked presence in most regions. Finally, the proportion of pixels with significant trends was less than I% in most of climate regions although it could be as large as 10%.

remote sensing↗

NASA NTRS2017

The Future of Planetary Climate Modeling and Weather Prediction

Modeling of planetary climate and weather has followed the development of tools for studying Earth, with lags of a few years. Early Earth climate studies were performed with 1-dimensionalradiative-convective models, which were soon fol-lowed by similar models for the climates of Mars and Venus and eventually by similar models for exoplan-ets. 3-dimensional general circulation models (GCMs) became common in Earth science soon after and within several years were applied to the meteorology of Mars, but it was several decades before a GCM was used to simulate extrasolar planets. Recent trends in Earth weather and and climate modeling serve as a useful guide to how modeling of Solar System and exoplanet weather and climate will evolve in the coming decade.

Del Genio, A. D.↗

NASA NTRSDate not supplied

TPSAS-NF1676L-10737-DND

The Clouds and the Earth's Radiant Energy System (CERES) project provides the community a quality climate TOA and surface fluxes and cloud properties and are key elements in evaluating the ability of climate models to predict both past and future climate states. One important aspect of successful climate monitoring is satellite calibration. The CERES instantaneous broadband calibration radiance stability is 0.1% per year, whereas the accuracy of the longwave (LW) and shortwave (SW) is better than 0.5% and 1% respectively. CERES uses the 3-hourly GEO fluxes and clouds to provide diurnally averaged daily and monthly TOA flux means from the CERES measurements onboard the Terra (10:30 AM local equator crossing time) and Aqua (13:30 PM) sun-synchronous satellites. The GEO radiances are calibrated against MODIS as a reference to provide consistent GEO retrieved cloud properties and derived broadband fluxes. These fluxes are then carefully normalized against the well-calibrated CERES fluxes to ensure climate quality fluxes, free of GEO artifacts. With the upcoming release of Edition3 products, CERES has just recalibrated all the CERES instruments to ensure that both Terra and Aqua fluxes are on the same radiometric scale and the removal of all known instrument trends. CERES will also recalibrate all GEO satellites using the entire GEO time record. CERES employs collocated, coincident ray-matched GEO/MODIS radiances as its primary technique, calibrating GEO radiances beginning in the year 2000. The advantage of the ray-matching technique is that it provides a full dynamic range of radiances to check the linearity of the GEO visible instrument. CERES uses deep convective clouds and invariant desert sites to validate the primary technique. All three methods can assess the stability of the GEO visible instrument. Examples of the CERES GEO calibration techniques and validation efforts will be shown at the conference. Special emphasis will be given to the newly incorporated desert site methodology.

R. Bhatt↗

NASA NTRS2014

Uncertainties in Predicting Rice Yield by Current Crop Models Under a Wide Range of Climatic Conditions

Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10 percent of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2] and temperature.

crop-model ensembles↗

NASA NTRS1995

Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment

Practitioners of climate change prediction base many of their future climate scenarios on General Circulation Models (GCM's), each model with differing assumptions and parameter requirements. For representing the atmosphere, GCM's typically contain equations for calculating motion of particles, thermodynamics and radiation, and continuity of water vapor. Hydrology and heat balance are usually included for continents, and sea ice and heat balance are included for oceans. The current issue of this journal contains a paper by Van Blarcum et al. (1995) that predicts runoff from nine high-latitude rivers under a doubled CO2 atmosphere. The paper is important since river flow is an indicator variable for climate change. The authors show that precipitation will increase under the imposed perturbations and that owing to higher temperatures earlier in the year that cause the snow pack to melt sooner, runoff will also increase. They base their simulations on output from a GCM coupled with an interesting water routing scheme they have devised. Climate change models have been linked to other models to predict deforestation.

Skiles, J. W.↗

NASA NTRS1990

The ice-core record - Climate sensitivity and future greenhouse warming

The prediction of future greenhouse-gas-warming depends critically on the sensitivity of earth's climate to increasing atmospheric concentrations of these gases. Data from cores drilled in polar ice sheets show a remarkable correlation between past glacial-interglacial temperature changes and the inferred atmospheric concentration of gases such as carbon dioxide and methane. These and other palaeoclimate data are used to assess the role of greenhouse gases in explaining past global climate change, and the validity of models predicting the effect of increasing concentrations of such gases in the atmosphere.

Lorius, C.↗

NASA NTRS2016

How Did Climate and Humans Respond to Past Volcanic Eruptions?

To predict and prepare for future climate change, scientists are striving to understand how global-scale climatic change manifests itself on regional scales and also how societies adapt or don't to sometimes subtle and complex climatic changes. In this regard, the strongest volcanic eruptions of the past are powerful test cases, showcasing how the broad climate system responds to sudden changes in radiative forcing and how societies have responded to the resulting climatic shocks. These issues were at the heart of the inaugural workshop of the Volcanic Impacts on Climate and Society (VICS) Working Group, convened in June 2016 at the Lamont-Doherty Earth Observatory of Columbia University in Palisades, N.Y. The 3-day meeting gathered approximately 50 researchers, who presented work intertwining the history of volcanic eruptions and the physical processes that connect eruptions with human and natural systems on a global scale.

societies↗

NASA NTRS2006

Contributions of Satellite Observations to Understanding Climate Change

One of the challenges facing atmospheric scientists is to interpret trends in multi-decadal data records. Although data records from satellite instruments are not as long as some ground-based records, global coverage and resolved vertical profiles provide unique information for identifying signatures of climate change. For example, the Halogen Occultation Experiment (HALOE) on the Upper Atmosphere Research Satellite provided profiles of O3, H2O, HC1, HF, CH4 from October 1991 until November 2005. There are also multi-annual ground based measurements of the column HCl. Middle latitude ground-based measurements show a seasonal cycle, and the HALOE profiles show that this is driven by the seasonal change in the composition and mass of the region between the tropopause and 380K surface (the lowermost stratosphere). Understanding the processes that produce the seasonal cycle makes it possible to interpret a future change in the seasonal cycle as a marker of a change in the stratospheric residual circulation. Satellite observations have also provided key information for improving the physical basis of models used to predict future composition and climate circulation. An example is the "tape recorder" signature in tropical stratospheric water vapor, i.e., the slow ascent of high and low water vapor anomalies roughly corresponding to the tropopause temperature at the time air entered the stratosphere. This signature has become a key diagnostic of performance for climate models.

Douglass, Anne R.↗

NASA NTRS2004

Polar Processes in a 50-year Simulation of Stratospheric Chemistry and Transport

The unique chemical, dynamical, and microphysical processes that occur in the winter polar lower stratosphere are expected to interact strongly with changing climate and trace gas abundances. Significant changes in ozone have been observed and prediction of future ozone and climate interactions depends on modeling these processes successfully. We have conducted an off-line model simulation of the stratosphere for trace gas conditions representative of 1975-2025 using meteorology from the NASA finite-volume general circulation model. The objective of this simulation is to examine the sensitivity of stratospheric ozone and chemical change to varying meteorology and trace gas inputs. This presentation will examine the dependence of ozone and related processes in polar regions on the climatological and trace gas changes in the model. The model past performance is base-lined against available observations, and a future ozone recovery scenario is forecast. Overall the model ozone simulation is quite realistic, but initial analysis of the detailed evolution of some observable processes suggests systematic shortcomings in our description of the polar chemical rates and/or mechanisms. Model sensitivities, strengths, and weaknesses will be discussed with implications for uncertainty and confidence in coupled climate chemistry predictions.

Kawa, S.R.↗

NASA NTRS2009

Synthesis and Assimilation Systems - Essential Adjuncts to the Observing System

Assimilation systems synthesize diverse in-situ and satellite data streams into full four-dimensional state estimates by combining the strengths of each data set and also of the model. The resulting analysis provides an integrated view of the information in the various observations as well as derived estimates of unobserved quantities. Assimilation systems are particularly important for the ocean where subsurface observations, even today, are sparse and intermittent compared with the scales needed to represent ocean variability and where satellites only sense the surface. Increasingly, models and assimilation systems are being used to provide information about the current observing system and to help in the design plans for new observations. Whether it is as a user of observations or a contributor to evaluation of the observing system, ocean synthesis and assimilation systems are now an integral part of the global ocean observing and information system. Major advances have been made over the last decade under the auspices of WCRP's Climate Variability and Predictability Project (CLIVAR) and the Global Ocean Data Assimilation Experiment (GODAE). In addition to advances in the assimilation systems, there have been major developments in the observing system, with satellite altimetry, the tropical moored buoy arrays in the Pacific and Atlantic, and more recently Argo. These developments have led to significant advances in our understanding and prediction of ocean variations at both mesoscale and climate scales. Many challenges remain. Some of these challenges lie in the observations themselves, some in the assimilation systems that, even in the more recent era of unprecedented observations from satellite altimetry and Argo, provide different views of climate variations. Yet there are many examples of successful applications from ocean assimilation products. Use of these systems for assessing the observing system helps identify the strengths of each observation type, and indicates that none of the current observations is redundant. Indeed, the indication is that the ocean remains under-sampled and that further improvements in the observing system are needed for both climate monitoring and prediction. Future developments will be increasingly towards consistent analyses across components of the Earth system using, e.g., coupled atmosphere-ocean models.

Rienecker, Michele M.↗

NASA NTRS2010

Modeling Fire Severity in Black Spruce Stands in the Alaskan Boreal Forest Using Spectral and Non-Spectral Geospatial Data

Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to the fire regime on carbon cycling, energy budgets, and post-fire succession. Remote sensing indices of fire severity have not consistently been well-correlated with in situ observations of important severity characteristics in Alaskan black spruce stands, including depth of burning of the surface organic layer. The incorporation of ancillary data such as in situ observations and GIS layers with spectral data from Landsat TM/ETM+ greatly improved efforts to map the reduction of the organic layer in burned black spruce stands. Using a regression tree approach, the R2 of the organic layer depth reduction models was 0.60 and 0.55 (pb0.01) for relative and absolute depth reduction, respectively. All of the independent variables used by the regression tree to estimate burn depth can be obtained independently of field observations. Implementation of a gradient boosting algorithm improved the R2 to 0.80 and 0.79 (pb0.01) for absolute and relative organic layer depth reduction, respectively. Independent variables used in the regression tree model of burn depth included topographic position, remote sensing indices related to soil and vegetation characteristics, timing of the fire event, and meteorological data. Post-fire organic layer depth characteristics are determined for a large (N200,000 ha) fire to identify areas that are potentially vulnerable to a shift in post-fire succession. This application showed that 12% of this fire event experienced fire severe enough to support a change in post-fire succession. We conclude that non-parametric models and ancillary data are useful in the modeling of the surface organic layer fire depth. Because quantitative differences in post-fire surface characteristics do not directly influence spectral properties, these modeling techniques provide better information than the use of remote sensing data alone.

Barrett, K.↗

NASA NTRS2010

Atmospheric Airborne Pressure Measurements Using the Oxygen A Band for the ASCENDS Mission

We report on airborne atmospheric pressure measurements using new fiber-based laser technology and the oxygen A-band at 765 nm. Remote measurements of atmospheric temperature and pressure are required for a number of NASA Earth science missions and specifically for the Active Sensing of CO2 Emissions Over Nights, Days, and Seasons (ASCENDS) mission. Accurate measurements of tropospheric CO2 on a global scale are very important in order to better understand its sources and sinks and to improve predictions on any future climate change. The ultimate goal of a CO2 remote sensing mission, such as ASCENDS, is to derive the CO2 concentration in the atmosphere in terms of mole fraction in unit of parts-per-million (ppmv) with regard to dry air. Therefore, both CO2 and the dry air number of molecules in the atmosphere are needed in deriving this quantity. O2 is a stable molecule and uniformly mixed in the atmosphere. Measuring the O2 absorption in the atmosphere can thus be used to infer the dry air number of molecules and then used to calculate CO2 concentration. With the knowledge of atmospheric water vapor, we can then estimate the total surface pressure needed for CO2 retrievals. Our work, funded by the ESTO IIP program, uses fiber optic technology and non-linear optics to generate 765 nm laser radiation coincident with the Oxygen A-band. Our pulsed, time gated technique uses several on- and off-line wavelengths tuned to the O2 absorption line. The choice of wavelengths allows us to measure the pressure by using two adjacent O2 absorptions in the Oxygen A-band. Our retrieval algorithm fits the O2 lineshapes and derives the pressure. Our measurements compare favorably with a local weather monitor mounted outside our laboratory and a local weather station.

Riris, Haris↗

NASA NTRS2011

Atmospheric Airborne Pressure Measurements Using the Oxygen A Band for the ASCENDS Mission

Riris, Haris↗

NASA NTRS2016

Climate-Induced Mortality of Siberian Pine and Fir in the Lake Baikal Watershed, Siberia

Siberian pine (Pinus sibirica) and fir (Abies sibirica) (so called ''dark needle conifers", DNC) showed decreased radial growth increment within the Lake Baikal watershed since the 1980s with increasing mortality recorded since the year 2000. Tree ring width was strongly correlated with vapor pressure deficit, aridity and root zone moisture. Water stress from droughts made trees more susceptible to insect attacks causing mortality in about 10% of DNC stands within the Lake Baikal watershed. Within Siberia DNC mortality increased in the southern part of the DNC range. Biogeographically, tree mortality was located within the DNC - forest-steppes transition. Tree mortality was significantly correlated with drought and soil moisture anomalies. Within the interior of the DNC range mortality occurred within relief features with high water stress risk (i.e., steep convex south facing slopes with shallow well-drained soils). In general, DNC mortality in Siberia was induced by increased aridity and severe drought (inciting factors) in synergy with biotic attacks (contributing factor). In future climate scenarios with predicted increase in aridity DNC could be eliminated from the southern part of its current range and will be replaced by drought-resistant conifers and broadleaf species (e.g., Larix sibirica, Pinus silvestris, and Betula pubescence).

Conifer Mortality↗

NASA NTRS2016

Climate-Induced Mortality of Siberian Pine and Fir in the Lake Baikal Watershed, Siberia

Siberian pine (Pinus sibirica) and fir (Abies sibirica) (so called "dark needle conifers", DNC) showed decreased radial growth increment within the Lake Baikal watershed since the 1980s with increasing mortality recorded since the year 2000. Tree ring width was strongly correlated with vapor pressure deficit, aridity and root zone moisture. Water stress from droughts made trees more susceptible to insect attacks causing mortality in about 10% of DNC stands within the Lake Baikal watershed. Within Siberia DNC mortality increased in the southern part of the DNC range. Biogeographically, tree mortality was located within the DNC - forest-steppes transition. Tree mortality was significantly correlated with drought and soil moisture anomalies. Within the interior of the DNC range mortality occurred within relief features with high water stress risk (i.e., steep convex south facing slopes with shallow well-drained soils). In general, DNC mortality in Siberia was induced by increased aridity and severe drought (inciting factors) in synergy with biotic attacks (contributing factor). In future climate scenarios with predicted increase in aridity DNC could be eliminated from the southern part of its current range and will be replaced by drought-resistant conifers and broadleaf species (e.g., Larix sibirica, Pinus silvestris, and Betula pubescence).

Viacheslav I Kharuk↗