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All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Contribution of Anthropogenic Warming to California Drought During 2012-2014

A suite of climate data sets and multiple representations of atmospheric moisture demand are used to calculate many estimates of the self-calibrated Palmer Drought Severity Index, a proxy for near-surface soil moisture, across California from 1901 to 2014 at high spatial resolution. Based on the ensemble of calculations, California drought conditions were record breaking in 2014, but probably not record breaking in 2012-2014, contrary to prior findings. Regionally, the 2012-2014 drought was record breaking in the agriculturally important southern Central Valley and highly populated coastal areas. Contributions of individual climate variables to recent drought are also examined, including the temperature component associated with anthropogenic warming. Precipitation is the primary driver of drought variability but anthropogenic warming is estimated to have accounted for 8-27 percent of the observed drought anomaly in 2012-2014 and 5-18 percent in 2014. Although natural variability dominates, anthropogenic warming has substantially increased the overall likelihood of extreme California droughts.

California↗
NASA NTRS2021

Illinois Disasters: Utilizing NASA Earth Observations to Enhance Drought Monitoring in Illinois

Drought and flooding in Illinois have severe impacts on the communities and ecosystems of the state. Soil moisture is a valuable indicator of drought and flood vulnerability but can be difficult to measure since in situ monitoring is limited to discrete stations throughout the state. The team created a framework to compare in situ, modeled, and NASA satellite soil moisture measurements to increase the spatial coverage of soil moisture monitoring. The team partnered with the Illinois State Weather Survey, USDA Midwest Climate Hub, NOAA Regional Climate Services of the Central Region, NOAA National Integrated Drought Information System’s Midwest Drought Early Warning System, and the NOAA North Central River ForecastCenter. The team standardized and compared soil moisture data from NASA’s Soil Moisture Active Passive (SMAP) mission, modeled soil moisture outputs from NASA’s SPoRT Land Information System (SPoRT-LIS), and in situ measurements from the Illinois State Weather Survey’s Water and Atmospheric Resources Monitoring (WARM) program. Compared to the WARM data, the satellite and modeled data showed seasonally variable differences and bias. The difference was highest in the winter months and lowest in the late summer and early fall months for the SMAP and SPoRT-LIS data products. SPoRT-LIS produced lower seasonal variability and SMAP demonstrated higher correlation values and lower differences. These analyses suggest that both SMAP and SPoRT-LIS products offer unique strengths and limitations when used for soil moisture monitoring

Joshua Green↗
NASA NTRS1980

Atmospheric aerosols and climate

The impact of terrestrial aerosols on the earth's climate and solar and infrared radiation budget are considered. Attention is given to the optical properties of aerosols, that is, optical depth, the single scattering albedo, and the asymmetry parameter, and to the relation between the optical depth and surface temperature for tropospheric and stratospheric aerosols. Also considered are experimental projects to determine the single scattering albedo, as well as the optical properties of natural aerosols such as sea salt, soil, and sulfates, and their variability. In addition, the impact of volcanic activity and the question of whether aerosols cause climatic warming or cooling are discussed, and the available observational evidence linking aerosols and climate is reviewed.

Toon, O. B.↗
NASA NTRS2018

Investigation of NO2 Measurements Made During DISCOVER-AQ and KORUS-AQ Campaigns in Conjunction with NO2 Tropospheric Column from the Ozone Monitoring Instrument (OMI) and High-Resolution Community Multi-Scale Air Quality (CMAQ) Model Simulation

Atmospheric NO2 is produced by combustion, lightning, and in soil. NO2 affects ozone production and criteria pollutant itself.It also has indirect radiative impacts in the troposphere, since ozone has largest warming effect in upper troposphere. Tropospheric vertical column densities (VCD) of NO2 are available from satellites (GOME, OMI, SCIAMACHY, GOME-2). DISCOVER-AQ and KORUS-AQ aircraft campaigns we reconducted to improve the use of satellites to monitor air quality for public health and environmental benefit in United States and South Korea. In this study, we investigate 1) How do these measurements compare? 2) What is the best way to make comparisons of space- and ground-based measurements?

multi-scale air quality↗
NASA NTRS2014

Spring Hydrology Determines Summer Net Carbon Uptake in Northern Ecosystems

Increased photosynthetic activity and enhanced seasonal CO2 exchange of northern ecosystems have been observed from a variety of sources including satellite vegetation indices (such as the Normalized Difference Vegetation Index; NDVI) and atmospheric CO2 measurements. Most of these changes have been attributed to strong warming trends in the northern high latitudes (greater than or equal to 50N). Here we analyze the interannual variation of summer net carbon uptake derived from atmospheric CO2 measurements and satellite NDVI in relation to surface meteorology from regional observational records. We find that increases in spring precipitation and snow pack promote summer net carbon uptake of northern ecosystems independent of air temperature effects. However, satellite NDVI measurements still show an overall benefit of summer photosynthetic activity from regional warming and limited impact of spring precipitation. This discrepancy is attributed to a similar response of photosynthesis and respiration to warming and thus reduced sensitivity of net ecosystem carbon uptake to temperature. Further analysis of boreal tower eddy covariance CO2 flux measurements indicates that summer net carbon uptake is positively correlated with early growing-season surface soil moisture, which is also strongly affected by spring precipitation and snow pack based on analysis of satellite soil moisture retrievals. This is attributed to strong regulation of spring hydrology on soil respiration in relatively wet boreal and arctic ecosystems. These results document the important role of spring hydrology in determining summer net carbon uptake and contrast with prevailing assumptions of dominant cold temperature limitations to high-latitude ecosystems. Our results indicate potentially stronger coupling of boreal/arctic water and carbon cycles with continued regional warming trends.

Carbon Uptake↗
NASA NTRS2015

Climate-Induced Larch Growth Response Within the Central Siberian Permafrost Zone

Aim: estimation of larch (Larix gmelinii) growth response to current climate changes. Location: permafrost area within the northern part of Central Siberia (approximately 65.8 deg N, 98.5 deg E). Method: analysis of dendrochronological data, climate variables, drought index SPEI, GPP (gross primary production) and EVI vegetation index (both Aqua/MODIS satellite derived), and soil water content anomalies (GRACE satellite measurements of equivalent water thickness anomalies, EWTA). Results: larch tree ring width (TRW) correlated with previous year August precipitation (r = 0.63), snow accumulation (r = 0.61), soil water anomalies (r = 0.79), early summer temperatures and water vapor pressure (r = 0.73 and r = 0.69, respectively), May and June drought index (r = 0.68-0.82). There are significant positive trends of TRW since late 1980s and GPP since the year 2000. Mean TRW increased by about 50%, which is similar to post-Little Ice Age warming. TRW correlated with GPP and EVI of larch stands (r = 0.68-0.69). Main conclusions: within the permafrost zone of central Siberia larch TRW growth is limited by early summer temperatures, available water from snowmelt, water accumulated within soil in the previous year, and permafrost thaw water. Water stress is one of the limiting factors of larch growth. Larch TRW growth and GPP increased during recent decades.

permafrost thaw↗
NASA NTRS2022

Irrigation and Warming Drive the Decreases in Surface Albedo Over High Mountain Asia

Human and climate induced land surface changes resulting from irrigation, snow cover decreases, and greening impact the surface albedo over High Mountain Asia (HMA). Here we use a partial information decomposition approach and remote sensing data to quantify the effects of the changes in leaf area index, soil moisture, and snow cover on the surface albedo in HMA, home to over a billion people, from 2003 to 2020. The study establishes strong evidence of anthropogenic agricultural water use over irrigated lands (e.g., Ganges-Brahmaputra) which causes the highest surface albedo decreases (≤1%/year). Greening and decreased snow cover from warming also drive changes in visible and near-infrared surface albedo in different areas of HMA. The significant role of irrigation and greening in influencing albedo suggests the potential of a positive feedback cycle where albedo decreases lead to increased evaporative demand and increased stress on water resources.

Climate sciences↗
NASA NTRS1998

A Technique for Assimilating GOES-Derived Land Surface Products into Regional Models to Improve the Representation of Land Surface Forcing

As the parameterizations of surface energy budgets in regional models have become more complete physically, models have the potential to be much more realistic in simulations of coupling between surface radiation, hydrology, and surface energy transfer. Realizing the importance of properly specifying the surface energy budget, many institutions are using land-surface models to represent the lower boundary forcing associated with biophysical processes and soil hydrology. However, the added degrees of freedom due to inclusion of such land-surface schemes require the specification of additional parameters within the model system such as vegetative resistances, green vegetation fraction, leaf area index, soil physical and hydraulic characteristics, stream flow, runoff, and the vertical distribution of soil moisture. A technique has been developed for assimilating GOES-IR skin temperature tendencies into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. An advantage of this technique for short-range forecasts is that it does not require a complex land-surface formulation within the atmospheric model. As a result, the need to specify poorly known soil and vegetative characteristics is eliminated. The GOES assimilation technique has been incorporated into the PSU/NCAR MM5. Results will be presented to demonstrate the ability of the assimilation scheme to improve short-term simulations of near-surface air temperature and mixing ratio during the warm season for several selected cases during June of 1995 and June 1997 which exhibit a variety of atmospheric and land-surface conditions. In addition, the simulations produced by the assimilation technique will be compared with those produced by the MM5/BATS coupled model initialized with soil water content derived from a soil hydrology model.

Lapenta, William M.↗
NASA NTRS2000

Diagnosing Warm Season Precipitation Over the GCIP Region from a GCM and Reanalysis

A 45 year simulation using a global general circulation model (GCM), the National Center for Atmospheric Research (NCAR) Community Climate Model v.3 (CCM3), forced with observed sea surface temperatures (SST), and 39 years of global National Centers for Environmental Prediction (NCEP) reanalyses were analyzed to determine Mississippi River basin warm season (May, June, July or MJJ) wet and dry year composites in the water and energy budgets. Years that have increased MJJ soil moisture over the GEWEX (Global Water and Energy Experiment) Continental Interior Project (GCIP) region also have high precipitation, lower surface temperature, decreased Bowen ratio, and reduced 500 hPa geopotential height (essentially reduced MJJ ridging). The reverse is true for years that have reduced MJJ soil moisture. Wet years are also accompanied by a general increase in moisture transport from the Gulf of Mexico into the central U.S. There is some indication (though weaker) that soil moisture may then affect precipitation and other quantities and be affected in turn by 500 hPa geopotential heights. The correlations are somewhat low, however, demonstrating the difficulty in providing definitive physical links between the remote and local effects. Analysis of two individual years with an extreme wet event (1993) and an extreme dry event (1988) yields the same general relationships as with the wet and dry composites. The composites from this study are currently serving as the basis for a series of experiments aimed at determining the predictability of the land surface and remote SST on the Mississippi River basin and other large-scale river basins.

Oglesby, Robert↗
NASA NTRS2023

Influence of Lower Tropospheric Moisture on Local Soil Moisture-Precipitation Feedback Over the U.S. Southern Great Plains

Land-atmosphere coupling (LAC) has long been studied focusing on land surface and atmospheric boundary layer processes. However, the influence of lower tropospheric (LT) humidity on LAC remains largely unexplored. In this study, we use radiosonde observations from the U.S. Southern Great Plains (SGP) site and an entrained parcel buoyancy model to investigate the impact of LT humidity on LAC there during the warm season (May–September). We quantify the effect of LT humidity on convective buoyancy by measuring the difference between the 2–4 km vertically integrated buoyancy with and without the influence of background LT humidity. Our results show that, under dry soil conditions, anomalously high LT humidity is necessary to produce the buoyancy profiles required for afternoon precipitation events (APEs). These APEs under dry soil moisture cannot be explained by commonly used local land-atmosphere coupling indices such as the convective triggering potential/low-level humidity index (CTP/HI Low ), which do not account for the influence of the LT humidity. On the other hand, consideration of LT humidity is unnecessary to explain APEs under wet soil moisture conditions, suggesting the boundary layer moisture alone could be sufficient to generate the required buoyancy profiles. These findings highlight the need to consider the impact of LT humidity, which is often decoupled from the humidity near the surface and largely controlled by moisture transport, in understanding land-atmospheric feedbacks over dry soil conditions, especially during droughts or dry spells over the SGP.

Gaoyun Wang↗
NASA NTRS1999

Impact of Assimilating GOES-Derived Land Surface Variables into the PSU/NCAR MM5

Land surface processes are known to have a profound impact on the overlying atmosphere over a wide range of spatial and temporal scales. Many atmospheric numerical models include special parameterizations to improve the specification and partitioning of surface fluxes which are critical to the accurate prediction of warm season boundary layer behavior, organized mesoscale circulations, and convective precipitation. However, the added degrees of freedom resulting from the inclusion of vegetation and soil schemes require the specification of additional surface parameters such as vegetative resistances, green vegetation fraction, leaf area index, soil physical and hydraulic characteristics, and the vertical distribution of soil moisture. As satellite data have become more readily available in recent years, many investigations have attempted to use these new measurements to infer missing components of the surface energy budget. Sensitivity studies have shown land-skin temperature (LST) tendencies during the mid-morning hours are strongly sensitive to the surface moisture availability (a function of soil wetness and vegetation) and less sensitive to other parameters such as surface roughness. Based upon results from these and other studies, developed a simple technique that dynamically assimilates Geostationary Operational Environmental Satellite (GOES) derived land-surface products into the surface energy budget of a mesoscale model. The purpose of this paper is to demonstrate that assimilating the GOES satellite data has the potential to improve the representation of land surface characteristics within the model without prior knowledge of the land surface characteristics. The assimilation technique is presented in Section 2 and the numerical experiments are detailed in Section 3. Preliminary results and conclusions are presented in Sections 4 and 5, respectively.

Lapenta, William M.↗
NASA NTRS2019

Widespread Increase of Boreal Summer Dry Season Length Over the Congo Rainforest

Dry season length strongly influences tropical rainforest vegetation and is largely determined by precipitation patterns. Over the Amazon, the dry season length has increased since 1979 and severe short-term droughts have occurred. However, similar changes have not been investigated for the world’s second largest rainforest, the Congo Basin, where long-term drying and large-scale declines in forest greenness and canopy water content were reported. Here we present observational evidence for widespread increases in the boreal summer (June–August) dry season length over the Congo Basin since the 1980s, from both hydrological and ecological perspectives. We analyzed both dry season onset and dry season end via multiple independent precipitation and satellite derived vegetation datasets for the period 1979–2015. The dry season length increased by 6.4–10.4 days per decade in the period 1988–2013, primarily attributed to an earlier dry season onset and a delayed dry season end. The earlier dry season onset was caused by long-term droughts due to decreased rainfall in the pre-dry season (April–June). The delayed dry season end resulted from insufficiently replenished soil moisture, which postpones the start of the next wet season and hinders vegetation regrowth. If such changes continue, the enhanced water stress in a warming climate may affect the carbon cycle and alter the composition and structure of evergreen rainforest.

Congo rainforest growing season NDVI SIF↗
NASA NTRS2019

Assessment of Soil Moisture Retrievals Using SMAP and ELBARA-III Measurements in a Tibetan Meadow Ecosystem

This study presents results evaluating retrievals of liquid water content for both thawed and frozen soils based on simultaneous SMAP and ELBARA-III measurements in a Tibetan meadow ecosystem. A good agreement is found between time series of the SMAP and ELBARA-III T(sub B(sup P)) measurements (R≥0.87). Differences noted between the two data sets are linked to distinct liquid water content variations found in the specific footprints, and the SMAP measurements are better explained by the in-situ liquid water content. Furthermore, the in-situ liquid water content shows better agreements with both SMAP and ELBARA-III measured T(sub B(sup P)) at horizontal polarization in the cold season, while the measurements at vertical polarization are more consistently varying with the liquid water content for the warm season. With the implementation of new vegetation and surface roughness parameterizations, the dynamics of in-situ liquid water content are better reproduced by corresponding retrievals for both thawed and frozen soils, leading to the reduction of the unbiased root mean-square error (ubRMSE) by more than 31 % in comparison to these retrievals using SMAP default parameterizations. Notably, the single channel algorithm configured with the new parameterizations using SMAP measured vertical polarization during the ascending overpass provides the best liquid water content retrievals with an ubRMSE of 0.035 cu m -cu m that outperforms the SMAP mission specification.

L-band microwave radiometry↗
NASA NTRS2014

The 183-WSL Fast Rain Rate Retrieval Algorithm. Part II: Validation Using Ground Radar Measurements

The Water vapour Strong Lines at 183 GHz (183-WSL) algorithm is a method for the retrieval of rain rates and precipitation type classification (convectivestratiform), that makes use of the water vapor absorption lines centered at 183.31 GHz of the Advanced Microwave Sounding Unit module B (AMSU-B) and of the Microwave Humidity Sounder (MHS) flying on NOAA-15-18 and NOAA-19Metop-A satellite series, respectively. The characteristics of this algorithm were described in Part I of this paper together with comparisons against analogous precipitation products. The focus of Part II is the analysis of the performance of the 183-WSL technique based on surface radar measurements. The ground truth dataset consists of 2.5 years of rainfall intensity fields from the NIMROD European radar network which covers North-Western Europe. The investigation of the 183-WSL retrieval performance is based on a twofold approach: 1) the dichotomous statistic is used to evaluate the capabilities of the method to identify rain and no-rain clouds; 2) the accuracy statistic is applied to quantify the errors in the estimation of rain rates.The results reveal that the 183-WSL technique shows good skills in the detection of rainno-rain areas and in the quantification of rain rate intensities. The categorical analysis shows annual values of the POD, FAR and HK indices varying in the range 0.80-0.82, 0.330.36 and 0.39-0.46, respectively. The RMSE value is 2.8 millimeters per hour for the whole period despite an overestimation in the retrieved rain rates. Of note is the distribution of the 183-WSL monthly mean rain rate with respect to radar: the seasonal fluctuations of the average rainfalls measured by radar are reproduced by the 183-WSL. However, the retrieval method appears to suffer for the winter seasonal conditions especially when the soil is partially frozen and the surface emissivity drastically changes. This fact is verified observing the discrepancy distribution diagrams where2the 183-WSL performs better during the warm months, while during the winter time the discrepancies with radar measurements tends to maximum values. A stable behavior of the 183-WSL algorithm is demonstrated over the whole study period with an overall overestimation for rain rates intensities lower than 1 millimeter per hour. This threshold is crucial especially in wintertime where the low precipitation regime is difficult to be classified.

validationradar↗
NASA NTRS2024

Increasing Prevalence of Hot Drought Across Western North America Since the 16th Century

Across western North America (WNA), 20th-21st century anthropogenic warming has increased the prevalence and severity of concurrent drought and heat events, also termed hot droughts. However, the lack of independent spatial reconstructions of both soil moisture and temperature limits the potential to identify these events in the past and to place them in a long-term context. We develop the Western North American Temperature Atlas (WNATA), a data-independent 0.5° gridded reconstruction of summer maximum temperatures back to the 16th century. Our evaluation of the WNATA with existing hydroclimate reconstructions reveals an increasing association between maximum temperature and drought severity in recent decades, relative to the past five centuries. The synthesis of these paleo-reconstructions indicates that the amplification of the modern WNA megadrought by increased temperatures and the frequency and spatial extent of compound hot and dry conditions in the 21st century are likely unprecedented since at least the 16th century.

Drought↗
NASA NTRS2011

Wildfires in Northern Siberian Larch Dominated Communities

The fire history of the northern larch forests within the permafrost zone in a portion of northern Siberia (approx 66 deg N, 100 deg E) was studied. Since there is little to no human activities in this area fires within the study area were mostly caused by lightning. Fire return intervals (FRI) were estimated based on burn marks on tree stems and dates of tree natality. FRI values varied from 130 yr to 350 yr with 200 +/- 50 yr mean. In southerly larch dominated communities FRI was found to be shorter (77 +/- 20 yr at approx 61 deg. N, and 82 +/- 7 at 64 deg N), and longer at the northern boundary (approx 71 deg) of larch stands (320 +/- 50 yr). During the Little Ice Age period in the 16th to 18th centuries FRI was approximately twice as long as recorded in this study. Fire caused changes in the soil including increases in soil drainage and permafrost thawing depth and a radial growth increase of about 2 times (with more than 6 times observed). This effect may simulate the predicted warming impact on the larch growth in the permafrost zone.

Khaurk, Viacheslav I.↗
NASA NTRS2020

Investigation of the 2016 Eurasia heat wave as an event of the recent warming

This study investigates the physical mechanisms that contributed to the 2016 Eurasian heat wave during boreal summer season (July–August, JA), characterized by much higher than normal temperatures over eastern Europe, East Asia, and the Kamchatka Peninsula. It is found that the 2016 JA mean surface air temperature, upper-tropospheric height, and soil moisture anomalies are characterized by a tri-pole pattern over the Eurasia continent and a wave train-like structure not dissimilar to recent (1980–2016) trends in those quantities. A series of forecast experiments designed to isolate the impacts of the land, ocean, and sea ice conditions on the development of the heat wave is carried out with the Global Seasonal Forecast System version 5. The results suggest that the tri-pole blocking pattern over Eurasia, which appears to be instrumental in the development of the 2016 summer heat wave, can be viewed as an expression of the recent trends, amplified by record-breaking oceanic warming and internal land-atmosphere interactions.

Eunkyo Seo↗
NASA NTRS2019

Improving SMAP freeze-thaw retrievals for pavements using effective soil temperature from GEOS-5: Evaluation against in situ road temperature data over the U.S

Seasonal freeze-thaw (FT) affects over half the northern hemisphere and impacts many key processes of the Earth System such as energy exchange, hydrology and vegetation. Nearly all past studies using spaceborne FT retrievals have focused on characterizing FT specifically for natural environments. FT in the built environment is also routinely studied and a topic of great interest, especially with regards to transportation infrastructure. Whereas natural FT process are frequently investigated using spaceborne observations, FT studies of roads are often limited to local scales, using in situ or nearby weather station data only. Comparisons between FT retrievals obtained from NASA's Soil Moisture Active Passive (SMAP) satellite and roads in Alaska (AK) and the Contiguous United States (CONUS) showed that spaceborne FT retrievals had good agreement with road data. But those results also indicated that NASA FT retrievals in CONUS were relatively too warm compared to road data. If SMAP FT retrievals were to be used for identifying FT transition timing for applications by the transportation community, it is also important for frozen conditions to be identified more accurately. This work is primarily concerned with improving frozen retrievals made in CONUS by calculating new Normalized Polarization Ratio (NPR) thresholds as compared to those currently used in SMAP FT. We found that focusing on a temporal subset of October through May for comparisons greatly improved the correlation between NPR and effective soil temperature (Teff, one of SMAP's ancillary datasets), often from about zero to 0.6. We then applied linear regression between NPR and Teff to obtain new NPR thresholds resulting in the FT-Roads (FT-R) product. NASA FT and FT-R were evaluated against road data at about 1000 locations in CONUS and a battery of different tests indicated that FT-R performed better under nearly all conditions compared to NASA FT. Overall, NASA FT accuracies were 69% and 80% for 6 am and 6 pm SMAP retrievals, while FT-R achieved accuracies of 79% and 82%. We also investigated the potential for using Teff for road FT (6 am, only) and found that those comparisons were even more accurate (84%). We've also quantified inter- and intraregional differences of SMAP FT performance and found that accuracy metrics vary over twice as much between geographic subdivisions (9%) as compared to between the states within a subdivision (4%). Most importantly, the main goal of improving the detection of in situ frozen conditions in CONUS was realized, with FT-R accurately detecting frozen conditions >50% more frequently than NASA FT.

Passive microwave↗