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At least 127 records · Page 7

Climatic History of the Northeastern United States During the Past 3000 Years

Many ecosystem processes that influence Earth system feedbacks - vegetation growth, water and nutrient cycling, disturbance regimes - are strongly influenced by multidecadal- to millennial-scale climate variations that cannot be directly observed. Paleoclimate records provide information about these variations, forming the basis of our understanding and modeling of them. Fossil pollen records are abundant in the NE US, but cannot simultaneously provide information about paleoclimate and past vegetation in a modeling context because this leads to circular logic. If pollen data are used to constrain past vegetation changes, then the remaining paleoclimate archives in the northeastern US (NE US) are quite limited. Nonetheless, a growing number of diverse reconstructions have been developed but have not yet been examined together. Here we conduct a systematic review, assessment, and comparison of paleotemperature and paleohydrological proxies from the NE US for the last 3000 years. Regional temperature reconstructions (primarily summer) show a long-term cooling trend (1000BCE - 1700CE) consistent with hemispheric-scale reconstructions, while hydroclimate data show gradually wetter conditions through the present day. Multiple proxies suggest that a prolonged, widespread drought occurred between 550 and 750CE. Dry conditions are also evident during the Medieval Climate Anomaly, which was warmer and drier than the Little Ice Age and drier than today. There is some evidence for an acceleration of the longer-term wetting trend in the NE US during the past century; coupled with an abrupt shift from decreasing to increasing temperatures in the past century, these changes could have wide-ranging implications for species distributions, ecosystem dynamics, and extreme weather events. More work is needed to gather paleoclimate data in the NE US to make inter-proxy comparisons and to improve estimates of uncertainty in reconstructions.

Marlon, Jennifer R.↗

Examination of Regional Trends in Low Level Cloud Properties Found in the Aqua-MODIS Satellite Record

Clouds have a pronounced influence on the Earth?s climate. Relative to cloud free conditions, they cool the planet by increasing the amount of solar radiation reflected back to space and reducing the amount of sunlight reaching the surface, but they warm the planet by decreasing the amount of thermal infrared radiation escaping to space and increasing the amount reaching the surface (a greenhouse effect). The global mean net cloud radiative effect (CRE) is about -20 W/m2, a cooling effect at both the top-ofatmosphere and surface. Given the magnitude of CRE?s, it is expected that changes in cloud properties could be a significant factor in climate change due to anthropogenic forcing?s, yet cloud feedbacks are not well known and remain one of the largest uncertainties in climate prediction. This paper explores relationships between coincident observations of atmospheric aerosols, clouds and radiation derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and from the Clouds and the Earth?s Radiant Energy System (CERES) instruments on the Aqua satellite. We investigate several interesting regional trends that have emerged in the nearly 18-year satellite record that suggest correlation between changes in low-level cloud properties and changes in aerosol optical depth that may be associated with changes in pollution emissions and possibly with other factors. MERRA reanalysis of meteorological conditions and aerosol particulate species are investigated to help better understand the potential mechanisms responsible for the observed cloud property trends. Finally, we analyze a new CERES flux by cloud type dataset in order to try and isolate the associated trends in low-level cloud radiative effects. It is anticipated that this study using long-term observations of clouds, aerosols and radiative fluxes combined with model reanalysis data will contribute to an improved understanding of cloud climate feedbacks.

William L Smith Jr.↗

Predictability of Malaria Transmission Intensity in the Mpumalanga Province, South Africa, Using Land Surface Climatology and Autoregressive Analysis

There has been increasing effort in recent years to employ satellite remotely sensed data to identify and map vector habitat and malaria transmission risk in data sparse environments. In the current investigation, available satellite and other land surface climatology data products are employed in short-term forecasting of infection rates in the Mpumalanga Province of South Africa, using a multivariate autoregressive approach. The climatology variables include precipitation, air temperature and other land surface states computed by the Off-line Land-Surface Global Assimilation System (OLGA) including soil moisture and surface evaporation. Satellite data products include the Normalized Difference Vegetation Index (NDVI) and other forcing data used in the Goddard Earth Observing System (GEOS-1) model. Predictions are compared to long- term monthly records of clinical and microscopic diagnoses. The approach addresses the high degree of short-term autocorrelation in the disease and weather time series. The resulting model is able to predict 11 of the 13 months that were classified as high risk during the validation period, indicating the utility of applying antecedent climatic variables to the prediction of malaria incidence for the Mpumalanga Province.

Grass, David↗

Uncertainty Analysis for the Miniaturized Laser Heterodyne Radiometer (mini-LHR)

Presented here is a sensitivity analysis for the miniaturized laser heterodyne radiometer (mini-LHR). This passive, ground-based instrument measures carbon dioxide (CO2) in the atmospheric column and has been under development at NASA/GSFC since 2009. The goal of this development is to produce a low-cost, easily-deployable instrument that can extend current ground measurement networks in order to (1) validate column satellite observations, (2) provide coverage in regions of limited satellite observations, (3) target regions of interest such as thawing permafrost, and (4) support the continuity of a long-term climate record. In this paper an uncertainty analysis of the instrument performance is presented and compared with results from three sets of field measurements. The signal-to-noise ratio (SNR) and corresponding uncertainty for a single scan are calculated to be 329.4+/-1.3 by deploying error propagation through the equation governing the SNR. Reported is an absorbance noise of 0.0024 for 6 averaged scans of field data, for an instrument precision of approximately 0.2 ppmv for CO2.

carbon dioxide (CO2)↗

Multi-Decadal Variation of Aerosols: Sources, Transport, and Climate Effects

We present a global model study of multi-decadal changes of atmospheric aerosols and their climate effects using a global chemistry transport model along with the near-term to longterm data records. We focus on a 27-year time period of satellite era from 1980 to 2006, during which a suite of aerosol data from satellite observations, ground-based measurements, and intensive field experiments have become available. We will use the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which involves a time-varying, comprehensive global emission dataset that we put together in our previous investigations and will be improved/extended in this project. This global emission dataset includes emissions of aerosols and their precursors from fuel combustion, biomass burning, volcanic eruptions, and other sources from 1980 to the present. Using the model and satellite data, we will analyze (1) the long-term global and regional aerosol trends and their relationship to the changes of aerosol and precursor emissions from anthropogenic and natural sources, (2) the intercontinental source-receptor relationships controlled by emission, transport pathway, and climate variability.

Chin, Mian↗

Validation of AIRS V6 Surface Temperature over Greenland with GCN and NOAA Stations

This work compares the temporal and spatial characteristics of the AIRSAMSU (Atmospheric Infrared Sounder Advanced Microwave Sounding Unit A) Version 6 and MODIS (Moderate resolution Imaging Spectroradiometer) Collection 5 derived surface temperatures over Greenland. To estimate uncertainties in space-based surface temperature measurements, we re-projected the MODIS Ice Surface Temperature (IST) to 0.5 by 0.5 degree spatial resolution. We also re-gridded AIRS Skin Temperature (Ts) into the same grid but classified with different cloud conditions and surface types. These co-located data sets make intercomparison between the two instruments relatively straightforward. Using this approach, the spatial comparison between the monthly mean AIRS Ts and MODIS IST is in good agreement with RMS 2K for May 2012. This approach also allows the detection of any long-term calibration drift and the careful examination of calibration consistency in the MODIS and AIRS temperature data record. The temporal correlations between temperature data are also compared with those from in-situ measurements from GC-Net (GCN) and NOAA stations. The coherent time series of surface temperature evident in the correlation between AIRS Ts and GCN temperatures suggest that at monthly time scales both observations capture the same climate signal over Greenland. It is also suggested that AIRS surface air temperature (Ta) can be used to estimate the boundary layer inversion.

AIRS↗

Tropical SNO Comparisons of AIRS and CrIS Calibration for Windows

AIRS (Atmospheric Infrared Sounder) on EOS (Earth Observing System)-Aqua and CrIS (Cross-track Infrared Sounder) on Suomi NPP (National Polar-orbiting Partnership) are two hyperspectral infrared sounders with similar capabilities and orbits, so there is a great opportunity to compare their absolute calibration while they are both in orbit. This insures that long-term climate record can be created by concatenating the two instrument records. There are significant differences in instrument architecture which may lead to subtle differences and complicate attempts to combine the records. We use Tropical Simultaneous Nadir Observations (TSNOs), cases where both instruments are looking nearly at the same place at the same time, to explore the differences. Due to the presence of cold clouds and clear hot desert surface, the data cover a brightness temperature range from 190 degrees Kelvin to 340 degrees Kelvin. We concentrate on the differences between the mean of the two instruments using atmospheric window channels as function of brightness temperature in 20-degree-Kelvin wide bins. With the currently available AIRS and CrIS official calibrated data, radiometric differences as large as 0.3 degrees Kelvin are seen at the extreme temperatures. These differences may be reduced in future releases of the AIRS and CrIS calibration.

CrIS↗

The Updated Umkehr Ozone Retrieval Algorithm and its Validation against Satellite Data

Improvements to the Umkehr ozone profile retrieval algorithm have been developed and are now being evaluated. The updated algorithm is able to simulate observations more accurately and provides data output that is easier to analyze. Among the new diagnostic capabilities that the updated algorithm provides is the averaging kernel (AK) method. The AK approach allows studying how the algorithm responds when a small perturbation is made in a particular layer of the atmosphere [Rodgers 1976, 1990]. We will use the AK method to define precisely what Umkehr should measure given a set of profiles measured by other platforms. This method allows us to compare trends and offsets in data more accurately than it has been done in the past. The updated Umkehr retrievals will be validated against SAGE II ozone profiles as well as SSBUV ozone profile data. We will discuss possible reasons for offset between data and differences in derived ozone profile trends. Considerable variability of the ozone profile within the 10-degree latitude envelope creates noise in the SAGE matching dataset and makes comparisons difficult. To eliminate this problem, the SAGE and Umkehr data had been previously de-seasonalized by subtracting the latitude/season dependent ozone climatology. However, the remaining noise in the ozone residuals was still considerably high for trend analysis and was attributed to longitude variability of SAGE sampling. The new ozone climatology (Labow, NASA) that has longitude dependent ozone variability will be used to minimize contribution of sampling noise in comparisons of satellite and ground station. The comparison of zenith-sky radiances (Umkehr N-value measurements) synthesized for a given set of SAGE profiles will be used to determine whether SAGE-derived N-values agree with the Umkehr-measured N-values. The instrumental effects will be discussed. Both the Umkehr data and SAGE II measurements will be analyzed for their information about ozone variability and loss and recovery rates at the mid- and upper (40 km) levels. The updated long-term Umkehr dataset can be used to provide high quality information for identifying signs of ozone recovery. The long Umkehr historical record can provide additional information for separating the dynamic and chemical mechanisms of depletion, and can help the community better understand climate change effects.

Petropavlovskikh, I.↗

Warming Experiments Underpredict Plant Phenological Responses to Climate Change

Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.

phenology↗

Synergy of Satellite Radiation, Precipitation, and Other Meteorological Variable Observations for Global Mean Sea Surface Turbulent Heat Flux Estimation

Sea surface turbulent heat flux is one of the key components in global freshwater and energy balances and plays an important role in atmospheric dynamics, thermodynamics and general circulation. This turbulent heat flux is dominantly decided by sea surface latent heat release with some contribution from sensible heat exchange. The flux and its anomaly could significantly affect ocean heat storage and ocean circulation. They are part of and have great impacts on climate variability. Though the turbulent heat flux is extremely important for the climate and weather systems, only very limited ship and buoy observations of the flux are available over open oceans. There are no global, operational, direct measurements of this crucial meteorological variable. Global estimates are, basically, indirectly calculated from bulk turbulent flux parameterization with a combination of satellite column water vapor, sea surface water temperature, and wind speed observations. Critical parameters such as sea surface air temperature and humidity are estimated from empirical relations of theses variables with the water vapor and sea surface water temperature, respectively. Lacking accurate knowledge on surface air temperature and humidity, uncertainties in the parameterization and potential changes in the non-linear turbulent processes with long-term climate variations could cause large errors in estimated long-term turbulent fluxes from the indirect method as shown in current global sea surface turbulent flux datasets. This study uses synergized data of satellite global radiation, precipitation, and other meteorological variable observations to estimate sea surface turbulent heat fluxes. The radiation observations are made by the satellite Clouds and the Earth’s Radiant Energy System (CERES) sensors, while the global precipitation data is from NASA’s satellite Global Precipitation Climatology Project (GPCP). Other data includes satellite sea surface water temperature and wind speed observations. These datasets are obtained from a wide range of space sensors from passive to active instruments and from visible and near infrared to thermal infrared and microwave spectral sounders. One significant feature of these datasets is that they have multi-decades long climate records. Top-of-atmosphere (TOA) radiation and its anomaly represents the net heat energy input to the climate system, and the oceanic precipitation and ocean-land moisture transport can be used to quantify sea surface latent heat release. Based on the synergized datasets and the principle of global water and energy balances, global mean turbulent heat fluxes are estimated. The turbulent heat anomalies for the first two decades of the 21st century are, then, obtained mainly from global CERES radiation and GPCP precipitation anomalies, along with CERES derived ocean-land heat transports. Analysis indicates that the uncertainties in the estimated turbulent flux anomalies may be reduced considerably. The results suggest a strong needs in synchronized and synergized observations of atmospheric radiation, precipitation, and oceanic meteorological variables for long-term climate studies.

Bing Lin↗

The Stratospheric Aerosol and Gas Experiment (SAGE III) on the International Space Station (ISS) Mission

The Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) mission will provide the science community with high-vertical resolution and nearly global observations of ozone, aerosols, water vapor, nitrogen dioxide, and other trace gas species in the stratosphere and upper-troposphere. SAGE III/ISS measurements will extend the long-term Stratospheric Aerosol Measurement (SAM) and SAGE data record begun in the 1970s. The multi-decadal SAGE ozone and aerosol data sets have undergone intense scrutiny and are considered the international standard for accuracy and stability. SAGE data have been used to monitor the effectiveness of the Montreal Protocol. Key objectives of the mission are to assess the state of the recovery in the distribution of ozone, to re-establish the aerosol measurements needed by both climate and ozone models, and to gain further insight into key processes contributing to ozone and aerosol variability. The space station mid-inclination orbit allows for a large range in latitude sampling and nearly continuous communications with payloads. The SAGE III instrument is the fifth in a series of instruments developed for monitoring atmospheric constituents with high vertical resolution. The SAGE III instrument is a moderate resolution spectrometer covering wavelengths from 290 nm to 1550 nm. Science data is collected in solar occultation mode, lunar occultation mode, and limb scatter measurement mode. A SpaceX Falcon 9 launch vehicle will provide access to space. Mounted in the unpressurized section of the Dragon trunk, SAGE III will be robotically removed from the Dragon and installed on the space station. SAGE III/ISS will be mounted to the ExPRESS Logistics Carrier-4 (ELC-4) location on the starboard side of the station. To facilitate a nadir view from this location, a Nadir Viewing Platform (NVP) payload was developed which mounts between the carrier and the SAGE III Instrument Payload (IP).

Cisewski, Michael↗

Sampling theory applied to measurement and analysis of temperature for climate studies

Of all the errors discussed in climatology literature, aliasing errors caused by undersampling of unsmoothed or improperly smoothed temperature data seem to be completely overlooked. This is a serious oversight in view of long-term trends of 1 K or less. Adequate sampling of properly smoothed data is demonstrated with a Hamming digital filter. It is also demonstrated that hourly temperatures, daily averages, and annual averages free of aliasing errors can be obtained by use of a microprocessor added to standard weather sensors and recorders.

Edwards, Howard B.↗

Variability and Extremes of Precipitation in the Global Climate as Determined by the 25-Year GEWEX/GPCP Data Set

The Global Precipitation Climatology Project (GPCP) 25-year precipitation data set is used to evaluate the variability and extremes on global and regional scales. The variability of precipitation year-to-year is evaluated in relation to the overall lack of a significant global trend and to climate events such as ENSO and volcanic eruptions. The validity of conclusions and limitations of the data set are checked by comparison with independent data sets (e.g., TRMM). The GPCP data set necessarily has a heterogeneous time series of input data sources, so part of the assessment described above is to test the initial results for potential influence by major data boundaries in the record. Regional trends, or inter-decadal changes, are also analyzed to determine validity and correlation with other long-term data sets related to the hydrological cycle (e.g., clouds and ocean surface fluxes). Statistics of extremes (both wet and dry) are analyzed at the monthly time scale for the 25 years. A preliminary result of increasing frequency of extreme monthly values will be a focus to determine validity. Daily values for an eight-year are also examined for variation in extremes and compared to the longer monthly-based study.

Adler, R. F.↗

Changes in Land Use Enhance the Sensitivity of Tropical Ecosystems to Fire-Climate Extremes

The Pantanal, the largest contiguous wetland in the world with a high diversity of ecosystems and habitat for several endangered species, was impacted by record-breaking wildfires in 2020. In this study, we integrate satellite and modeling data that enable exploration of natural and human contributing factors to the unprecedented 2020 fires. We demonstrate that the fires were fueled by an exceptional multi-year drought, but dry conditions solely could not explain the spatial patterns of burning. Our analysis reveals how human-caused fires exacerbated drought effects on natural ecosystem within the Pantanal, with large burned fractions primarily over natural (52%), and low cattle density areas (44%) in 2020. The post-fire ecosystem and hydrology changes also had strong ecological effects, with vegetation productivity less than − 1.5 σ over more than 30% of the natural and conservation areas. In contrast to more managed areas, there was a clear decrease in evaporation (by ~ 9%) and an increase in runoff (by ~ 5%) over the natural areas, with long-term impacts on ecosystem recovery and fire risk. This study provides the first tropical evidence outside rainforests of the synergy between climate, land management and fires, and the associated impacts on the ecosystem and hydrology over the largest contiguous wetlands in the world.

Sujay Kumar↗

Satellite Contributions to the Quantitative Characterization of Biomass Burning for Climate Modeling

Characterization of biomass burning from space has been the subject of an extensive body of literature published over the last few decades. Given the importance of this topic, we review how satellite observations contribute toward improving the representation of biomass burning quantitatively in climate and air-quality modeling and assessment. Satellite observations related to biomass burning may be classified into five broad categories: (i) active fire location and energy release, (ii) burned areas and burn severity, (iii) smoke plume physical disposition, (iv) aerosol distribution and particle properties, and (v) trace gas concentrations. Each of these categories involves multiple parameters used in characterizing specific aspects of the biomass-burning phenomenon. Some of the parameters are merely qualitative, whereas others are quantitative, although all are essential for improving the scientific understanding of the overall distribution (both spatial and temporal) and impacts of biomass burning. Some of the qualitative satellite datasets, such as fire locations, aerosol index, and gas estimates have fairly long-term records. They date back as far as the 1970s, following the launches of the DMSP, Landsat, NOAA, and Nimbus series of earth observation satellites. Although there were additional satellite launches in the 1980s and 1990s, space-based retrieval of quantitative biomass burning data products began in earnest following the launch of Terra in December 1999. Starting in 2000, fire radiative power, aerosol optical thickness and particle properties over land, smoke plume injection height and profile, and essential trace gas concentrations at improved resolutions became available. The 2000s also saw a large list of other new satellite launches, including Aqua, Aura, Envisat, Parasol, and CALIPSO, carrying a host of sophisticated instruments providing high quality measurements of parameters related to biomass burning and other phenomena. These improved data products have enabled significant progress in the study of biomass burning from space. However, appreciable uncertainty remains in many of the measurements that still needs to be addressed. Nevertheless, climate and other atmospheric models are

Ichoku, Charles↗

State of the Climate in 2020: Global Oceans

This chapter details 2020 global patterns in select observed oceanic physical, chemical, and biological variables relative to long-term climatologies, their differences between 2020 and 2019, and puts 2020 observations in the context of the historical record. In this overview we address a few of the highlights, first in haiku, then paragraph form: La Niña arrives, shifts winds, rain, heat, salt, carbon: Pacific—beyond. Compiled by NOAA’s National Centers for Environmental Information, "State of the Climate in 2020" is based on contributions from scientists from around the world. It provides a detailed update on global climate indicators, notable weather events, and other data collected by environmental monitoring stations and instruments located on land, water, ice, and in space. The full report is available from: https://doi.org/10.1175/2021BAMSStateoftheClimate.1.

Gregory C Johnson↗

Long-Term Ozone Variability and Trends from Reanalyses

Stratospheric ozone has a profound impact on radiation and chemistry over various spatial and temporal scales. The evolution of stratospheric ozone over the 21st century, however, is not well understood, especially in the lower stratosphere. Highly vertically resolved ozone data from satellite-borne limb sounders have proved to be invaluable for studying ozone in the middle and upper stratosphere but it was not until recently that these measurements were successfully incorporated in atmospheric reanalyses. Validation and comparison studies have demonstrated that the addition of observations from the Microwave Limb Sounder (MLS) on EOS (Earth Observing System) Aura greatly improved the quality of ozone fields in MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) making these assimilated data sets more useful for scientific research. In this presentation we demonstrate that multidecadal lower-stratospheric ozone variability and trends can be derived from NASA's MERRA-2 reanalysis ozone. In particular, the reanalysis ozone bias-corrected using a chemistry model simulation as a transfer function agrees very well with recently reprocessed long ozonesonde records. Ozone trends in the lower stratosphere will be discussed in the context of recent findings (Ball et al., 2018) and interpreted in connection with long-term circulation changes in the lower stratosphere. Next, we show that the use of ozone data retrieved from the next generation OMPS (Ozone Mapping Profiler Suite) instruments, including the OMPS Limb Profiler, can successfully extend the reanalyses into the future allowing comprehensive monitoring of global ozone and interpretation of its evolution during the critical period of expected ozone recovery and climate change from increasing concentration of greenhouse gases.

ozone↗

Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

Clouds cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the whole globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years in length. However, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provided the first coordinated intercomparison of publically available, standard global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multiangle view and polarization capabilities), IR sounders and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude), cloud radiative properties (optical depth or emissivity), cloud thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. A monthly, gridded database, in common format, facilitates further assessments, climate studies and the evaluation of climate models.

Stubenrauch, C. J.↗