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At least 163 records · Page 9

Autonomous, Full-Time Cloud Profiling at Arm Sites with Micro Pulse Lidar

Since the early 1990's technology advances permit ground based lidar to operate full time and profile all significant aerosol and cloud structure of the atmosphere up to the limit of signal attenuation. These systems are known as Micro Pulse Lidars (MPL), as referenced by Spinhirne (1993), and were first in operation at DOE Atmospheric Radiation Measurement (ARM) sites. The objective of the ARM program is to improve the predictability of climate change, particularly as it relates to cloud-climate feedback. The fundamental application of the MPL systems is towards the detection of all significant hydrometeor layers, to the limit of signal attenuation. The heating and cooling of the atmosphere are effected by the distribution and characteristics of clouds and aerosol concentration. Aerosol and cloud retrievals in several important areas can only be adequately obtained with active remote sensing by lidar. For cloud cover, the height and related emissivity of thin clouds and the distribution of base height for all clouds are basic parameters for the surface radiation budget, and lidar is essetial for accurate measurements. The ARM MPL observing network represents the first long-term, global lidar study known within the community. MPL systems are now operational at four ARM sites. A six year data set has been obtained at the original Oklahoma site, and there are several years of observations at tropical and artic sites. Observational results include cloud base height distributions and aerosol profiles. These expanding data sets offer a significant new resource for cloud, aerosol and atmospheric radiation analysis. The nature of the data sets, data processing algorithms, derived parameters and application results are presented.

Spinhirne, James D.↗

Full-Time, Eye-Safe Cloud and Aerosol Lidar Observation at Atmospheric Radiation Measurement Program Sites: Instruments and Data Analysis

Atmospheric radiative forcing, surface radiation budget, and top of the atmosphere radiance interpretation involves a knowledge of the vertical height structure of overlying cloud and aerosol layers. During the last decade, the U.S. Department of Energy through I the Atmospheric Radiation Measurement (ARM) program has constructed four long- term atmospheric observing sites in strategic climate regimes (north central Oklahoma, In Barrow. Alaska, and Nauru and Manus Islands in the tropical western Pacific). Micro Pulse Lidar (MPL) systems provide continuous, autonomous observation of all significant atmospheric cloud and aerosol at each of the central ARM facilities. Systems are compact and transmitted pulses are eye-safe. Eye-safety is achieved by expanding relatively low-powered outgoing Pulse energy through a shared, coaxial transmit/receive telescope. ARM NIPL system specifications, and specific unit optical designs are discussed. Data normalization and calibration techniques are presented. A multiple cloud boundary detection algorithm is also described. These techniques in tandem represent an operational value added processing package used to produce normalized data products for Cloud and aerosol research and the historical ARM data archive.

Campbell, James R.↗

Combining Satellite Data, Trajectory Modeling and Surface Insolation Measurements to Deduce the Direct Radiative Effect of Smoke Aerosol

In this paper, we have introduced a method of inferring the radiative effect of smoke aerosols using a technique that combines satellite remote sensing with trajectory modeling. The results shown here clearly show large flux biases between theoretical and measured radiative fluxes correlate with the arrival of smoke aerosol to the area. Further analysis is required to convincingly demonstrate that the reason for these differences is the radiative effect of the smoke aerosols. To do this, the estimated fluxes taken from the ERA-15 will be recomputed every 3 hours using International Satellite Cloud Climatology Project (ISCCP) data set entitled DX gridded to a 1o equal angle resolution (see paper 7B.2 for details). Surface radiometric and ancillary data for several more Canadian surface sites are being obtained at minute temporal resolution. The ultimate purpose of this research is to derive aerosol smoke maps for fire events such as this to be included in an aerosol climatology and be incorporated in the computation of the earth's surface radiation budget to better understand the radiative effect of aerosols.

Stackhouse, Paul W., Jr.↗

Comparison of Monthly Mean Cloud Fraction and Cloud Optical depth Determined from Surface Cloud Radar, TOVS, AVHRR, and MODIS over Barrow, Alaska

A one year comparison is made of mean monthly values of cloud fraction and cloud optical depth over Barrow, Alaska (71 deg 19.378 min North, 156 deg 36.934 min West) between 35 GHz radar-based retrievals, the TOVS Pathfinder Path-P product, the AVHRR APP-X product, and a MODIS based cloud retrieval product from the CERES-Team. The data sets represent largely disparate spatial and temporal scales, however, in this paper, the focus is to provide a preliminary analysis of how the mean monthly values derived from these different data sets compare, and determine how they can best be used separately, and in combination to provide reliable estimates of long-term trends of changing cloud properties. The radar and satellite data sets described here incorporate Arctic specific modifications that account for cloud detection challenges specific to the Arctic environment. The year 2000 was chosen for this initial comparison because the cloud radar data was particularly continuous and reliable that year, and all of the satellite retrievals of interest were also available for the year 2000. Cloud fraction was chosen as a comparison variable as accurate detection of cloud is the primary product that is necessary for any other cloud property retrievals. Cloud optical depth was additionally selected as it is likely the single cloud property that is most closely correlated to cloud influences on surface radiation budgets.

Uttal, Taneil↗

A Global Perspective: NASA's Prediction of Worldwide Energy Resources (POWER) Project

The Prediction of the Worldwide Energy Resources (POWER) Project, initiated under the NASA Science Mission Directorate Applied Science Energy Management Program, synthesizes and analyzes data on a global scale that are invaluable to the renewable energy industries, especially to the solar and wind energy sectors. The POWER project derives its data primarily from NASA's World Climate Research Programme (WCRP)/Global Energy and Water cycle Experiment (GEWEX) Surface Radiation Budget (SRB) project (Version 2.9) and the Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS) assimilation model (Version 4). The latest development of the NASA POWER Project and its plans for the future are presented in this paper.

Zhang, Taiping↗

Evaluation of Aerosol-cloud Interaction in the GISS Model E Using ARM Observations

Observations from the US Department of Energy's Atmospheric Radiation Measurement (ARM) program are used to evaluate the ability of the NASA GISS ModelE global climate model in reproducing observed interactions between aerosols and clouds. Included in the evaluation are comparisons of basic meteorology and aerosol properties, droplet activation, effective radius parameterizations, and surface-based evaluations of aerosol-cloud interactions (ACI). Differences between the simulated and observed ACI are generally large, but these differences may result partially from vertical distribution of aerosol in the model, rather than the representation of physical processes governing the interactions between aerosols and clouds. Compared to the current observations, the ModelE often features elevated droplet concentrations for a given aerosol concentration, indicating that the activation parameterizations used may be too aggressive. Additionally, parameterizations for effective radius commonly used in models were tested using ARM observations, and there was no clear superior parameterization for the cases reviewed here. This lack of consensus is demonstrated to result in potentially large, statistically significant differences to surface radiative budgets, should one parameterization be chosen over another.

Clouds↗

TPSAS-NF1676L-32099-DND

This talk provides a short overview of the new POWER web site that provides data parameters to energy sector societal benefit areas from NASA research projects. The NASA research projects include the GEWEX Surface Radiation Budget project, the CERES Fast Shortwave and Longwave radiative flux project (FLASHFlux) and NASA Goddard's Global Modeling and Assimilation Office (GMAO) MERRA-2 atmospheric reanalysis. Data products are customized to the energy industry and make products available from the daily time scale to long-term climatological averages. The web services allow uses to choose multiple parameters and obtain the data in multiple file formats. This short talk is designed to be delivered at the NASA booth area at the 2018 Fall American Geophysical Union conference.

Paul W Stackhouse, Jr.↗

A Method for Landsat and Sentinel 2 (HLS) BRDF Normalization

The Harmonized Landsat/Sentinel-2 (HLS) project aims to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2 remote sensing satellites. These satellites’ sampling characteristics provide nearly constant observation geometry and low illumination variation through the scene. However, the illumination variation throughout the year impacts the surface reflectance by producing higher values for low solar zenith angles and lower reflectance for large zenith angles. In this work, we present a model to derive the bidirectional reflectance distribution function (BRDF) normalization and apply it to the HLS product at 30m spatial resolution. It is based on the BRDF parameters estimated from the MODerate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product (M{O,Y}D09) at 1 km spatial resolution using the VJB method (Vermote et al., 2009). Unsupervised classification (segmentation) of HLS images is used to disaggregate the BRDF parameters to the HLS spatial resolution and to build a BRDF parameters database at HLS scale. We first test the proposed BRDF normalization for different solar zenith angles over two homogeneous sites, in particular one desert and one Peruvian Amazon forest. The proposed method reduces both the correlation with the solar zenith angle and the coefficient of variation (CV) of the reflectance time series in the red and near infrared bands to 4% in forest and keeps a low CV of 3% to 4% for the deserts. Additionally, we assess the impact of the view zenith angle (VZA) in an area of the Brazilian Amazon forest close to the equator, where impact of the angular variation is stronger because it occurs in the principal plane. The directional reflectance shows a strong dependency with the VZA. The current HLS BRDF correction reduces this dependency but still shows an under-correction, especially in the near infrared, while the proposed method shows no dependency with the view angles. We also evaluate the BRDF parameters using field surface albedo measurements as a reference over seven different sites of the US surface radiation budget observing network (SURFRAD) and five sites of the Australian OzFlux network.

Belen Franch↗

Towards a More Realistic Representation of Surface Albedo in NASA CERES Satellite Products: A Comparison with MOSAiC Field Campaign

Observing the Arctic from space is one of the most challenging tasks in climate science. Uncertainty in the NASA Clouds and the Earth’s Radiant Energy System (CERES)-derived irradiances is larger over sea ice than any other scene type and comes from several sources. The one-year long MOSAiC expedition in the central Arctic provides a rare opportunity to explore uncertainty in CERES-derived radiative fluxes. First, a systematic and statistically robust assessment of surface shortwave and longwave fluxes has been conducted using in-situ measurements from MOSAiC flux stations. The CERES SYN1deg product overestimates the SW_down flux by 11.40 Wm-2 and underestimates the SW_up flux by −15.70 Wm-2 and LW_down fluxes by −13.30 Wm-2 at the surface during summertime. In addition, large differences are found in the LW_up flux (~320 Wm-2) when the surface reaches melting point (~0℃). The large negative bias in upwelling shortwave flux can be attributed to the underestimation of surface albedo (−0.15) in SYN1deg. In addition to direct comparison, a series of perturbation experiments with a radiative transfer model are performed to estimate the contributions to the differences. By correcting both cloud and albedo inputs, the biases in SW_net flux and LW_net flux can be reduced to less than half of the control run biases to +19.90% and −10.53%, respectively. Furthermore, a compensating effect between underestimation of broadband albedo and overestimation of spectral albedo in visible and mid-infrared bands in SYN1deg datasets is found and contributes to the shortwave flux differences. The difference in CERES broadband albedo (~20 Wm 2) contributes to larger uncertainty in SW_up flux than spectral albedo shape (~3 Wm 2). The results of this study inform the future development of CERES products and will ultimately reduce uncertainties in Arctic surface radiation budget derived from satellite measurements.

Yiyi Huang↗

CERES Top-of-atmosphere and Surface fluxes in the Arctic: A comparison with ARISE and MOSAiC measurements

Uncertainty in the NASA Clouds and the Earth’s Radiant Energy System (CERES)-derived irradiances is larger over sea ice than any other surface type and comes from several sources. This presentation summarizes results from comparisons of CERES data with the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic and the Arctic Radiation and Icebridge Sea ice Experiment (ARISE). The CERES Synoptic 1degree (SYN1deg) product overestimates the downwelling shortwave flux by 11.40 Wm–2 and underestimates the upwelling shortwave flux by –15.70 Wm–2 and downwelling longwave fluxes by –12.58 Wm–2 at the surface during summer. In addition, large differences are found in the upwelling longwave flux when the surface approaches the melting point (approximately 0C). The large negative bias in upwelling shortwave flux can be attributed in large part to lower surface albedo (–0.15) in satellite footprint relative to surface sensors. The CERES-MOSAiC broadband albedo differences (approximately 20 Wm–2) explain a larger portion of the upwelling shortwave flux difference than the spectral albedo shape differences (approximately 3 Wm–2). The ARISE results indicate the some of these differences in the SW are due to the scene identification and representation of anisotropy in partly cloud scenes. Switching from imager-based to passive microwave-based sea ice data in the CERES inversion process reduces the differences in the grid box average fluxes and in the sea ice partly cloudy scene anisotropy in the instantaneously-matched footprints. Our analysis indicates that calibration and sampling uncertainty limit the ability to place strong constraints (<7%) on CERES TOA fluxes with aircraft measurements. The results indicate that improvements in the surface albedo and cloud data would substantially reduce the uncertainty in the Arctic surface radiation budget derived from CERES data products.

Patrick C Taylor↗

Creating A Consistent Historical NASA POWER Solar Radiation Dataset to Support Renewable Energy, Building Energy Efficiency and Agro-Climatology Decisions

Prediction of Worldwide Energy Resources (POWER) project provides irradiance dataset to support renewable energy, building energy efficiency and agricultural needs. These datasets are derived from Global Energy and Water Cycle Experiment Surface Radiation Budget (GEWEX SRB) and Clouds and the Earth’s Radiant Energy System (CERES SYN1Deg). A systematic bias has been reported between these two datasets for the years with overlapping observations. For obtaining a consistent climate data record spanning the entire time record of observations, it is crucial to understand and remove the bias in the irradiance dataset. Inconsistency in solar radiation data can lead to inaccurate conclusions about solar energy potential and obscure real trends in solar radiation patterns that would impact energy availability assessments. In this study, we adapt quantile mapping approach to remove the systematic bias and to improve reliability of shortwave and longwave irradiance data. We present a validation of the bias corrected data against ground truth. For each 1° latitude and 1° longitude grid box across the globe, we match the CDFs of the reference dataset (CERES SYN1Deg) to that of the SRB dataset, thereby, adjusting the irradiance values to match the empirical distribution of two different measurements. The performance of quantile mapping is evaluated by using the metrics such as Mean Absolute Deviation (MAD). The results indicate that the quantile mapping significantly improves the accuracy and reliability of solar irradiance dataset especially for the weather conditions associated with high cloud cover and extreme irradiance values. The initial range of MAD for the studied sites for daily data was 4 to 19 Wm-2. After correction these reduced to 3 to 7 Wm-2. The findings from this study have important implications for solar energy system design, agricultural planning, and climate modeling community. Reducing the inconsistency and biases in solar irradiance dataset can enable better planning and operation of solar energy systems, leading to increased efficiency and cost-effectiveness. Additionally, this work also contributes to the statistical post-processing techniques in the renewable energy domain and highlights the potential of historical and near-real-time NASA POWER dataset as a valuable resource for solar energy research and applications.

POWER↗

A Comparison of Time-Series Gap-Filling Methods to Impute Solar Radiation Data: Preprint

Complete solar resource data sets play a critical role at every stage of solar energy projects; however, measured or modeled solar resource data come with significant uncertainties and usually suffer from several issues, including, but not limited to, data gaps and data quality issues. To mitigate these issues, an appropriate data imputation method should be implemented to build a complete and reliable temporal (and spatial) database. Motivated by this, in this study, we extensively compare the performance of eight different gap-filling methods by creating random and artificial data gaps in (i) hourly irradiance data for 1 year using a few locations of the National Solar Radiation Database (NSRDB) and (ii) 1-minute ground measurement data sets from the Surface Radiation Budget Network (SURFRAD) and the National Renewable Energy Laboratory (NREL) stations.

clearness index↗

Assessing the Variability of Radiation, Water and Energy in the Deep Tropics Over the Last 3 Decades

Global surface energy closure and its variability depends heavily upon the surface radiative energy budget in the deep tropics. A key process observed is the change in convection regimes from disorganized convection to organized deep convection. During these periods an imbalance is observed between energy and water fluxes in terms of energy closure in some atmospheric reanalysis systems, implying that processes are not simulated well. A recent paper by Hsaio et al (2023, pre-published version) found that the transition process has wind shear and longwave cloud radiative feedback signatures. In this presentation, we assess the surface radiative budget in the deep tropics by comparing multiple data products (GEWEX SRB Rel4IP, CERES Ed4.1, ISSCP FH, etc.) and describing the variability across the deep tropics for the period from 1988 to near present. We assess this variability of the radiative flux anomalies (including the net TOA, surface and the atmospheric divergence fluxes) against water vapor divergence, cloud properties (include ISCCP “Weather States, Tselioudis et al. 2021) and larger scale wind shear. We include further analysis contrasting 6 key tropical oceanic regions (Indian Ocean east and west, tropical western, central and eastern Pacific Ocean, and Tropical Atlantic Ocean) and the sensitivity of the fluxes as a function of fluctuations in cloud types in response to various larger scale atmospheric processes (e.g. El Niño, Indian Ocean Dipole). These are contrasted against the modeled radiative fluxes from ERA-5 and MERRA-2. Ocean buoy measurements of radiative fluxes are utilized to help assess data radiative flux uncertainty over the nearly 40 year period. In general, the variability for overlap periods of these various data products agrees well, but there are significant differences in the net fluxes that vary according to the rendering of surface, atmospheric, aerosol and cloud properties. We conclude with recommendations for continuing work.

Radiation budget↗

Impact of clouds on the shortwave radiation budget of the surface-atmosphere system for snow-covered surfaces

Recent data from the Earth Radiation Budget Experiment (ERBE) have raised the question as to whether or not the addition of clouds to the atmospheric column can decrease the top-of-the atmosphere (TOA) albedo over bright snow-covered surface. To address this issue, ERBE shortwave pixel measurements have been collected with surface insolation measurements made at two snow-covered locations: the South Pole and Saskatoon, Saskatchewan. Both collected datasets show a negative correlation (with solar zenith angle variability removed) between TOA albedo and surfaces insolation. Because increased cloudiness acts to reduce surface insolation, these negative correlations demonstrate that clouds increase the TOA albedo at both snow-covered locations.

Nemesure, Seth↗

Impact of Asian Dust on Global Surface Air Quality and Radiation Budget

Dust originating from Asian deserts and desertification areas can be transported regionally and globally to affect surface air quality, visibility, and radiation budget not only at immediate downwind locations (e.g., eastern Asia) but also regions far away from the sources (e.g., North America). Deposition of Asian dust to the North Pacific Ocean basin influences the ocean productivity. In this study, we will use the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, remote sensing data form satellite and from the ground-based network, and in-situ data from aircraft and surface observations to address the following questions: - What are the effects of Asian dust on the surface air quality and visibility over Asia and North America? - What are the seasonal and spatial variations of dust deposition to the North Pacific Ocean? How does the Asian dust affect surface radiation budget?

Chin, Mian↗

A radiometric model of an earth radiation budget radiometer optical system with diffuse-specular surfaces

The Earth Radiation Budget Experiment (ERBE) is to fly on NASA's Earth Radiation Budget Satellite (ERBS) and on NOAA F and NOAA G. Large spatial scale earth energy budget data will be derived primarily from measurements made by the ERBE nonscanning instrument (ERBE-NS). A description is given of a mathematical model capable of simulating the radiometric response of any of the ERBE-NS earth viewing channels. The model uses a Monte Carlo method to accurately account for directional distributions of emission and reflection from optical surfaces which are neither strictly diffuse nor strictly specular. The model computes radiation exchange factors among optical system components, and determines the distribution in the optical system of energy from an outside source. Attention is also given to an approach for implementing the model and results obtained from the implementation.

Luther, M. R.↗

Surface temperature comparison of the Arctic winter MOSAiC observations, ERA5 reanalysis, and MODIS satellite retrieval

Atmospheric model systems, such as those used for weather forecast and reanalysis production, often have significant and systematic errors in their representation of the Arctic surface energy budget and its components. The newly available observation data of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition (2019/2020) enable a range of model analyses and validation in order to advance our understanding of potential model deficiencies. In the present study, we analyze deficiencies in the surface radiative energy budget over Arctic sea ice in the ERA5 global atmospheric reanalysis by comparing against the winter MOSAiC campaign data, as well as, a pan-Arctic level-2 MODIS ice surface temperature remote sensing product. We find that ERA5 can simulate the timing of radiatively clear periods, though it is not able to distinguish the two observed radiative Arctic winter states, radiatively clear and opaquely cloudy, in the distribution of the net surface radiative budget. The ERA5 surface temperature over Arctic sea ice has a conditional error with a positive bias in radiatively clear conditions and a negative bias in opaquely cloudy conditions. The mean surface temperature error is 4°C for radiatively clear situations at MOSAiC and up to 15°C in some parts of the Arctic. The spatial variability of the surface temperature, given by 4 observation sites at MOSAiC, is not captured by ERA5 due to its spatial resolution but represented in the level-2 satellite product. The sensitivity analysis of possible error sources, using satellite products of snow depth and sea ice thickness, shows that the positive surface temperature errors during radiatively clear events are, to a large extent, caused by insufficient sea ice thickness and snow depth representation in the reanalysis system. A positive bias characterizes regions with ice thickness greater than 1.5 m, while the negative bias for thinner ice is partly compensated by the effect of snow.

54 ENVIRONMENTAL SCIENCES↗

The modulation of the low-latitude radiation budget by cloud and surface forcing on interannual time scales

Regionally confined interannual perturbations in the tropical radiation budget associated with east-west circulations are examined along with the forcing mechanisms of these perturbations in relation to surface and cloudiness variability. A zonal harmonic analysis of emitted longwave radiation emphasizes that these variations are largely controlled at the planetary wave scale. The overall effect leads to an approximately 50 deg/yr propagation phase speed that is considerably slower than the oceanic Kelvin wave capable of driving east-west longwave (LW) anomalies through SST feedback. Examination of the time-dependent radiative energetics over the tropics reveals that the aforementioned anomaly LW propagation is mainly due to cloud forcing associated with east-west circulation changes. Diabatic heating associated with coupled ocean-atmosphere feedback appears to be larger responsible for the LW anomaly propagation.

Sohn, Byung-Ju↗