Engineering topics

Baidar, Sunil

Publications and source records attributed to Baidar, Sunil.

12 records

DOE OSTI2024

Coastal-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) Science Plan

Understanding the mechanisms governing the urban atmospheric environment is critical for informing urban populations regarding the impacts of climate change and associated mitigation and adaptation measures. Earth system (climate and weather) models have not yet been adapted to provide accurate predictions of climate and weather variability within cities, nor do they provide well-tested representations of the impacts of urban systems on the atmospheric environment. These limitations are largely due to limited field data available for testing and development of these models. We will deploy the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s first Mobile Facility (AMF1) to the mid-Atlantic region surrounding the city of Baltimore for the Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE). This deployment will create a four-node regional atmospheric observatory network including Baltimore and its three primary surrounding environments – rural, urban, and bay. CoURAGE investigators will study the interactions among the Earth’s surface, the atmospheric boundary layer, aerosols and atmospheric composition, clouds, radiation, and precipitation at each site, and examine how the spatial gradients across the region interact to create the climate conditions in Baltimore. This study will determine the degree to which Baltimore’s atmospheric environment depends on interactive feedbacks in the atmospheric system and the degree to which conditions in Baltimore depend on the surrounding environment. Some topics of interest include how urban land management exacerbates heat waves, the impact of regional mesoscale winds (nocturnal jet, bay breeze) on urban air pollution and cloud cover, and the impact of the urban heat island and aerosol production on heavy precipitation events. Understanding this integrated coast-urban-rural system quantitatively and with good accuracy and precision is critical to informing climate adaptation and mitigation efforts in the city of Baltimore. The understanding gained should be applicable to many similar coastal, mid-latitude urban centers. Another important objective of CoURAGE is to improve the representation of the climate of coastal cities in Earth systems models (ESMs). CoURAGE investigators will use the observations to test current ESMs, identify weaknesses and work towards improved simulations of this complex environment. The ARM core facility will be deployed in the city of Baltimore, complementing the Baltimore Social-Environmental Collaborative (BSEC), a DOE urban integrated field laboratory (UIFL). Ancillary sites will be deployed to rural Maryland northwest of Baltimore, and to the southern end of Kent Island within Chesapeake Bay. The fourth node will be a long-term atmospheric observatory operated in Beltsville, Maryland by Howard University and the Maryland Department of the Environment. Measurements will be conducted for one year, starting in December of 2024. There will be two intensive operational periods (IOPs), one in summer and one in winter, when the ancillary sites will be enhanced with additional balloon launches, tethered balloon system (TBS) operation, and added atmospheric composition measurements.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Lidar - ESRL WindCube 200s, Wasco Airport - Reviewed Data

The available "Readme" file introduces the basics of the Doppler lidar data and offers a detailed description of the variables present in the data files. For those with any further questions about the data and its interpretation, contact either Alan Brewer ( ) or Sunil Baidar ( ). It is highly recommended to discuss any planned use of the data with National Oceanic and Atmospheric Administration-Chemical Sciences Division (NOAA-CSD) scientists. For more information, refer to the Readme file: "noaa-esrl-wascolidar-readme-1.pdf."

17 WIND ENERGY↗

DOE OSTI2023

Lidar - ESRL WindCube 200s, Arlington Airport - Reviewed Data

The available "readme" file introduces the basics of the Doppler lidar data and offers a detailed description of the variables present in the data files. For those with any further questions about the data and its interpretation, contact either Alan Brewer ( ) or Sunil Baidar ( ). It is highly recommended to discuss any planned use of the data with National Oceanic and Atmospheric Administration-Chemical Sciences Division (NOAA-CSD) scientists. For more information, refer to the Readme file: "noaa-esrl-arlingtonlidar-readme-1.pdf."

17 WIND ENERGY↗

DOE OSTI2023

Using optimal estimation to retrieve winds from velocity-azimuth display (VAD) scans by a Doppler lidar

Abstract. Low-powered commercially available coherent Doppler lidar (CDL) wind profilers provide continuous measurement of vertical profiles of wind in the lower troposphere, usually close to or up to the top of the planetary boundary layer. The vertical extent of these wind profiles is limited by the availability of scatterers and thus varies substantially throughout the day and from one day to the next. This makes it challenging to develop continuous products that rely on CDL-observed wind profiles. In order to overcome this problem, we have developed a new method for wind profile retrievals from CDL that combines the traditional velocity-azimuth display (VAD) technique with optimal estimation (OE) to provide continuous wind profiles up to 3 km. The new method exploits the level-to-level covariance present in the wind profile to fill in the gaps where the signal-to-noise ratio of the CDL return is too low to provide reliable results using the traditional VAD method. Another advantage of the new method is that it provides the full error covariance matrix of the solution and profiles of information content, which more easily facilitates the assimilation of the observed wind profiles into numerical weather prediction models. This method was tested using yearlong CDL measurements at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility in 2019. Comparison with the ARM operational CDL wind profile product and collocated radiosonde wind measurements shows excellent agreement (R2>0.99) with no degradation in results where the traditional VAD provided a valid solution. In the region where traditional VAD does not provide results, the OE wind speed and wind vector have uncertainties of 3.44 and 4.33 m s−1, respectively. As a result, the new method provides additional information over the standard technique and increases the effective range of existing CDL systems without the need for additional hardware.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Model Evaluation by Measurements from Collocated Remote Sensors in Complex Terrain

Model improvement efforts involve an evaluation of changes in model skill in response to changes in model physics and parameterization. When using wind measurements from various remote sensors to determine model forecast accuracy, it is important to understand the effects of measurement-uncertainty differences among the sensors resulting from differences in the methods of measurement, the vertical and temporal resolution of the measurements, and the spatial variability of these differences. Here we quantify instrument measurement variability in 80-m wind speed during WFIP2 and its impact on the calculated errors and the change in error from one model version to another. Here the model versions tested involved updates in model physics from HRRRv1 to HRRRv4, and reductions in grid interval from 3 km to 750 m. Model errors were found to be 2–3 m s –1 . Differences in errors as determined by various instruments at each site amounted to about 10% of this value, or 0.2–0.3 m s –1 . Changes in model skill due to physics or grid-resolution updates also differed depending on the instrument used to determine the errors; most of the instrument-to-instrument differences were ~0.1 m s –1 , but some reached 0.3 m s –1 . All instruments at a given site mostly showed consistency in the sign of the change in error. In two examples, though, the sign changed, illustrating a consequence of differences in measurements: errors determined using one instrument may show improvement in model skill, whereas errors determined using another instrument may indicate degradation. This possibility underscores the importance of having accurate measurements to determine the model error.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Lidar - ESRL WindCube 200s, Wasco Airport - Processed Data

17 WIND ENERGY↗

DOE OSTI2021

Lidar - ESRL WindCube 200s, Arlington Airport - Processed Data

The available "readme" file introduces the basics of the Doppler lidar data and offers a detailed description of the variables present in the data files. If you have any further questions about the data and its interpretation, contact either Alan Brewer ( ) or Sunil Baidar ( ). It is highly recommended to discuss any planned use of the data with NOAA-CSD scientists. For more information, refer to the attached readme.

17 WIND ENERGY↗

DOE OSTI2020

Evaluating the WFIP2 updates to the HRRR model using scanning Doppler lidar measurements in the complex terrain of the Columbia River Basin

The wind-energy (WE) industry relies on numerical weather prediction (NWP) forecast models as foundational or base models for many purposes, including wind-resource assessment and wind-power forecasting. During the Second Wind Forecast Improvement Project (WFIP2) in the Columbia River Basin of Oregon and Washington, a significant effort was made to improve NWP forecasts through focused model development, to include experimental refinements to the High Resolution Rapid Refresh (HRRR) model physics and horizontal grid spacing. In this study, the performance of an experimental version of HRRR that includes these refinements is tested against a control version, which corresponds to that of the operational HRRR run by National Oceanic and Atmospheric Administration/National Centers for Environmental Protection at the outset of WFIP2. Furthermore, the effects of horizontal grid resolution were also tested by comparing wind forecasts from the HRRR (with 3-km grid spacing) with those from a finer-resolution HRRR nest with 750-m grid spacing. Model forecasts are validated against accurate wind-profile measurements by three scanning, pulsed Doppler lidars at sites separated by a total distance of 71 km. Model skill and improvements in model skill, attributable to physics refinements and improved horizontal grid resolution, varied by season, by site, and during periods of atmospheric phenomena relevant to WE. In general, model errors were the largest below 150 m above ground level (AGL). Experimental HRRR refinements tended to reduce the mean absolute error (MAE) and other error metrics for many conditions, but degradation in skill (increased MAE) was noted below 150 m AGL at the two lowest-elevation sites at night. Finer resolution was found to produce the most significant reductions in the error metrics.

17 WIND ENERGY↗

DOE OSTI2020

Characterizing NWP Model Errors Using Doppler-Lidar Measurements of Recurrent Regional Diurnal Flows: Marine-Air Intrusions into the Columbia-River Basin

Ground-based Doppler-lidar instrumentation provides atmospheric wind data at dramatically improved accuracies and spatial/temporal resolutions. These capabilities have provided new insights into atmospheric flow phenomena, but they also should have a strong role in NWP model improvement. Insight into the nature of model errors can be gained by studying recurrent atmospheric flows, here a regional summertime diurnal sea breeze and subsequent marine-air intrusion into the arid interior of Oregon-Washington, where these winds are an important windenergy resource. These marine intrusions were sampled by three scanning Doppler lidars in the Columbia-River Basin as part of the Second Wind Forecast Improvement Project (WFIP2), using data from summer 2016. Lidar time-height cross sections of wind speed identified eight days when the diurnal-flow cycle, (peak wind speeds at midnight, afternoon minima) was obvious and strong. Eight-day composite time-height cross sections of lidar wind speeds are used to validate those generated by the operational NCEP-HRRR model. HRRR simulated the diurnal wind cycle, but produced errors in the timing of onset and significant errors due to a premature nighttime demise of the intrusion flow, producing low-bias errors of 6 m s-1 . Day-to-day and in the composite, whenever a marine intrusion occurred, HRRR made these same errors. The errors occurred under a range of gradient wind conditions indicating that they resulted from the misrepresentation of physical processes within a limited region around the measurement locations. Because of their generation within a limited geographical area, field-measurement programs can be designed to find and address the sources of these NWP errors.

Banta, Robert M.↗

NASA NTRS2017

BrO and Inferred Bry Profiles over the Western Pacific: Relevance of Inorganic Bromine Sources and a Bry Minimum in the Aged Tropical Tropopause Layer

We report measurements of bromine monoxide (BrO) and use an observationally constrained chemical box model to infer total gas-phase inorganic bromine (Br(sub y)) over the tropical western Pacific Ocean (tWPO) during the CONTRAST field campaign (January-February 2014). The observed BrO and inferred Bry profiles peak in the marine boundary layer (MBL), suggesting the need for a bromine source from sea-salt aerosol (SSA), in addition to organic bromine (CBry ). Both profiles are found to be C-shaped with local maxima in the upper free troposphere (FT). The median tropospheric BrO vertical column density (VCD) was measured as 1.6 x 10(exp 13) molec cm(exp -2), compared to model predictions of 0.9 x 10(exp 13) molec cm(exp -2) in GEOS-Chem (CBr(sub y) but no SSA source), 0.4 x 10(exp 13) molec cm(exp -2) in CAM-Chem (CBr(sub y) and SSA), and 2.1 x 10(exp 13) molec cm(exp -2) in GEOS-Chem (CBry and SSA). Neither global model fully captures the Cshape of the Br(sun y) profile. A local Br(sub y) maximum of 3.6 ppt (2.9-4.4 ppt; 95% confidence interval, CI) is inferred between 9.5 and 13.5 km in air masses influenced by recent convective outflow. Unlike BrO, which increases from the convective tropical tropopause layer (TTL) to the aged TTL, gas-phase Br(sub y) decreases from the convective TTL to the aged TTL. Analysis of gas-phase Br(sub y) against multiple tracers (CFC-11, H2O/O3 ratio, and potential temperature) reveals a Br(sub y) minimum of 2.7 ppt (2.3-3.1 ppt; 95% CI) in the aged TTL, which agrees closely with a stratospheric injection of 2.6 +/- 0.6 ppt of inorganic Br(sub y) (estimated from CFC-11 correlations), and is remarkably insensitive to assumptions about heterogeneous chemistry. Bry increases to 6.3 ppt (5.6-7.0 ppt; 95% CI) in the stratospheric "middleworld" and 6.9 ppt (6.5-7.3 ppt; 95% CI) in the stratospheric "overworld". The local Br(sub y) minimum in the aged TTL is qualitatively (but not quantitatively) captured by CAM-Chem, and suggests a more complex partitioning of gas-phase and aerosol Br(sub y) species than previously recognized. Our data provide corroborating evidence that inorganic bromine sources (e.g., SSA-derived gas-phase Br(sub y) ) are needed to explain the gas-phase Br(sub y) budget in the upper free troposphere and TTL. They are also consistent with observations of significant bromide in Upper Troposphere-Lower Stratosphere aerosols. The total Br(sub y) budget in the TTL is currently not closed, because of the lack of concurrent quantitative measurements of gas-phase Br(sub y) species (i.e., BrO, HOBr, HBr, etc.) and aerosol bromide. Such simultaneous measurements are needed to (1) quantify SSA-derived Br(sub y) in the upper FT, (2) test Br(sub y) partitioning, and possibly explain the gas-phase Br(sub y) minimum in the aged TTL, (3) constrain heterogeneous reaction rates of bromine, and (4) account for all of the sources of Br(sub y) to the lower stratosphere.

Atmospheric Chemistry; bromine; troposphere; CONTR↗

NASA NTRS2015

Active and Widespread Halogen Chemistry in the Tropical and Subtropical Free Troposphere

Halogens in the troposphere are increasingly recognized as playing an important role for atmospheric chemistry, and possibly climate. Bromine and iodine react catalytically to destroy ozone (O3), oxidize mercury, and modify oxidative capacity that is relevant for the lifetime of greenhouse gases. Most of the tropospheric O3 and methane (CH4) loss occurs at tropical latitudes. Here we report simultaneous measurements of vertical profiles of bromine oxide (BrO) and iodine oxide (IO) in the tropical and subtropical free troposphere (10degN to 40degS), and show that these halogens are responsible for 34% of the column-integrated loss of tropospheric O3. The observed BrO concentrations increase strongly with altitude (approx.3.4 pptv at 13.5 km), and are 2-4 times higher than predicted in the tropical free troposphere. BrO resembles model predictions more closely in stratospheric air. The largest model low bias is observed in the lower tropical transition layer (TTL) over the tropical eastern Pacific Ocean, and may reflect a missing inorganic bromine source supplying an additional 2.5-6.4 pptv total inorganic bromine (Bry), or model overestimated Bry wet scavenging. Our results highlight the importance of heterogeneous chemistry on ice clouds, and imply an additional Bry source from the debromination of sea salt residue in the lower TTL. The observed levels of bromine oxidize mercury up to 3.5 times faster than models predict, possibly increasing mercury deposition to the ocean. The halogen-catalyzed loss of tropospheric O3 needs to be considered when estimating past and future ozone radiative effects.

Wang, Siyuan↗

NASA NTRS2013

Airborne MAX-DOAS Measurements Over California: Testing the NASA OMI Tropospheric NO2 Product

Airborne Multi-AXis Differential Optical Absorption Spectroscopy (AMAX-DOAS) measurements of NO2 tropospheric vertical columns were performed over California for two months in summer 2010. The observations are compared to the NASA Ozone Monitoring Instrument (OMI) tropospheric vertical columns (data product v2.1) in two ways: (1) Median data were compared for the whole time period for selected boxes, and the agreement was found to be fair (R = 0.97, slope = 1.4 +/- 0.1, N= 10). (2) A comparison was performed on the mean of coincident AMAX-DOAS measurements within the area of the corresponding OMI pixels with the tropospheric NASA OMI NO2 assigned to that pixel. The effects of different data filters were assessed. Excellent agreement and a strong correlation (R = 0.85, slope = 1.05 +/- 0.09, N= 56) was found for (2) when the data were filtered to eliminate large pixels near the edge of the OMI orbit, the cloud radiance fraction was<50%, the OMI overpass occurred within 2 h of the AMAX-DOAS measurements, the flight altitude was>2 km, and a representative sample of the footprint was taken by the AMAX-DOAS instrument. The AMAX-DOAS and OMI data sets both show a reduction of NO2 tropospheric columns on weekends by 38 +/- 24% and 33 +/- 11%, respectively. The assumptions in the tropospheric satellite air mass factor simulations were tested using independent measurements of surface albedo, aerosol extinction, and NO2 profiles for Los Angeles for July 2010 indicating an uncertainty of 12%.

remote sensing↗