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Evaluation of Reanalysis Temperature and Humidity Profiles for Producing Surface Radiative Flux Climate Record
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An Algorithm to Derive Temperature and Humidity Profile Changes Using Spatially and Temporally Averaged Spectral Radiance Differences
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Reconstructing the vertical profile of humidity on the basis of the vertical profile of temperature
The vertical profile of humidity in the atmosphere is developed on the basis of the vertical profile of temperature using an empirical formula linking changes in humidity with changes in temperature and altitude. The atmosphere is divided into three layers by altitude, since the condition for the formation of humidity varies with altitude.
Using Dual-Regression to Produce 16-Day Average AIRS Soundings
Temperature and humidity profiles are needed to estimate surface radiation budget. The Clouds and the Earth’s Radiant Energy System (CERES) team uses temperature and humidity profiles from a reanalysis product produced by NASA’s Global Modeling and Assimilation Office for surface irradiance computations. Biases and drifts in temperature and humidity profiles in the reanalysis product result in biases and drifts in surface irradiances computed with them. One approach to correct biases and drifts in temperature and humidity profile is to use satellite observations, similar to assimilating instantaneous spectral radiances to correct modeled temperature and humidity profiles. In this work, we use mean spectral radiances to test the possibility of understanding biases in reanalysis mean temperature and humidity profiles. Specifically, we use 16-day mean Atmospheric Infrared Sounder (AIRS) radiances and only use clear-sky spectral radiances with a viewing zenith angle nadir to near-nadir. We use the dual-regression method (Smith et al. 2012) to test whether temperature and humidity profiles retrieved from the 16-day mean spectral radiances agree with the average of temperature and humidity profiles derived from instantaneous spectral radiances. When daytime and nighttime spectral radiances are averaged separately and daytime and nighttime retrievals are performed separately, temperature and humidity profiles derived from the mean spectral radiances agree well with mean temperature and humidity profiles derived from instantaneous spectral radiances. The agreement improves when clouds are further screened to compute 16-day mean clear-sky spectral radiances.
Millimeter-Wave Imaging Radiometer (MIR) Data Processing and Development of Water Vapor Retrieval Algorithms
This document describes the final report of the Millimeter-wave Imaging Radiometer (MIR) Data Processing and Development of Water Vapor Retrieval Algorithms. Volumes of radiometric data have been collected using airborne MIR measurements during a series of field experiments since May 1992. Calibrated brightness temperature data in MIR channels are now available for studies of various hydrological parameters of the atmosphere and Earth's surface. Water vapor retrieval algorithms using multichannel MIR data input are developed for the profiling of atmospheric humidity. The retrieval algorithms are also extended to do three-dimensional mapping of moisture field using continuous observation provided by airborne sensor MIR or spaceborne sensor SSM/T-2. Validation studies for water vapor retrieval are carried out through the intercomparison of collocated and concurrent measurements using different instruments including lidars and radiosondes. The developed MIR water vapor retrieval algorithm is capable of humidity profiling under meteorological conditions ranging from clear column to moderately cloudy sky. Simulative water vapor retrieval studies using extended microwave channels near 183 and 557 GHz strong absorption lines indicate feasibility of humidity profiling to layers in the upper troposphere and improve the overall vertical resolution through the atmosphere.
Development of Mission Profiles for Humidity Models in the Reliability Testing of PV Inverters: Preprint
To understand the impacts of humidity on PV inverters, mission profiles were developed to accurately describe the different processes and rates based on the environmental factors of temperature, relative humidity, and irradiance. The operating environment of the device introduces stress factors dependent on component temperature, relative humidity, and component voltage. The development of profiles started from looking at historical climate conditions at Cocoa, Florida, a hot and humid location. The profile developed from field location was compared with existing humidity test profiles in industrial and military standards to determine acceleration factors. Prior to the evaluation of the mission profiles, critical components in the PV inverter were identified based on vendor discussions along with failure modes of interest. The profiles considered in this study was demonstrated using a 4-kVA string inverter. The measurements from the devices were substituted in device manufacturer specified equation to determine the severity of each test. The severity of each test was compared against the severity of the 24-hour result to determine the acceleration factor of each test. The acceleration factors were determined to be over a range of 1.2-6 for the existing humidity tests from standards, when compared against the mission profile developed from field data. This optimal humidity/thermal profile will be passed to the IEC standards development for inverter qualification testing.
Numerical simulation of advection fog formation on multi-disperse aerosols due to combustion-related pollutants
The effects of multi-disperse distribution of the aerosol population are presented. Single component and multi-component aerosol species on the condensation/nucleation processes which affect the reduction in visibility are described. The aerosol population with a high particle concentration provided more favorable conditions for the formation of a denser fog than the aerosol population with a greater particle size distribution when the value of the mass concentration of the aerosols was kept constant. The results were used as numerical predictions of fog formation. Two dimensional observations in horizontal and vertical coordinates, together with time-dependent measurements were needed as initial values for the following physical parameters: (1)wind profiles; (2) temperature profiles; (3) humidity profiles; (4) mass concentration of aerosol particles; (5) particle size distribution of aerosols; and (6) chemical composition of aerosols. Formation and dissipation of advection fog, thus, can be forecasted numerically by introducing initial values obtained from the observations.
Recent Developments and Applications of Quantum Well Infrared Photodetector Focal Plane Arrays
There are many applications that require long wavelength, large, uniform, reproducible, low cost, stable, and radiation-hard infrared (IR) focal plane arrays (FPAs). For example, the absorption lines of many gas molecules, such as ozone, water, carbon monoxide, carbon dioxide, and nitrous oxide occur in the wavelength region from 3 to 18 micron. Thus, IR imaging systems that operate in the long wavelength IR (LWIR) region (6 - 18 micron) are required in many space borne applications such as monitoring the global atmospheric temperature profiles, relative humidity profiles, cloud characteristics, and the distribution of minor constituents in the atmosphere which are being planned for future NASA Earth and planetary remote sensing systems. Due to higher radiation hardness, lower 1/f noise, and larger array size the GaAs based Quantum Well Infrared Photodetector (QWIP) FPAs are very attractive for such space borne applications compared to intrinsic narrow band gap detector arrays. In this presentation we will discuss the optimization of the detector design, material growth and processing that has culminated in realization of large format long-wavelength QWIP FPAs, portable and miniature LWIR cameras, holding forth great promise for myriad applications in 6-18 micron wavelength range in science, medicine, defense and industry. In addition, we will present some system demonstrations using broadband, two-color, and high quantum efficiency long-wavelength QWIP FPAs.
Spatial and Temporal Inter-Relationships Between Anomalies of Temperature, Moisture, Cloud Cover, and OLR as Observed by AIRS/AMSU on Aqua
AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU include surface skin temperature and atmospheric temperature profiles; atmospheric humidity profiles, percent cloud cover and cloud top pressure, and OLR. Near real time products, stating with September 2002, have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. Results in this paper included products through April 2008. The time period studied is marked by a substantial warming trend of Northern Hemisphere Extropical land surface skin temperatures, as well as pronounced El Nino - La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear Sky and All Sky OLR The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, are shown below, with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. The ability to match this data represents a good test of a model's response to El Nino.
Spatial and Temporal Inter-Relationship between Anomalies and Trends of Temperature, Moisture, Cloud Cover and OLR as Observed by AIRS/AMSU on Aqua
AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU by the AIRS Science Team include surface skin temperature and atmospheric temperature profiled; atmospheric humidity profiles, fractional cloud clover and cloud top pressure, and OLR. Products covering the period September 2002 through the present have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. In this paper, we will show results covering the time period September 2006 - November 2008. This time period is marked by a substantial warming trend of Northern Hemisphere Extra-tropical land surface skin temperatures, as well as pronounced El Nino - La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear Sky and All Sky OLR. The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, will be shown with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. Results will also be shown to evaluate the anomalies and trends of temperature profiles and OLR as determined from analysis of AIRS/AMSU data. Global and regional trends during the 6 1/3 year time period are not necessarily indicative of what has happened in the past, or what may happen in the future. Nevertheless, the inter-relationships of spatial and temporal anomalies of atmospheric geophysical parameters with those of surface skin temperature are indicative of climate processes, and can be used to test the performance of climate models when driven by changes in surface temperatures.
Spatial and Temporal Inter-Relationships between Anomalies and Trends of Temperature, Moisture, Cloud Cover, and OLR as Observed by AIRS/AMSU on Aqua
AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU by the AIRS Science Team include surface skin temperature and atmospheric temperature profiles; atmospheric humidity profiles, fractional cloud cover and cloud top pressure, and OLR. Products covering the period September 2002 through the present have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. In this paper, we will show results covering the time period September 2006 - November 2008. This time period is marked by a substantial warming trend of Northern Hemisphere Extratropical land surface skin temperatures, as well as pronounced El Nino - La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear sky and All Sky OLR. The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, will be shown, with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. Results will also be shown to validate the anomalies and trends of temperature profiles and OLR as determined from analysis of AIRS/AMSU data. Global and regional trends during the 6 1/3 year period are not necessarily indicative of what has happened in the past, or what may happen in the future. Nevertheless, the inter-relationships of spatial and temporal anomalies of atmospheric geophysical parameters with those of surface skin temperature are indicative of climate processes, and can be used to test the performance of climate models when driven by changes in surface temperatures.
Low Noise Amplifiers and Receivers for Remote Sensing
The study of atmospheric dynamics and climatology depend on accurate and frequent measurements of temperature and humidity profiles of the atmosphere. These measurements furthermore enable highly accurate measurements of ocean topography by providing total column water vapour data for radar path delay correction. The atmospheric temperature profile is characterized at the oxygen molecule absorption frequencies (60 and 118 GHz) and the humidity profile at the water molecule absorption frequencies (23 and 183 GHz). Total column measurements can be achieved by comparing measured radiometric temperatures at atmospheric window channels, such as 90, 130, and 166 GHz. The standard receiver technology for these frequencies was diode mixers with MMIC LNAs being applied at the lower frequencies. The sensitivity of millimeter wave receivers improved significantly with the introduction of the low noise 35 nm gate length InP MMIC amplifiers. We currently achieve 3 dB noise figure at 180 GHz and 2 dB noise figure at 90 GHz with our MMIC low noise amplifiers (LNAs) in room temperature. These amplifiers and the receivers we have built using them made it possible to conduct highly accurate airborne measurements campaigns from the Global Hawk unmanned aerial vehicle, develop millimeter wave internally calibrated radiometers for altimeter radar path delay correction, and build prototypes of large arrays of millimeter receivers for a geostationary interferometric sounder. We use the developed millimeter wave receivers to measure temperature and humidity profiles in the atmosphere and in hurricanes as well as to characterize the path delay error in ocean topography alitmetery.
Low Noise Amplifiers and Receivers for Remote Sensing
The study of atmospheric dynamics and climatology depend on accurate and frequent measurements of temperature and humidity profiles of the atmosphere. These measurements furthermore enable highly accurate measurements of ocean topography by providing total column water vapour data for radar path delay correction. The atmospheric temperature profile is characterised at the oxygen molecule absorption frequencies (60 and 118 GHz) and the humidity profile at the water molecule absorption frequencies (23 and 183 GHz). Total column measurements can be achieved by comparing measured radiometric temperatures at atmospheric window channels, such as 90, 130 and 166 GHz. The standard receiver technology for these frequencies was diode mixers with MMIC LNAs being applied at the lower frequencies. The sensitivity of millimetre wave receivers improved significantly with the introduction of the low noise 35 nm gate length InP MMIC amplifiers. We currently achieve 3 dB noise figure at 180 GHz and 2 dB noise figure at 90 GHz with our MMIC low noise amplifiers (LNAs) in room temperature. These amplifiers and the receivers we have built using them made it possible to conduct highly accurate airborne measurement campaigns from the Global Hawk unmanned aerial vehicle, develop millimeter wave internally calibrated radiometers for altimeter radar path delay correction, and build prototypes of large arrays of millimeter receivers for a geostationary interferometric sounder. We use the developed millimeter wave receivers to measure temperature and humidity profiles in the atmosphere and in hurricanes as well as to characterize the path delay error in ocean topography altimetry.
Atmospheric parameterization schemes for satellite cloud property retrieval during FIRE IFO 2
Satellite cloud retrieval algorithms generally require atmospheric temperature and humidity profiles to determine such cloud properties as pressure and height. For instance, the CO2 slicing technique called the ratio method requires the calculation of theoretical upwelling radiances both at the surface and a prescribed number (40) of atmospheric levels. This technique has been applied to data from, for example, the High Resolution Infrared Radiometer Sounder (HIRS/2, henceforth HIRS) flown aboard the NOAA series of polar orbiting satellites and the High Resolution Interferometer Sounder (HIS). In this particular study, four NOAA-11 HIRS channels in the 15-micron region are used. The ratio method may be applied to various channel combinations to estimate cloud top heights using channels in the 15-mu m region. Presently, the multispectral, multiresolution (MSMR) scheme uses 4 HIRS channel combination estimates for mid- to high-level cloud pressure retrieval and Advanced Very High Resolution Radiometer (AVHRR) data for low-level (is greater than 700 mb) cloud level retrieval. In order to determine theoretical upwelling radiances, atmospheric temperature and water vapor profiles must be provided as well as profiles of other radiatively important gas absorber constituents such as CO2, O3, and CH4. The assumed temperature and humidity profiles have a large effect on transmittance and radiance profiles, which in turn are used with HIRS data to calculate cloud pressure, and thus cloud height and temperature. For large spatial scale satellite data analysis, atmospheric parameterization schemes for cloud retrieval algorithms are usually based on a gridded product such as that provided by the European Center for Medium Range Weather Forecasting (ECMWF) or the National Meteorological Center (NMC). These global, gridded products prescribe temperature and humidity profiles for a limited number of pressure levels (up to 14) in a vertical atmospheric column. The FIRE IFO 2 experiment provides an opportunity to investigate current atmospheric profile parameterization schemes, compare satellite cloud height results using both gridded products (ECMWF) and high vertical resolution sonde data from the National Weather Service (NWS) and Cross Chain Loran Atmospheric Sounding System (CLASS), and suggest modifications in atmospheric parameterization schemes based on these results.
Simultaneous Observations of Surface Layer Profiles of Humidity, Temperature, and Wind Using Scanning Lidar Instruments
We demonstrate the combination of three Doppler lidars (DLs), a water vapor differential absorption lidar and a temperature rotational Raman lidar for the investigation of the interactions between the land-surface and the atmospheric boundary layer. This combination of scanning lidars was operated for the first time during the Land-Atmosphere Feedback Experiment at the Atmospheric Radiation Measurement program's Southern Great Plain site, Oklahoma, USA, in August 2017, and provided simultaneous surface layer profiles of horizontal wind, humidity and temperature. The horizontal wind profiles were determined using the dual-Doppler method with two DLs. The scans were performed above four towers providing atmospheric variables and fluxes. These combined lidar data allowed for the estimation of the friction velocity as well as the surface latent and sensible heat fluxes. For this purpose, profiles calculated with Monin-Obukhov similarity theory were fitted with the Levenberg-Marquardt nonlinear least squares curve-fitting method to the measured surface-layer lidar profiles. We present case studies of three 50-min periods to illustrate the new method. The measurements resulted in friction velocities of 0.31, 0.29, and 0.38 ms –1 , sensible surface heat fluxes of 312.1, 234.1, and 183.3 Wm –2 and latent surface heat fluxes of 251.8, 227.3, and 274.4 Wm –2 . These values were compared with the in-situ measurements of the towers. Considering the sampling differences and the error analyses, the results agree within 25.1%, 42.5%, and 28.8%, respectively, demonstrating that this synergy of scanning active remote sensing systems can be used to derive surface fluxes with reasonable accuracy.
Retrieval of total precipitable water using radiometric measurements near 183.3 GHz and 90 GHz frequencies
Data collected with the Advanced Microwave Moisture Sounder (AMMS), which operates in the 183.3 GHz range, are compared to measurements collected at 22 GHz in order to show that the 183 GHz measurements are more sensitive to total precipitable water (W) values than the 22 GHz measurements. Radiative transfer calculations for the upwelling microwave emission from the ocean surface were performed at the AMMS frequencies with a variety of atmospheric temperature and humidity profiles. The derived brightness temperatures at these frequencies are compared with W values derived from the humidity profiles. It is observed that the sensitivity between the brightness temperatures and W values at the AMMS channel is greater than 130 K/g per sq cm and 12 K/g per sq cm for the 22 GHz frequency.
Detail Enhancement of AIRS/AMSU Temperature and Moisture Profiles Using a 3D Deep Neural Network
In recent decades, spaceborne microwave and hyperspectral infrared sounding instruments have significantly benefited weather forecasting and climate science. However, existing retrievals of lower troposphere temperature and humidity profiles have limitations in vertical resolution, and often cannot accurately represent key features such as the mixed layer thermodynamic structure and the inversion at the planetary boundary layer (PBL) top. Because of the existing limitations in PBL remote sensing from space, there is a compelling need to improve routine, global observations of the PBL and enable advances in scientific understanding and weather and climate prediction. To address this, we have developed a new 3D deep neural network (DNN) which enhances detail and reduces noise in Level 2 granules of temperature and humidity profiles from the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) sounder instruments aboard NASA’s Aqua spacecraft. We show that the enhancement improves accuracy and detail including key features such as capping inversions at the top of the PBL over land, resulting in improved accuracy in estimations of PBL height.