The Experts below are selected from a list of 263859 Experts worldwide ranked by ideXlab platform
Fuzhong Weng - One of the best experts on this subject based on the ideXlab platform.
-
hurricane sandy warm core structure observed from Advanced Technology microwave sounder
Geophysical Research Letters, 2013Co-Authors: Tong Zhu, Fuzhong WengAbstract:[1] The warm-core structures of Hurricane Sandy and other nine tropical cyclones (TCs) are studied using the temperatures retrieved from Advanced Technology Microwave Sounder (ATMS). A new algorithm is developed for the retrieval of atmospheric temperature profiles from the ATMS radiances. Since ATMS observation has a higher spatial resolution and better coverage than its predecessor, Advanced Microwave Sounding Unit-A, the retrieved temperature field explicitly resolves TC warm core throughout troposphere and depicts the cold temperature anomalies in the eyewall and spiral rainbands. Unlike a typical TC, the height of maximum warm core of Hurricane Sandy is very low, but the storm size is quite large. Based on the analysis of 10 TCs in 2012, close correlations are found between ATMS-derived warm core and the TC maximum sustained wind (MSW) or minimum sea level pressure (MSLP). The estimation errors of MSW and MSLP from ATMS-retrieved warm core are 13.5 mph and 13.1 hPa, respectively.
-
Calibration of Suomi national polar-orbiting partnership Advanced Technology microwave sounder
Journal of Geophysical Research Atmospheres, 2013Co-Authors: Fuzhong Weng, Xiaolei Zou, Ninghai Sun, William J. Blackwell, Hu Yang, Miao Tian, Lin Lin, Xiang Wang, Kent AndersonAbstract:The Suomi National Polar-Orbiting Partnership (NPP) satellite was launched on 28 October 2011 and carries the Advanced Technology Microwave Sounder (ATMS) on board. ATMS is a cross-track scanning instrument observing in 22 channels at frequencies ranging from 23 to 183 GHz, permitting the measurements of the atmospheric temperature and moisture under most weather conditions. In this study, the ATMS radiometric calibration algorithm used in the operational system is first evaluated through independent analyses of prelaunch thermal vacuum data. It is found that the ATMS peak nonlinearity for all the channels is less than 0.5 K, which is well within the specification. For the characterization of the ATMS instrument sensitivity or noise equivalent differential temperatures (NEDT), both standard deviation and Allan variance of warm counts are computed and compared. It is shown that NEDT derived from the standard deviation is about three to five times larger than that from the Allan variance. The difference results from a nonstationary component in the standard deviation of warm counts. The Allan variance is better suited than the standard deviation for describing NEDT. In the ATMS sensor brightness temperature data record (SDR) processing algorithm, the antenna gain efficiencies of main beam, cross-polarization beam, and side lobes must be derived accurately from the antenna gain distribution function. However, uncertainties remain in computing the efficiencies at ATMS high frequencies. Thus, ATMS antenna brightness temperature data records (TDR) at channels 1 to 15 are converted to SDR with the actual beam efficiencies whereas those for channels 16 to 22 are only corrected for the near-field sidelobe contributions. The biases of ATMS SDR measurements to the simulations are consistent between GPS RO and NWP data and are generally less than 0.5 K for those temperature-sounding channels where both the forward model and input atmospheric profiles are reliable.
-
introduction to suomi national polar orbiting partnership Advanced Technology microwave sounder for numerical weather prediction and tropical cyclone applications
Journal of Geophysical Research, 2012Co-Authors: Fuzhong Weng, Xiaolei Zou, Xing Wang, Suying Yang, M D GoldbergAbstract:[1] The Suomi National Polar-orbiting Partnership (NPP) satellite was successfully launched on 28 October 2011. On board the Suomi NPP, the Advanced Technology Microwave Sounder (ATMS) is a cross-track scanning instrument and has 22 channels at frequencies ranging from 23 to 183 GHz which allows for probing the atmospheric temperature and moisture under clear and cloudy conditions. ATMS inherited most of the sounding channels from its predecessors: Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS) onboard NOAA and MetOp satellites. However, ATMS has a wider scan swath and has no gaps between two consecutive orbits. It includes one new temperature sounding channel and two water vapor sounding channels and provides more details of thermal structures in lower troposphere, especially for the storm conditions such as tropical cyclones. While ATMS temperature sounding channels have shorter integration time and therefore higher noise than AMSU-A, the ATMS observations from their overlapping field of views are resampled to produce AMSU-A-like measurements.
Xiaolei Zou - One of the best experts on this subject based on the ideXlab platform.
-
capturing size and intensity changes of hurricanes irma and maria 2017 from polar orbiting satellite microwave radiometers
Journal of the Atmospheric Sciences, 2018Co-Authors: Xiaoxu Tian, Xiaolei ZouAbstract:AbstractA recently refined hurricane warm-core retrieval algorithm was applied to data from multiple polar-orbiting satellites that carry the Advanced Technology Microwave Sounder (ATMS) and the Ad...
-
Calibration of Suomi national polar-orbiting partnership Advanced Technology microwave sounder
Journal of Geophysical Research Atmospheres, 2013Co-Authors: Fuzhong Weng, Xiaolei Zou, Ninghai Sun, William J. Blackwell, Hu Yang, Miao Tian, Lin Lin, Xiang Wang, Kent AndersonAbstract:The Suomi National Polar-Orbiting Partnership (NPP) satellite was launched on 28 October 2011 and carries the Advanced Technology Microwave Sounder (ATMS) on board. ATMS is a cross-track scanning instrument observing in 22 channels at frequencies ranging from 23 to 183 GHz, permitting the measurements of the atmospheric temperature and moisture under most weather conditions. In this study, the ATMS radiometric calibration algorithm used in the operational system is first evaluated through independent analyses of prelaunch thermal vacuum data. It is found that the ATMS peak nonlinearity for all the channels is less than 0.5 K, which is well within the specification. For the characterization of the ATMS instrument sensitivity or noise equivalent differential temperatures (NEDT), both standard deviation and Allan variance of warm counts are computed and compared. It is shown that NEDT derived from the standard deviation is about three to five times larger than that from the Allan variance. The difference results from a nonstationary component in the standard deviation of warm counts. The Allan variance is better suited than the standard deviation for describing NEDT. In the ATMS sensor brightness temperature data record (SDR) processing algorithm, the antenna gain efficiencies of main beam, cross-polarization beam, and side lobes must be derived accurately from the antenna gain distribution function. However, uncertainties remain in computing the efficiencies at ATMS high frequencies. Thus, ATMS antenna brightness temperature data records (TDR) at channels 1 to 15 are converted to SDR with the actual beam efficiencies whereas those for channels 16 to 22 are only corrected for the near-field sidelobe contributions. The biases of ATMS SDR measurements to the simulations are consistent between GPS RO and NWP data and are generally less than 0.5 K for those temperature-sounding channels where both the forward model and input atmospheric profiles are reliable.
-
introduction to suomi national polar orbiting partnership Advanced Technology microwave sounder for numerical weather prediction and tropical cyclone applications
Journal of Geophysical Research, 2012Co-Authors: Fuzhong Weng, Xiaolei Zou, Xing Wang, Suying Yang, M D GoldbergAbstract:[1] The Suomi National Polar-orbiting Partnership (NPP) satellite was successfully launched on 28 October 2011. On board the Suomi NPP, the Advanced Technology Microwave Sounder (ATMS) is a cross-track scanning instrument and has 22 channels at frequencies ranging from 23 to 183 GHz which allows for probing the atmospheric temperature and moisture under clear and cloudy conditions. ATMS inherited most of the sounding channels from its predecessors: Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS) onboard NOAA and MetOp satellites. However, ATMS has a wider scan swath and has no gaps between two consecutive orbits. It includes one new temperature sounding channel and two water vapor sounding channels and provides more details of thermal structures in lower troposphere, especially for the storm conditions such as tropical cyclones. While ATMS temperature sounding channels have shorter integration time and therefore higher noise than AMSU-A, the ATMS observations from their overlapping field of views are resampled to produce AMSU-A-like measurements.
M D Goldberg - One of the best experts on this subject based on the ideXlab platform.
-
introduction to suomi national polar orbiting partnership Advanced Technology microwave sounder for numerical weather prediction and tropical cyclone applications
Journal of Geophysical Research, 2012Co-Authors: Fuzhong Weng, Xiaolei Zou, Xing Wang, Suying Yang, M D GoldbergAbstract:[1] The Suomi National Polar-orbiting Partnership (NPP) satellite was successfully launched on 28 October 2011. On board the Suomi NPP, the Advanced Technology Microwave Sounder (ATMS) is a cross-track scanning instrument and has 22 channels at frequencies ranging from 23 to 183 GHz which allows for probing the atmospheric temperature and moisture under clear and cloudy conditions. ATMS inherited most of the sounding channels from its predecessors: Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS) onboard NOAA and MetOp satellites. However, ATMS has a wider scan swath and has no gaps between two consecutive orbits. It includes one new temperature sounding channel and two water vapor sounding channels and provides more details of thermal structures in lower troposphere, especially for the storm conditions such as tropical cyclones. While ATMS temperature sounding channels have shorter integration time and therefore higher noise than AMSU-A, the ATMS observations from their overlapping field of views are resampled to produce AMSU-A-like measurements.
Kent Anderson - One of the best experts on this subject based on the ideXlab platform.
-
Calibration of Suomi national polar-orbiting partnership Advanced Technology microwave sounder
Journal of Geophysical Research Atmospheres, 2013Co-Authors: Fuzhong Weng, Xiaolei Zou, Ninghai Sun, William J. Blackwell, Hu Yang, Miao Tian, Lin Lin, Xiang Wang, Kent AndersonAbstract:The Suomi National Polar-Orbiting Partnership (NPP) satellite was launched on 28 October 2011 and carries the Advanced Technology Microwave Sounder (ATMS) on board. ATMS is a cross-track scanning instrument observing in 22 channels at frequencies ranging from 23 to 183 GHz, permitting the measurements of the atmospheric temperature and moisture under most weather conditions. In this study, the ATMS radiometric calibration algorithm used in the operational system is first evaluated through independent analyses of prelaunch thermal vacuum data. It is found that the ATMS peak nonlinearity for all the channels is less than 0.5 K, which is well within the specification. For the characterization of the ATMS instrument sensitivity or noise equivalent differential temperatures (NEDT), both standard deviation and Allan variance of warm counts are computed and compared. It is shown that NEDT derived from the standard deviation is about three to five times larger than that from the Allan variance. The difference results from a nonstationary component in the standard deviation of warm counts. The Allan variance is better suited than the standard deviation for describing NEDT. In the ATMS sensor brightness temperature data record (SDR) processing algorithm, the antenna gain efficiencies of main beam, cross-polarization beam, and side lobes must be derived accurately from the antenna gain distribution function. However, uncertainties remain in computing the efficiencies at ATMS high frequencies. Thus, ATMS antenna brightness temperature data records (TDR) at channels 1 to 15 are converted to SDR with the actual beam efficiencies whereas those for channels 16 to 22 are only corrected for the near-field sidelobe contributions. The biases of ATMS SDR measurements to the simulations are consistent between GPS RO and NWP data and are generally less than 0.5 K for those temperature-sounding channels where both the forward model and input atmospheric profiles are reliable.
Jon P Christophersen - One of the best experts on this subject based on the ideXlab platform.
-
Advanced Technology development program for lithium ion batteries gen 2 performance evaluation final report
2006Co-Authors: Jon P Christophersen, Kevin L. Gering, Ira Bloom, Vincent Battaglia, Edward V. Thomas, G.l. Henriksen, David HowellAbstract:The Advanced Technology Development Program has completed performance testing of the second generation of lithium-ion cells (i.e., Gen 2 cells). The 18650-size Gen 2 cells, with a baseline and variant chemistry, were distributed over a matrix consisting of three states-of-charge (SOCs) (60, 80, and 100% SOC), four temperatures (25, 35, 45, and 55°C), and three life tests (calendar-, cycle-, and accelerated-life). The calendar- and accelerated-life cells were clamped at an open-circuit voltage corresponding to the designated SOC and were subjected to a once-per-day pulse profile. The cycle-life cells were continuously pulsed using a profile that was centered around 60% SOC. Life testing was interrupted every four weeks for reference performance tests (RPTs), which were used to quantify changes in cell degradation as a function of aging. The RPTs generally consisted of C1/1 and C1/25 static capacity tests, a low-current hybrid pulse power characterization test, and electrochemical impedance spectroscopy. The rate of cell degradation generally increased with increasing test temperature, and SOC. It was also usually slowest for the calendar-life cells and fastest for the accelerated-life cells. Detailed capacity-, power-, and impedance-based performance results are reported.
-
u s doe freedomcar and vehicle technologies Advanced Technology development program for lithium ion batteries gen 2 performance evaluation interim report
2003Co-Authors: Jon P Christophersen, Chet Motloch, Ira Bloom, Vincent Battaglia, Ganesan Nagasubramanian, Tien Q DuongAbstract:The Advanced Technology Development Program is currently evaluating the performance of the second generation of Lithium-ion cells (i.e., Gen 2 cells). The 18650-size Gen 2 cells consist of a baseline chemistry and one variant chemistry. These cells were distributed over a matrix consisting of three states-of-charge (SOC) (60, 80, and 100% SOC), four temperatures (25, 35, 45, and 55°C), and three life tests (calendar-, cycle-, and accelerated-life). The calendar-life cells are clamped at an opencircuit voltage corresponding to 60% SOC and undergo a once-per-day pulse profile. The cycle-life cells are continuously pulsed using a profile that is centered around 60% SOC. The accelerated-life cells are following the calendar-life test procedures, but using the cycle-life pulse profile. Life testing is interrupted every four weeks for reference performance tests (RPTs), which are used to quantify changes in capacity, resistance, and power. The RPTs consist of a C1/1 and C1/25 static capacity tests, a low-current hybrid pulse power characterization test, and electrochemical impedance spectroscopy at 60% SOC. Capacity-, power-, and electrochemical impedance spectroscopy-based performance results are reported.
-
calendar and cycle life studies of Advanced Technology development program generation 1 lithium ion batteries
Journal of Power Sources, 2002Co-Authors: R B Wright, Chet Motloch, Ira Bloom, Vincent Battaglia, Jon P Christophersen, Jeffrey R Belt, Chinh D Ho, S A Jones, Roger Allen Richardson, G.l. HenriksenAbstract:Abstract This paper presents the test results and life modeling of special calendar- and cycle-life tests conducted on 18650-size generation 1 (Gen 1) lithium-ion battery cells (nominal capacity of 0.9 Ah; 3.0–4.1 V rating) developed to establish a baseline chemistry and performance for the Department of Energy sponsored Advanced Technology development (ATD) program. Electrical performance testing was conducted at the Argonne National Laboratory (ANL), Sandia National Laboratory (SNL) and the Idaho National Engineering and Environmental Laboratory (INEEL). As part of the electrical performance testing, a new calendar-life test protocol was used. The test consisted of a once per day discharge and charge pulse designed to have minimal impact on the cell yet establish its performance over a period of time such that the calendar-life of the cell could be determined. The calendar-life test matrix included two states-of-charge (SOCs) (i.e. 60 and 80%) and four test temperatures (40, 50, 60 and 70 °C). Discharge and regen resistances were calculated from the test data. Results indicate that both the discharge and regen resistances increased non-linearly as a function of the test time. The magnitude of the resistances depended on the temperature and SOC at which the test was conducted. Both resistances had a non-linear increase with respect to time at test temperature. The discharge resistances are greater than the regen resistances at all of the test temperatures of 40, 50, 60 and 70 °C. For both the discharge and regen resistances, generally the higher the test temperature, the lower the resistance. The measured resistances were then used to develop an empirical model that was used to predict the calendar-life of the cells. This model accounted for the time, temperature and SOC of the batteries during the calendar-life test. The functional form of the model is given by: R(t,T,SOC)=A(T, SOC)F(t)+B(T, SOC), where t is the time at test temperature, T the test temperature and SOC the SOC of the cell at the start of the test. A(T, SOC) and B(T, SOC) are assumed to be functions of the temperature and SOC; F is assumed to only be a function of the time at test temperature. Using curve-fitting techniques for a number of time-dependent functions, it was found that both the discharge and regen resistances were best correlated with F(t) having a square-root of test time dependence. These results led to the relationship for the discharge and regen resistances: R(t,T,SOC)=A(T, SOC)t1/2+B(T, SOC). The square-root of time dependence can be accounted for by either a one-dimensional diffusion type of mechanism, presumably of the lithium-ions or by a parabolic growth mechanism for the growth of a thin-film solid electrolyte interface (SEI) layer on the anode and/or cathode. The temperature dependence of the resistance was then investigated using various model fits to the functions A(T, SOC) and B(T, SOC). The results of this exercise lead to a functional form for the temperature dependence of the fitting functions having an Arrhenius-like form: A(T,SOC)=a(SOC){exp[b(SOC)/T]} and B(T,SOC)=c(SOC){exp[d(SOC)/T]}, where a and c are constants, and b and d are related to activation energy (Eb and Ed) by using the gas constant (R) such that b=Eb/R and d=Ed/R. The functional form, therefore, for the discharge and regen resistances, including the SOC, is then: R(t,T,SOC)=a(SOC){exp[b(SOC)/T]}t1/2+c(SOC){exp[d(SOC)/T]}. The a, b, c and d parameters are explicitly shown as being functions of the SOC. However, due to the lack of testing at SOC values other than 60 and 80% SOC, the exact form of the SOC dependence could not be determined from the experimental data. The values of a, b, c and d were determined, thus permitting the function R(t, T, SOC) to be used to correlate the discharge and regen data and to predict what the resistances would be at different test times and temperatures. This paper also presents, discusses and models the results of a special cycle-life test conducted for a period of time at specified temperatures of 40, 50, 60 and 70 °C. This test, consisting of specified discharge and charge protocols, was designed to establish the cycle-life performance of the cells over a time interval such that their cycle-life could be determined. The cycle-life test was conducted at 60% SOC, with SOC swings of Δ3, Δ6 and Δ9%. During the cycle-life test, the discharge and regen resistances were determined after every 100 test cycles. The results of the cycle-life testing indicate that both the discharge and regen resistances increased non-linearly as a function of the test time at each Δ% SOC test. The magnitude of the resistances and the rate at which they changed depended on the temperature and Δ% SOC at which the test was conducted. Both resistances had a non-linear increase with respect to time at test temperature, i.e. as the number of test cycles increased the discharge and regen resistances increased also. For a given Δ% SOC test, the discharge resistances are greater than the regen resistances at all of the test temperatures of 40, 50, 60 and 70 °C. For both the discharge and regen resistances, generally the higher the test temperature, the lower the resistance. At each of the four test temperatures, the magnitude of the discharge and regen resistances was generally in the following order: Δ3% SOC>Δ9% SOC>Δ6% SOC, but the ordering was dependent on test time. A model was also developed to account for the time, temperature, SOC and Δ% SOC of the batteries during the cycle-life test. The functional form of the model is given by R (t,T, SOC , Δ % SOC )=A (T, SOC, Δ% SOC)F(t)+B(T, SOC, Δ% SOC) where t is the time at test temperature, T the test temperature, SOC the SOC of the cell at the start and end of the test and Δ% SOC the SOC swing during the test. A(T, SOC, Δ% SOC) and B(T, SOC, Δ% SOC) are assumed to be functions of the test temperature, SOC and Δ% SOC swing. F(t) is assumed to only be a function of the test time at test temperature. Using curve-fitting techniques for a number of time-dependent functions, it was found that both the discharge and regen resistances were best correlated by a square-root of test time dependence. These results led to the relationship for the discharge and regen resistances having the form R (t,T, SOC , Δ % SOC )=A (T, SOC, Δ% SOC)t1/2+B(T, SOC, Δ% SOC). This model is essentially the same as used to analyze the calendar-life test data. The temperature dependence of the resistance was then investigated using various model fits to the functions A(T) and B(T). The results of this exercise lead to a functional form for the functions having again an Arrhenius-like form: A(T)=a[exp(b/T)] and B(T)=c[exp(d/T)] where a and c are constants, and b and d are related to activation energies. The functional form, therefore, for the discharge and regen resistances including the SOC and Δ% SOC is R (t,T, SOC , Δ % SOC )=a (SOC, Δ% SOC){exp[b(SOC, Δ% SOC)/T]}t1/2+c(SOC, Δ% SOC){exp[d(SOC, Δ% SOC)/T]}. The a, b, c and d parameters are explicitly shown as being functions of the SOC and the Δ% SOC. However, due to the lack of testing at SOC values other than 60% SOC, the exact form of the SOC dependence could not be determined from the experimental data. In addition, no model was found that consistently correlated the observed resistance changes with the Δ% SOC of the tests. Eliminating the SOC and Δ% SOC from the resistance function, the function R(t, T) was then used to correlate the discharge and regen resistances data. This model also allows the prediction of what the resistances would be at different test times at a particular Δ% SOC test condition and temperature.
-
initial comparisons between the Advanced Technology development gen 2 baseline cells and variant c cells
40th Power Sources Conference Cherry Hill NJ 06 10 2002 06 13 2002, 2002Co-Authors: Jon P Christophersen, Chet Motloch, Ira Bloom, Vincent Battaglia, R B Wright, Timothy Collins Murphy, Jeffrey R Belt, Chinh D Ho, S A Jones, Rudy G JungstAbstract:The Advanced Technology Development Program is testing a second generation of lithium-ion cells, consisting of a baseline and three variant chemistries. The cathode composition of the Variant C chemistry was altered with an increase to the aluminum dopant and a decrease to the cobalt dopant to explore the impact on performance. However, it resulted in a 20% drop in rated capacity. Also, the Variant C average power fade is higher, but capacity fade is higher for the Baseline cell chemistry. Initial results indicate that the Variant C chemistry will reach end of life sooner than the Baseline chemistry.
