scholarly journals Characterization of the long-term radiosonde temperature biases in the upper troposphere and lower stratosphere using COSMIC and Metop-A/GRAS data from 2006 to 2014

2017 ◽  
Vol 17 (7) ◽  
pp. 4493-4511 ◽  
Author(s):  
Shu-peng Ho ◽  
Liang Peng ◽  
Holger Vömel
Keyword(s):  
Lower Stratosphere ◽  
Temperature Measurements ◽  
Climate Data ◽  
Upper Troposphere ◽  
Global Trend ◽  
The Mean ◽  
Temperature Climate

Abstract. Radiosonde observations (RAOBs) have provided the only long-term global in situ temperature measurements in the troposphere and lower stratosphere since 1958. In this study, we use consistently reprocessed Global Positioning System (GPS) radio occultation (RO) temperature data derived from the COSMIC and Metop-A/GRAS missions from 2006 to 2014 to characterize the inter-seasonal and interannual variability of temperature biases in the upper troposphere and lower stratosphere for different radiosonde sensor types. The results show that the temperature biases for different sensor types are mainly due to (i) uncorrected solar-zenith-angle-dependent errors and (ii) change of radiation correction. The mean radiosonde–RO global daytime temperature difference in the layer from 200 to 20 hPa for Vaisala RS92 is equal to 0.20 K. The corresponding difference is equal to −0.06 K for Sippican, 0.71 K for VIZ-B2, 0.66 K for Russian AVK-MRZ, and 0.18 K for Shanghai. The global daytime trend of differences for Vaisala RS92 and RO temperature at 50 hPa is equal to 0.07 K/5 yr. Although there still exist uncertainties for Vaisala RS92 temperature measurement over different geographical locations, the global trend of temperature differences between Vaisala RS92 and RO from June 2006 to April 2014 is within ±0.09 K/5 yr. Compared with Vaisala RS80, Vaisala RS90, and sondes from other manufacturers, the Vaisala RS92 seems to provide the most accurate RAOB temperature measurements, and these can potentially be used to construct long-term temperature climate data records (CDRs). Results from this study also demonstrate the feasibility of using RO data to correct RAOB temperature biases for different sensor types.

scholarly journals Characterization of the Long-term Radiosonde Temperature Biases in the Lower Stratosphere using COSMIC and Metop-A/GRAS Data from 2006 to 2014

2016 ◽  
Author(s):  
Shu-Peng Ho ◽  
Liang Peng ◽  
Holger Vömel
Keyword(s):  
Global Positioning System ◽  
Lower Stratosphere ◽  
Temperature Measurements ◽  
Global Trend ◽  
Global Positioning ◽  
The Mean ◽  
Geographical Locations

Abstract. Radiosonde observations (RAOBs) have provided the only long-term global in situ temperature measurements in the troposphere and lower stratosphere since 1958. In this study, we use consistently reprocessed Global Positioning System (GPS) radio occultation (RO) temperature data derived from COSMIC and Metop-A/GRAS missions from 2006 to 2014 to characterize the inter-seasonal and inter-annual variability of temperature biases in the lower stratosphere for different sensor types. The results show that the RAOB temperature biases for different RAOB sensor types are mainly owing to i) uncorrected solar zenith angle dependent errors, and ii) change of radiation correction. The mean daytime temperature difference (ΔT) for Vaisala RS92 is equal to 0.18 K in Australia, 0.20 K in Germany, 0.10 K in Canada, 0.13 K in England, and 0.33 K in Brazil. The mean daytime ΔT is equal to −0.06 K for Sippican, 0.71 K for VIZ-B2, 0.66 K for AVK-MRZ, and 0.18 K for Shanghai. The daytime trend of anomalies for Vaisala RS92 and RO temperature at 50 hPa is equal to 0.00 K/5 yrs over United States, −0.02 K/5 yrs over Germany, 0.17 K/5 yrs over Australia, 0.23 K/5 yrs over Canada, 0.26 K/5 yrs over England, and 0.12 K/5 yrs over Brazil, respectively. Although there still exist uncertainties for Vaisala RS92 temperature measurements over different geographical locations, the global trend of temperature anomaly between Vaisala RS92 and RO from June 2006 to April 2014 is within +/−0.09 K/5 yrs globally. Comparing with Vaisala RS80, Vaisala RS90 and sondes from other manufacturers, the Vaisala RS92 seems to provide the best RAOB temperature measurements, which can potentially be used to construct long term temperature CDRs. Results from this study also demonstrate the feasibility to use RO data to correct RAOB temperature biases for different sensor types.

scholarly journals Comparative study on long term climate data sources over South Korea

2018 ◽  
Vol 10 (3) ◽  
pp. 504-523 ◽  
Author(s):  
Dong-Ik Kim ◽  
Dawei Han
Keyword(s):  
South Korea ◽  
Climate Impact ◽  
Climate Data ◽  
The World ◽  
In Situ Observations ◽  
The Mean ◽  
Global Datasets ◽  
Different Parts

Abstract Long term climate data are vitally important in reliably assessing water resources and water related hazards, but in-situ observations are generally sparse in space and limited in time. Although there are several global datasets available as substitutes, there is a lack of comparative studies about their suitability in different parts of the world. In this study, to find out the reliable century-long climate dataset in South Korea, we first evaluate multi-decadal reanalyses (ERA-20 cm, ERA-20c, ERA-40 and NOAA 20th century reanalysis (20CR)) and gridded observations (CRUv3.23 and GPCCv7) for monthly mean precipitation and temperature. In the temporal and statistical comparisons, CRUv3.23 and GPCCv7 for precipitation and ERA-40 for temperature perform the best, and ERA-20c and 20CR also indicate meaningful agreements. For ERA-20 cm, it has only a statistical agreement, but the mean has the difficulty in representing its ensemble. This paper also shows that the applicability of each dataset may vary by region and all products should be locally adjusted before being applied in climate impact assessments. These findings not only help to fill in the knowledge gaps about these datasets in South Korea but also provide a useful guideline for the applicability of the global datasets in different parts of the world.

scholarly journals Investigation of dominant traveling 10-day wave components using long-term MERRA-2 database

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Chunming Huang ◽  
Wei Li ◽  
Shaodong Zhang ◽  
Gang Chen ◽  
Kaiming Huang ◽  
...  
Keyword(s):  
Flow Instability ◽  
Transmission Condition ◽  
Wave Number ◽  
Mean Flow ◽  
Excited Wave ◽  
Propagating Waves ◽  
Zonal Wave Number ◽  
The Mean

AbstractThe eastward- and westward-traveling 10-day waves with zonal wavenumbers up to 6 from surface to the middle mesosphere during the recent 12 years from 2007 to 2018 are deduced from MERRA-2 data. On the basis of climatology study, the westward-propagating wave with zonal wave number 1 (W1) and eastward-propagating waves with zonal wave numbers 1 (E1) and 2 (E2) are identified as the dominant traveling ones. They are all active at mid- and high-latitudes above the troposphere and display notable month-to-month variations. The W1 and E2 waves are strong in the NH from December to March and in the SH from June to October, respectively, while the E1 wave is active in the SH from August to October and also in the NH from December to February. Further case study on E1 and E2 waves shows that their latitude–altitude structures are dependent on the transmission condition of the background atmosphere. The presence of these two waves in the stratosphere and mesosphere might have originated from the downward-propagating wave excited in the mesosphere by the mean flow instability, the upward-propagating wave from the troposphere, and/or in situ excited wave in the stratosphere. The two eastward waves can exert strong zonal forcing on the mean flow in the stratosphere and mesosphere in specific periods. Compared with E2 wave, the dramatic forcing from the E1 waves is located in the poleward regions.

scholarly journals Aircraft measurements of gravity waves in the upper troposphere and lower stratosphere during the START08 field experiment

2015 ◽  
Vol 15 (13) ◽  
pp. 7667-7684 ◽  
Author(s):  
Fuqing Zhang ◽  
Junhong Wei ◽  
Meng Zhang ◽  
K. P. Bowman ◽  
L. L. Pan ◽  
...  
Keyword(s):  
Power Law ◽  
Gravity Waves ◽  
Lower Stratosphere ◽  
Potential Temperature ◽  
Shear Instability ◽  
Aircraft Measurements ◽  
Upper Troposphere ◽  
Airborne Measurements ◽  
Wide Range

Abstract. This study analyzes in situ airborne measurements from the 2008 Stratosphere–Troposphere Analyses of Regional Transport (START08) experiment to characterize gravity waves in the extratropical upper troposphere and lower stratosphere (ExUTLS). The focus is on the second research flight (RF02), which took place on 21–22 April 2008. This was the first airborne mission dedicated to probing gravity waves associated with strong upper-tropospheric jet–front systems. Based on spectral and wavelet analyses of the in situ observations, along with a diagnosis of the polarization relationships, clear signals of mesoscale variations with wavelengths ~ 50–500 km are found in almost every segment of the 8 h flight, which took place mostly in the lower stratosphere. The aircraft sampled a wide range of background conditions including the region near the jet core, the jet exit and over the Rocky Mountains with clear evidence of vertically propagating gravity waves of along-track wavelength between 100 and 120 km. The power spectra of the horizontal velocity components and potential temperature for the scale approximately between ~ 8 and ~ 256 km display an approximate −5/3 power law in agreement with past studies on aircraft measurements, while the fluctuations roll over to a −3 power law for the scale approximately between ~ 0.5 and ~ 8 km (except when this part of the spectrum is activated, as recorded clearly by one of the flight segments). However, at least part of the high-frequency signals with sampled periods of ~ 20–~ 60 s and wavelengths of ~ 5–~ 15 km might be due to intrinsic observational errors in the aircraft measurements, even though the possibilities that these fluctuations may be due to other physical phenomena (e.g., nonlinear dynamics, shear instability and/or turbulence) cannot be completely ruled out.

scholarly journals Two decades of in-situ temperature measurements in the upper troposphere and lowermost stratosphere from IAGOS long-term routine observation

2017 ◽  
Author(s):  
Florian Berkes ◽  
Patrick Neis ◽  
Martin G. Schultz ◽  
Ulrich Bundke ◽  
Susanne Rohs ◽  
...  
Keyword(s):  
Weather Forecast ◽  
Global Scale ◽  
Temperature Trend ◽  
Data Set ◽  
Medium Range Weather Forecast ◽  
Upper Troposphere ◽  
Temperature Trends ◽  
Geographical Regions

Abstract. Despite several studies on temperature trends in the tropopause region, a comprehensive understanding of the evolution of temperatures in this climate-sensitive region of the atmosphere remains elusive. Here we present a unique global-scale, long-term data set of high-resolution in-situ temperature data measured aboard passenger aircraft within the European Research Infrastructure IAGOS (In-service Aircraft for a Global Observing System, www.iagos.org). This data set is used to investigate temperature trends within the global upper troposphere and lowermost stratosphere (UTLS) for the period 1995 to 2012 in different geographical regions and vertical layers of the UTLS. The largest amount of observations is available over the North Atlantic. Here, a neutral temperature trend is found within the lowermost stratosphere. This contradicts the temperature trend in the European Centre for Medium Range Weather Forecast (ECMWF) ERA-Interim reanalysis, where a significant (95 % confidence) temperature increase of +0.56 K/decade is obtained. Differences between trends derived from observations and reanalysis data can be traced back to changes in the temperature bias between observation and model data over the studied period. This study demonstrates the value of the IAGOS temperature observations as anchor point for the evaluation of reanalyses and its suitability for independent trend analyses.

scholarly journals Creep Behavior of Passive Bovine Extraocular Muscle

2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
Author(s):  
Lawrence Yoo ◽  
Hansang Kim ◽  
Andrew Shin ◽  
Vijay Gupta ◽  
Joseph L. Demer
Keyword(s):  
Relaxation Function ◽  
Loading Rate ◽  
Creep Function ◽  
Testing Conditions ◽  
Loading Rates ◽  
Creep Coefficient ◽  
Wide Range ◽  
The Mean

This paper characterized bovine extraocular muscles (EOMs) using creep, which represents long-term stretching induced by a constant force. After preliminary optimization of testing conditions, 20 fresh EOM samples were subjected to four different loading rates of 1.67, 3.33, 8.33, and 16.67%/s, after which creep was observed for 1,500 s. A published quasilinear viscoelastic (QLV) relaxation function was transformed to a creep function that was compared with data. Repeatable creep was observed for each loading rate and was similar among all six anatomical EOMs. The mean creep coefficient after 1,500 seconds for a wide range of initial loading rates was at1.37±0.03(standard deviation, SD). The creep function derived from the relaxation-based QLV model agreed with observed creep to within 2.7% following 16.67%/s ramp loading. Measured creep agrees closely with a derived QLV model of EOM relaxation, validating a previous QLV model for characterization of EOM biomechanics.

scholarly journals Satellite-based time-series of sea-surface temperature since 1981 for climate applications

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Christopher J. Merchant ◽  
Owen Embury ◽  
Claire E. Bulgin ◽  
Thomas Block ◽  
Gary K. Corlett ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Ocean Model ◽  
Sea Surface ◽  
Climate Data ◽  
Satellite Measurements ◽  
Data Record ◽  
The Mean ◽  
Climate Data Record

Abstract A climate data record of global sea surface temperature (SST) spanning 1981–2016 has been developed from 4 × 1012 satellite measurements of thermal infra-red radiance. The spatial area represented by pixel SST estimates is between 1 km2 and 45 km2. The mean density of good-quality observations is 13 km−2 yr−1. SST uncertainty is evaluated per datum, the median uncertainty for pixel SSTs being 0.18 K. Multi-annual observational stability relative to drifting buoy measurements is within 0.003 K yr−1 of zero with high confidence, despite maximal independence from in situ SSTs over the latter two decades of the record. Data are provided at native resolution, gridded at 0.05° latitude-longitude resolution (individual sensors), and aggregated and gap-filled on a daily 0.05° grid. Skin SSTs, depth-adjusted SSTs de-aliased with respect to the diurnal cycle, and SST anomalies are provided. Target applications of the dataset include: climate and ocean model evaluation; quantification of marine change and variability (including marine heatwaves); climate and ocean-atmosphere processes; and specific applications in ocean ecology, oceanography and geophysics.

scholarly journals Pure rotational-Raman channels of the Esrange lidar for temperature and particle extinction measurements in the troposphere and lower stratosphere

2013 ◽  
Vol 6 (1) ◽  
pp. 91-98 ◽  
Author(s):  
P. Achtert ◽  
M. Khaplanov ◽  
F. Khosrawi ◽  
J. Gumbel
Keyword(s):  
Lower Stratosphere ◽  
Thermal Structure ◽  
Atmospheric Temperature ◽  
Temperature Measurements ◽  
Integration Time ◽  
Aerosol Extinction ◽  
Temperature Profiles ◽  
Backscatter Coefficient ◽  
Upper Troposphere ◽  
532 Nm

Abstract. The Department of Meteorology at Stockholm University operates the Esrange Rayleigh/Raman lidar at Esrange (68° N, 21° E) near the Swedish city of Kiruna. This paper describes the design and first measurements of the new pure rotational-Raman channel of the Esrange lidar. The Esrange lidar uses a pulsed Nd:YAG solid-state laser operating at 532 nm as light source with a repetition rate of 20 Hz and a pulse energy of 350 mJ. The minimum vertical resolution is 150 m and the integration time for one profile is 5000 shots. The newly implemented channel allows for measurements of atmospheric temperature at altitudes below 35 km and is currently optimized for temperature measurements between 180 and 200 K. This corresponds to conditions in the lower Arctic stratosphere during winter. In addition to the temperature measurements, the aerosol extinction coefficient and the aerosol backscatter coefficient at 532 nm can be measured independently. Our filter-based design minimizes the systematic error in the obtained temperature profile to less than 0.51 K. By combining rotational-Raman measurements (5–35 km height) and the integration technique (30–80 km height), the Esrange lidar is now capable of measuring atmospheric temperature profiles from the upper troposphere up to the mesosphere. With the improved setup, the system can be used to validate current lidar-based polar stratospheric cloud classification schemes. The new capability of the instrument measuring temperature and aerosol extinction furthermore enables studies of the thermal structure and variability of the upper troposphere/lower stratosphere. Although several lidars are operated at polar latitudes, there are few instruments that are capable of measuring temperature profiles in the troposphere, stratosphere, and mesosphere, as well as aerosols extinction in the troposphere and lower stratosphere with daylight capability.

Towards a long term global snow climate data record from satellite data generated within the Snow Climate Change Initiative

2020 ◽  
Author(s):  
Gabriele Schwaizer ◽  
Lars Keuris ◽  
Thomas Nagler ◽  
Chris Derksen ◽  
Kari Luojus ◽  
...  
Keyword(s):  
Time Series ◽  
Satellite Data ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Process Models ◽  
Climate Data ◽  
Seasonal Snow ◽  
Snow Water

<p>Seasonal snow is an important component of the global climate system. It is highly variable in space and time and sensitive to short term synoptic scale processes and long term climate-induced changes of temperature and precipitation. Current snow products derived from various satellite data applying different algorithms show significant discrepancies in extent and snow mass, a potential source for biases in climate monitoring and modelling. The recently launched ESA CCI+ Programme addresses seasonal snow as one of 9 Essential Climate Variables to be derived from satellite data.</p><p>In the snow_cci project, scheduled for 2018 to 2021 in its first phase, reliable fully validated processing lines are developed and implemented. These tools are used to generate homogeneous multi-sensor time series for the main parameters of global snow cover focusing on snow extent and snow water equivalent. Using GCOS guidelines, the requirements for these parameters are assessed and consolidated using the outcome of workshops and questionnaires addressing users dealing with different climate applications. Snow extent product generation applies algorithms accounting for fractional snow extent and cloud screening in order to generate consistent daily products for snow on the surface (viewable snow) and snow on the surface corrected for forest masking (snow on ground) with global coverage. Input data are medium resolution optical satellite images (AVHRR-2/3, AATSR, MODIS, VIIRS, SLSTR/OLCI) from 1981 to present. An iterative development cycle is applied including homogenisation of the snow extent products from different sensors by minimizing the bias. Independent validation of the snow products is performed for different seasons and climate zones around the globe from 1985 onwards, using as reference high resolution snow maps from Landsat and Sentinel- 2as well as in-situ snow data following standardized validation protocols.</p><p>Global time series of daily snow water equivalent (SWE) products are generated from passive microwave data from SMMR, SSM/I, and AMSR from 1978 onwards, combined with in-situ snow depth measurements. Long-term stability and quality of the product is assessed using independent snow survey data and by intercomparison with the snow information from global land process models.</p><p>The usability of the snow_cci products is ensured through the Climate Research Group, which performs case studies related to long term trends of seasonal snow, performs evaluations of CMIP-6 and other snow-focused climate model experiments, and applies the data for simulation of Arctic hydrological regimes.</p><p>In this presentation, we summarize the requirements and product specifications for the snow extent and SWE products, with a focus on climate applications. We present an overview of the algorithms and systems for generation of the time series. The 40 years (from 1980 onwards) time series of daily fractional snow extent products from AVHRR with 5 km pixel spacing, and the 20-year time series from MODIS (1 km pixel spacing) as well as the coarse resolution (25 km pixel spacing) of daily SWE products from 1978 onwards will be presented along with first results of the multi-sensor consistency checks and validation activities.</p>

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