Driftsondes: Providing In Situ Long-Duration Dropsonde Observations over Remote Regions

Cohn, Stephen A.; Hock, Terry; Cocquerez, Philippe; Wang, Junhong; Rabier, Florence; Parsons, David B.; Harr, Patrick A.; Wu, Chun‐Chieh; Drobinski, Philippe; Karbou, Fatima; Venel, Stephanie; Vargas, André; Fourrié, Nadia; Saint-Ramond, Nathalie; Guidard, Vincent; Doerenbecher, Alexis; Hsu, Huang‐Hsiung; Lin, Po‐Hsiung; Chou, Ming-Dah; Redelsperger, Jean‐Luc; Martin, Charles L.; Fox, Jack J.; Potts, Nick; Young, Kathryn; Cole, Hal

doi:10.1175/bams-d-12-00075.1

Cited by 24 publications

(20 citation statements)

References 24 publications

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“…Also, ECMWF has larger analysis differences (Figure (c)), which is consistent with Figure . The average impact over the Antarctic plateau is to lower the temperature, which is consistent with a compensation of the model biases (Cohn et al, ; Rabier et al, ). The models are not cold enough over the plateau and the dropsondes manage to correct part of this bias.…”

Section: Observing‐system Experimentssupporting

confidence: 69%

“…Such factors include relatively large uncertainty in background forecasts for data assimilation over this region, due to the particular difficulty in forecasting the extreme weather over the Antarctic plateau, with strong thermal inversions and strong coupling with the snow-covered surface. As explained in Cohn et al (2013), all models fail to represent the strong thermal inversion with the right intensity.…”

Section: Observation Coverage and Analysis Uncertainty In The Southermentioning

confidence: 94%

“…It was a contribution to the THORPEX‐IPY projects (The Observing System Research and Predictability Experiment International Polar Year projects), with the main meteorological objective to improve numerical weather prediction systems (Rabier et al, ). The additional in situ observations provided by Concordiasi constitute a reference dataset which was used to compare in situ data with satellite retrievals (Wang et al, ) and numerical forecasts (Cohn et al, ) in order to document shortcomings in models and data assimilation. This knowledge can then be used to improve forecasting and assimilation and lead to more accurate real‐time analyses as well as improved re‐analyses.…”

Section: Introductionmentioning

confidence: 99%

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Observation impact over the southern polar area during the Concordiasi field campaign

Boullot

Rabier

Langland

et al. 2014

Quart J Royal Meteoro Soc

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The impact of observations on analysis uncertainty and forecast performance was investigated for austral spring 2010 over the southern polar area for four different systems (NRL, GMAO, ECMWF and Météo-France) at the time of the Concordiasi field experiment. The largest multi-model variance in 500 hPa height analyses is found in the southern sub-Antarctic oceanic region, where there are rapidly evolving weather systems, rapid forecast-error growth, and fewer upper-air wind observation data to constrain the analyses. The total impact of all observations on the model forecast was computed using the 24 h forecast sensitivity-to-observations diagnostic. Observation types that contribute most to the reduction of the forecast error are shown to be AMSU, IASI, AIRS, GPS-RO, radiosonde, surface and atmospheric motion vector observations. For sounding data, radiosondes and dropsondes, one can note a large impact on the analysis and forecasts of temperature at low levels and a large impact of wind at high levels. Observing system experiments using the Concordiasi dropsondes show a large impact of the observations over the Antarctic plateau extending to lower latitudes with the forecast range, with the largest impact around 50-70 • S. These experiments indicate there is a potential benefit from using radiance data better over land and sea-ice and from innovative atmospheric motion vectors obtained from a combination of various satellites to fill the current data gaps and improve numerical weather prediction analyses in this region.

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Section: Observing‐system Experimentssupporting

confidence: 69%

Section: Observation Coverage and Analysis Uncertainty In The Southermentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Observation impact over the southern polar area during the Concordiasi field campaign

Boullot

Rabier

Langland

et al. 2014

Quart J Royal Meteoro Soc

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“…This effect is maximal at 850 hPa with warming average values exceeding 2 K in the Northern Hemisphere and 1 K in the Southern Hemisphere. One can note that this increase is consistent with findings from the Concordiasi results, showing that the ARPEGE model is too cold over sea ice (Cohn et al 2013). Furthermore, Tjernstrom and Graversen (2009) studied the vertical thermal structure of the lower troposphere using in situ data and 40-yr ECMWF Re-Analysis (ERA-40) data and showed in particular that ERA-40 temperatures are too cold in the upper half of the troposphere.…”

Section: B Impacts On Analysessupporting

confidence: 82%

The Assimilation of Observations from the Advanced Microwave Sounding Unit over Sea Ice in the French Global Numerical Weather Prediction System

Karbou

Rabier

Prigent

2014

Monthly Weather Review

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The aim of this study is to test the feasibility of assimilating microwave observations from the Advanced Microwave Sounding Units (AMSU-A and AMSU-B) through the implementation of an appropriate parameterization of sea ice emissivity. AMSU observations are relevant to the description of air temperature and humidity, and their assimilation into numerical weather prediction (NWP) helps better constrain models in regions where very few observations are assimilated. A sea ice emissivity model suitable for AMSU-A and AMSU-B data is described in this paper and its impact is studied through two assimilation experiments run during the period of the Arctic winter. The first experiment is representative of the operational version of the M et eo-France NWP model whereas the second simulation uses the sea ice emissivity parameterization and assimilates a selection of AMSU channels above polar regions. The assimilation of AMSU observations over sea ice is shown to have a significant effect on atmospheric analyses (in particular those of temperature and humidity). The effect on temperature induces a warming in the lower troposphere, especially around 850 hPa. This leads to an increase in the Arctic inversion strength over the ice cap by almost 2 K. An improvement in medium-range forecasts is also noticed when the NWP model assimilates AMSU observations over sea ice.

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“…During this campaign, 13 National Center for Atmospheric Research driftsonde systems were launched from McMurdo Station. Each driftsonde system consisted of a stratospheric superpressure balloon attached to a gondola that housed up to 56 Miniature In‐Situ Sounding Technology (MIST) dropsondes [ Cohn et al ., ]. Between 23 September and 8 December 2010, 648 atmospheric soundings were collected over the Antarctic landmass and the surrounding ocean (Figure ).…”

Section: Methodsmentioning

confidence: 99%

Validation of AIRS version 6 temperature profiles and surface‐based inversions over Antarctica using Concordiasi dropsonde data

et al. 2015

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During the 2010 Concordiasi field experiment, 635 dropsondes were released from the lower stratosphere providing in situ atmospheric profiles from the release height (~60 hPa) to the surface over Antarctica. They provide a unique data set of high vertical resolution temperature profiles over the entire Antarctic continent and surrounding ocean. This study uses temperature profiles and derived surface-based inversion (SBI) properties from the sonde data set to evaluate Atmospheric Infrared Sounder (AIRS) versions 5 (v5) and 6 (v6) temperature profiles. A total of 1486 matched pairs of profiles are available for analysis. The AIRS averaging kernel, representing the AIRS measurement sensitivity, is applied to the dropsonde profiles. The AIRS data are compared to kernel-averaged dropsonde profiles and found, on average, to have a small cold bias (~0.5°C) (for v6) in the troposphere. AIRS v6 is improved over v5 with both profile-averaged bias and root-mean-square errors reduced by over 25%. Compared to the kernel-averaged dropsonde profiles, AIRS v6 accurately detects the existence of SBIs in 79% of the profiles and agrees on the inversion depth 79% of the time. AIRS correctly identifies SBIs in 59% of cases when compared to the full-resolution sonde. AIRS systematically underestimates the SBI intensity. This is due to warmer reported AIRS surface air temperatures (T a ) than T a measured with the dropsonde. Replacement of AIRS T a with that measured by the dropsonde improves the agreement in both SBI detection and intensity. If AIRS T a could be improved, AIRS has the potential to be a stand-alone SBI detection tool over Antarctica.

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Driftsondes: Providing In Situ Long-Duration Dropsonde Observations over Remote Regions

Cited by 24 publications

References 24 publications

Observation impact over the southern polar area during the Concordiasi field campaign

Observation impact over the southern polar area during the Concordiasi field campaign

The Assimilation of Observations from the Advanced Microwave Sounding Unit over Sea Ice in the French Global Numerical Weather Prediction System

Validation of AIRS version 6 temperature profiles and surface‐based inversions over Antarctica using Concordiasi dropsonde data

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