Publications by Nick Schutgens

On the Limits of CALIOP for Constraining Modeled Free Tropospheric Aerosol


D Watson-Parris, N Schutgens, D Winker, SP Burton, RA Ferrare, P Stier

THE GLOBAL AEROSOL SYNTHESIS AND SCIENCE PROJECT (GASSP): Measurements and Modeling to Reduce Uncertainty


CL Reddington, KS Carslaw, P Stier, N Schutgens, H Coe, D Liu, J Allan, J Browse, KJ Pringle, LA Lee, M Yoshioka, JS Johnson, LA Regayre, DV Spracklen, GW Mann, A Clarke, M Hermann, S Henning, H Wex, TB Kristensen, WR Leaitch, U Poeschl, D Rose, MO Andreae, J Schmale, Y Kondo, N Oshima, JP Schwarz, A Nenes, B Andersrson, GC Roberts, JR Snider, C Leck, PK Quinn, X Chi, A Ding, JL Jimenez, Q Zhang

Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0


E Di Tomaso, NAJ Schutgens, O Jorba, CP Garcia-Pando

On the spatio-temporal representativeness of observations


N Schutgens, S Tsyro, E Gryspeerdt, D Goto, N Weigum, M Schulz, P Stier

Will a perfect model agree with perfect observations? The impact of spatial sampling


NAJ Schutgens, E Gryspeerdt, N Weigum, S Tsyro, D Goto, M Schulz, P Stier

Community Intercomparison Suite (CIS) v1.4.0: a tool for intercomparing models and observations


D Watson-Parris, N Schutgens, N Cook, Z Kipling, P Kershaw, E Gryspeerdt, B Lawrence, P Stier

The importance of temporal collocation for the evaluation of aerosol models with observations


NAJ Schutgens, DG Partridge, P Stier

Effect of aerosol subgrid variability on aerosol optical depth and cloud condensation nuclei: implications for global aerosol modelling


N Weigum, N Schutgens, P Stier

Jury is still out on the radiative forcing by black carbon.

Proceedings of the National Academy of Sciences of the United States of America 113 (2016) E5092-E5093

O Boucher, Y Balkanski, Ø Hodnebrog, CL Myhre, G Myhre, J Quaas, BH Samset, N Schutgens, P Stier, R Wang

Effects of data assimilation on the global aerosol key optical properties simulations

ATMOSPHERIC RESEARCH 178 (2016) 175-186

X Yin, T Dai, NAJ Schutgens, D Goto, T Nakajima, G Shi

Will a perfect model agree with perfect observations? the impact of spatial sampling

Atmospheric Chemistry and Physics Discussions 2016 (2016)

NAJ Schutgens, E Gryspeerdt, N Weigum, S Tsyro, D Goto, M Schulz, P Stier

© Author(s) 2016. The spatial resolution of global climate models with interactive aerosol and the observations used to evaluate them is very different. Current models use grid-spacings of ∼ 200 km, while satellite observations of aerosol use so-called pixels of ∼ 10 km. Ground site or air-borne observations concern even smaller spatial scales. We study the errors incurred due to different resolutions by aggregating high-resolution simulations (10 km grid-spacing) over either the large areas of global model grid-boxes ("perfect" model data) or small areas corresponding to the pixels of satellite measurements or the field-of-view of ground-sites ("perfect" observations). Our analysis suggests that instantaneous RMS differences between these perfect observations and perfect global models can easily amount to 30-160%, for a range of observables like AOT (Aerosol Optical Thickness), extinction, black carbon mass concentrations, PM 2.5 , number densities and CCN (Cloud Condensation Nuclei). These differences, due entirely to different spatial sampling of models and observations, are often larger than measurement errors in real observations. Temporal averaging over a month of data reduces these differences more strongly for some observables (e.g. a three-fold reduction i.c. AOT), than for others (e.g. a two-fold reduction for surface black carbon concentrations), but significant RMS differences remain (10-75%). Note that this study ignores the issue of temporal sampling of real observations, which is likely to affect our present monthly error estimates. We examine several other strategies (e.g. spatial aggregation of observations, interpolation of model data) for reducing these differences and show their effectiveness. Finally, we examine consequences for the use of flight campaign data in global model evaluation and show that significant biases may be introduced depending on the flight strategy used.

Fire emission heights in the climate system - Part 2: Impact on transport, black carbon concentrations and radiation


A Veira, S Kloster, NAJ Schutgens, JW Kaiser

Development of Seamless Chemical Assimilation System and Its Application for Atmospheric Environmental Materials

シミュレーション 小宮山印刷工業 34 (2015) 104-114

T Nakajima, R Imasu, A Takami, D Goto, H Tsuruta, J Uchida, T Dai, S Misawa, K Ueda, CFS Ng, C Watanabe, S Konishi, Y Sato, A Higuchi, Y Masutomi, A Murakami, K Tsuchiya, H Kondo, Y Niwa, K Yoshimura, T Ohara, Y Morino, N Schutgens, K Sudo, T Takemura, T Inoue, Y Arai, R Murata, R Yonemoto, TTN Trieu, M Uematsu, M Satoh, H Tomita, H Yashiro, M Hara

Improvement of aerosol optical properties modeling over Eastern Asia with MODIS AOD assimilation in a global non-hydrostatic icosahedral aerosol transport model.

Environmental pollution (Barking, Essex : 1987) 195 (2014) 319-329

T Dai, NAJ Schutgens, D Goto, G Shi, T Nakajima

A new global aerosol assimilation system adopting a more complex icosahedral grid configuration is developed. Sensitivity tests for the assimilation system are performed utilizing satellite retrieved aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the results over Eastern Asia are analyzed. The assimilated results are validated through independent Aerosol Robotic Network (AERONET) observations. Our results reveal that the ensemble and local patch sizes have little effect on the assimilation performance, whereas the ensemble perturbation method has the largest effect. Assimilation leads to significantly positive effect on the simulated AOD field, improving agreement with all of the 12 AERONET sites over the Eastern Asia based on both the correlation coefficient and the root mean square difference (assimilation efficiency). Meanwhile, better agreement of the Ångström Exponent (AE) field is achieved for 8 of the 12 sites due to the assimilation of AOD only.

C459 大気環境物質のためのシームレス同化システム構築とその応用(都市における気候変動適応研究の最先端,専門分科会)

大会講演予講集 日本気象学会 105 (2014)

映 中島, 良 今須, 光 植松, 昭 高見, 大 五藤, 純 打田, 豊 井上, 治 鶴田, 翔 三澤, 諒 村田, T Dai, N Schutgens, 佳 上田, C-F-S Ng, 正 佐藤, 陽 佐藤, 暁 村上, 篤 樋口, SALSAプロジェクトチーム

A pathway analysis of global aerosol processes


NAJ Schutgens, P Stier

Simulated aerosol key optical properties over global scale using an aerosol transport model coupled with a new type of dynamic core


T Dai, D Goto, NAJ Schutgens, X Dong, G Shia, T Nakajima

Applying a local Ensemble transform Kalman filter assimilation system to the NICAM-SPRINTARS model

AIP Conference Proceedings 1531 (2013) 744-747

T Dai, NAJ Schutgens, T Nakajima

A Local Ensemble Transform Kalman Filter (LETKF) assimilation system has been implemented to a new type of ultra-high resolution aerosol-coupled global cloud resolving model called the Nonhydrostatic Icosahedral Atmospheric Model or NICAM to perform an experimental aerosol reanalysis. The Level 3 filtered, corrected, and aggregated MODIS AOD based on MODIS Level 2 aerosol product using the standard Collection 5 MODIS AOD algorithm are used to test the assimilation system. A posteriori AOT reduced the RMSD between MODIS AOT by 29.7% compared to a priori AOT. © 2013 AIP Publishing LLC.

Improvement of the retrieval algorithm for GOSAT SWIR XCO<inf>2</inf>and XCH<inf>4</inf>and their validation using TCCON data

Atmospheric Measurement Techniques 6 (2013) 1533-1547

Y Yoshida, N Kikuchi, I Morino, O Uchino, S Oshchepkov, A Bril, T Saeki, N Schutgens, GC Toon, D Wunch, CM Roehl, PO Wennberg, DWT Griffith, NM Deutscher, T Warneke, J Notholt, J Robinson, V Sherlock, B Connor, M Rettinger, R Sussmann, P Ahonen, P Heikkinen, E Kyrö, J Mendonca, K Strong, F Hase, S Dohe, T Yokota

The column-averaged dry-air mole fractions of carbon dioxide and methane (XCO2 and XCH4) have been retrieved from Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed (SWIR) observations and released as a SWIR L2 product from the National Institute for Environmental Studies (NIES). XCO2 and XCH4 retrieved using the version 01.xx retrieval algorithm showed large negative biases and standard deviations (-8.85 and 4.75 ppm for XCO2 and -20.4 and 18.9 ppb for XCH 4, respectively) compared with data of the Total Carbon Column Observing Network (TCCON). Multiple reasons for these error characteristics (e.g., solar irradiance database, handling of aerosol scattering) are identified and corrected in a revised version of the retrieval algorithm (version 02.xx). The improved retrieval algorithm shows much smaller biases and standard deviations (-1.48 and 2.09 ppm for XCO2 and -5.9 and 12.6 ppb for XCH4, respectively) than the version 01.xx. Also, the number of post-screened measurements is increased, especially at northern mid- and high-latitudinal areas. © Author(s) 2013.

Validation and empirical correction of MODIS AOT and AE over ocean


NAJ Schutgens, M Nakata, T Nakajima