The ACOS CO_2 retrieval algorithm – Part II: Global X_(CO_2) data characterization

Here, we report preliminary estimates of the column averaged carbon dioxide (CO_2) dry air mole fraction, X_(CO_2), retrieved from spectra recorded over land by the Greenhouse gases Observing Satellite, GOSAT (nicknamed "Ibuki"), using retrieval methods originally developed for the NASA Orbiting Carbon Observatory (OCO) mission. After screening for clouds and other known error sources, these retrievals reproduce much of the expected structure in the global X_(CO_2) field, including its variation with latitude and season. However, low yields of retrieved X_(CO_2) over persistently cloudy areas and ice covered surfaces at high latitudes limit the coverage of some geographic regions, even on seasonal time scales. Comparisons of early GOSAT X_(CO_2) retrievals with X_(CO_2) estimates from the Total Carbon Column Observing Network (TCCON) revealed a global, −2% (7–8 parts per million, ppm, with respect to dry air) X_(CO_2) bias and 2 to 3 times more variance in the GOSAT retrievals. About half of the global X_(CO_2) bias is associated with a systematic, 1% overestimate in the retrieved air mass, first identified as a global +10 hPa bias in the retrieved surface pressure. This error has been attributed to errors in the O_2 A-band absorption cross sections. Much of the remaining bias and spurious variance in the GOSAT X_(CO_2) retrievals has been traced to uncertainties in the instrument's calibration, oversimplified methods for generating O_2 and CO_2 absorption cross sections, and other subtle errors in the implementation of the retrieval algorithm. Many of these deficiencies have been addressed in the most recent version (Build 2.9) of the retrieval algorithm, which produces negligible bias in X_(CO_2) on global scales as well as a ~30% reduction in variance. Comparisons with TCCON measurements indicate that regional scale biases remain, but these could be reduced by applying empirical corrections like those described by Wunch et al. (2011b). We recommend that such corrections be applied before these data are used in source sink inversion studies to minimize spurious fluxes associated with known biases. These and other lessons learned from the analysis of GOSAT data are expected to accelerate the delivery of high quality data products from the Orbiting Carbon Observatory-2 (OCO-2), once that satellite is successfully launched and inserted into orbit

Study Of The Tsunami Aftermath And Recovery (STAR): Ketahanan dan Pemulihan di Sumatra Setelah Tsunami

Tsunami di Samudera Hindia pada tahun 2004 telah menghancurkan ribuan komunitas di negara-negara yang berbatasan dengan Samudera Hindia. Kerusakan paling parah terjadi di Nanggroe Aceh Darussalam dan Provinsi Sumatera Utara, di mana diperkirakan 170.000 jiwa tewas dan ratusan kilometer lingkungan di sepanjang garis pantai hancur. Bencana Tsunami ini telah mendorong diberikannya bantuan yang begitu besar baik dari Pemerintah Indonesia, LSM dan donor bagi kedua provinsi ini. Pada tahun 2007, upaya untuk membangun kembali daerah yang terdampak Tsunami di Indonesia tercatat sebagai proyek rekonstruksi yang paling besar yang pernah dilakukan di sebuah negara berkembang. Studi Paska Tsunami dan Pemulihannya (The Study of the Tsunami Aftermath and Recovery) atau STAR merupakan sebuah studi longitudinal yang mengumpulkan informasi dari individu, rumah tangga, komunitas dan fasilitas di Nanggroe Aceh Darussalam dan Provinsi Sumatera Utara. Studi dirancang untuk mengumpulkan data tentang dampak Tsunami Tahun 2004 baik dampak pendek maupun dampak jangka panjang serta berbagai upaya pemulihan yang dilakukan. Untuk mengetahui dampak Tsunami terhadap kehidupan individu, komunitas dan keluarga serta bagaimana respon mereka terhadap bencana tersebut, kami melaksanakan STAR. Pada tahun 2005 kami mulai dengan mengunjungi kembali 32.000 responden, tersebar dalam 487 komunitas yang sebelumnya pada tahun 2004 sudah pernah diwawancarai dalam survei rumah tangga oleh BPS (Survei Pra-Tsunami). Wawancara paska Tsunami kami lakukan setiap tahun selama 5 tahun sesudah terjadinya Tsunami. Sebanyak 98% dari responden BPS tersebut selamat dari bencana Tsunami di mana kami kemudian berhasil mewawancarai 96% dari mereka, untuk setidaknya sekali dari rangkaian wawancara paska Tsunami yang kami lakukan. Data yang dihasilkan dari studi ini memberikan informasi tentang dampak jangka pendek yang dialami oleh masyarakat dan upaya pemulihan di wilayah-wilayah yang paling parah terdampak Tsunami, yang mana kemudian kami bandingkannya dengan kehidupan masyarakat di wilayah yang tidak terdampak atau hanya sedikit terdampak Tsunami. Kami akan melaporkan hasil studi kami berdasarkan data yang dikumpulkan sejak tahun 2004 sampai tahun 2010. Saat ini kami sedang melakukan survei lanjutan 10 tahun setelah Tsunami

Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes

Canopy structural and leaf photosynthesis parameterizations such as maximum carboxylation capacity (Vcmax), slope of the Ball–Berry stomatal conductance model (BBslope) and leaf area index (LAI) are crucial for modeling plant physiological processes and canopy radiative transfer. These parameters are large sources of uncertainty in predictions of carbon and water fluxes. In this study, we develop an optimal moving window nonlinear Bayesian inversion framework to use the Soil Canopy Observation Photochemistry and Energy fluxes (SCOPE) model for constraining Vcmax, BBslope and LAI with observations of coupled carbon and energy fluxes and spectral reflectance from satellites. We adapted SCOPE to follow the biochemical implementation of the Community Land Model and applied the inversion framework for parameter retrievals of plant species that have both the C3 and C4 photosynthetic pathways across three ecosystems. We present comparative analysis of parameter retrievals using observations of (i) gross primary productivity (GPP) and latent energy (LE) fluxes and (ii) improvement in results when using flux observations along with reflectance. Our results demonstrate the applicability of the approach in terms of capturing the seasonal variability and posterior error reduction (40&thinsp;%–90&thinsp;%) of key ecosystem parameters. The optimized parameters capture the diurnal and seasonal variability in the GPP and LE fluxes well when compared to flux tower observations (0.95&gt;R2&gt;0.79). This study thus demonstrates the feasibility of parameter inversions using SCOPE, which can be easily adapted to incorporate additional data sources such as spectrally resolved reflectance and fluorescence and thermal emissions.</p

Application of Pulsed Field Gel Electrophoresis to Determine γ-ray-induced Double-strand Breaks in Yeast Chromosomal Molecules

The frequency of DNA double-strand breaks (dsb) was determined in yeast cells exposed to γ-rays under anoxic conditions. Genomic DNA of treated cells was separated by pulsed field gel electrophoresis, and two different approaches for the evaluation of the gels were employed: (1) The DNA mass distribution profile obtained by electrophoresis was compared to computed profiles, and the number of DSB per unit length was then derived in terms of a fitting procedure; (2) hybridization of selected chromosomes was performed, and a comparison of the hybridization signals in treated and untreated samples was then used to derive the frequency of dsb

Toward accurate CO_2 and CH_4 observations from GOSAT

The column-average dry air mole fractions of atmospheric carbon dioxide and methane (X_(CO_2) and X_(CH_4)) are inferred from observations of backscattered sunlight conducted by the Greenhouse gases Observing SATellite (GOSAT). Comparing the first year of GOSAT retrievals over land with colocated ground-based observations of the Total Carbon Column Observing Network (TCCON), we find an average difference (bias) of −0.05% and −0.30% for X_(CO_2) and X_(CH_4) with a station-to-station variability (standard deviation of the bias) of 0.37% and 0.26% among the 6 considered TCCON sites. The root-mean square deviation of the bias-corrected satellite retrievals from colocated TCCON observations amounts to 2.8 ppm for X_(CO_2) and 0.015 ppm for X_(CH_4). Without any data averaging, the GOSAT records reproduce general source/sink patterns such as the seasonal cycle of X_(CO_2) suggesting the use of the satellite retrievals for constraining surface fluxes

A method for evaluating bias in global measurements of CO_2 total columns from space

We describe a method of evaluating systematic errors in measurements of total column dry-air mole fractions of CO_2 (X_(CO_2)) from space, and we illustrate the method by applying it to the v2.8 Atmospheric CO_2 Observations from Space retrievals of the Greenhouse Gases Observing Satellite (ACOS-GOSAT) measurements over land. The approach exploits the lack of large gradients in X_(CO_2) south of 25° S to identify large-scale offsets and other biases in the ACOS-GOSAT data with several retrieval parameters and errors in instrument calibration. We demonstrate the effectiveness of the method by comparing the ACOS-GOSAT data in the Northern Hemisphere with ground truth provided by the Total Carbon Column Observing Network (TCCON). We use the observed correlation between free-tropospheric potential temperature and X_(CO_2) in the Northern Hemisphere to define a dynamically informed coincidence criterion between the ground-based TCCON measurements and the ACOS-GOSAT measurements. We illustrate that this approach provides larger sample sizes, hence giving a more robust comparison than one that simply uses time, latitude and longitude criteria. Our results show that the agreement with the TCCON data improves after accounting for the systematic errors, but that extrapolation to conditions found outside the region south of 25° S may be problematic (e.g., high airmasses, large surface pressure biases, M-gain, measurements made over ocean). A preliminary evaluation of the improved v2.9 ACOS-GOSAT data is also discussed

Multiscale analyses of solar‐induced florescence and gross primary production

Solar‐induced fluorescence (SIF) has shown great promise for probing spatiotemporal variations in terrestrial gross primary production (GPP), the largest component flux of the global carbon cycle. However, scale mismatches between SIF and ground‐based GPP have posed challenges toward fully exploiting these data. We used SIF obtained at high spatial sampling rates and resolution by NASA’s Orbiting Carbon Observatory‐2 satellite to elucidate GPP‐SIF relationships across space and time in the U.S. Corn Belt. Strong linear scaling functions (R2 ≥ 0.79) that were consistent across instantaneous to monthly time scales were obtained for corn ecosystems and for a heterogeneous landscape based on tall tower observations. Although the slope of the corn function was ~56% higher than for the landscape, SIF was similar for corn (C4) and soybean (C3). Taken together, there is strong observational evidence showing robust linear GPP‐SIF scaling that is sensitive to plant physiology but insensitive to the spatial or temporal scale.Key PointsGPP scales linearly with SIF from instantaneous to monthly time scalesAggregating ecosystem GPP‐SIF functions yield a representative landscape relation that matched one obtained directly using tall tower GPPGPP‐SIF relations showed sensitivity to plant physiology but not spatiotemporal scalePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135999/1/grl55274_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135999/2/grl55274.pd

Organische Dünger in Topfkulturen auf dem Prüfstand - wie steht es mit der Stickstofffreisetzung?

Matching nitrogen demand of plants and N release of organic fertilizers with respect to amount and timing is one key for successful cultivation of organic ornamentals. Thereby for plants with a low to moderate N demand growers can add the fertilizer as complete preplant application (CPA). For plants with a high N demand splitting fertilization in a reduced preplant application combined with an additional fertigation (RPA+F) is preferable. Aim of the current research was the investigation of N release of organic fertilizers in incubation experiments. Results of the incubation experiment were linked to a pot trial with pelargonium. Incubation experiments reveal that most fertilizers release about 40 to 50 % of total N and most nitrogen is released within the first 21 days. Only for sheep wool a delay of N release up to ten days was found. CPA using sheep wool and RPA+F (irrespective of fertilizer) give the best results. The delayed release pattern of sheep wool seems to match best N demand of plants