Relationship between SAR-Derived Wind Vectors and Wind at 10-m Height Represented by a Mesoscale Model

Koch, Wolfgang; Feser, Frauke

doi:10.1175/mwr3134.1

Cited by 39 publications

(44 citation statements)

References 21 publications

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“…The REMO physics are adapted from the ECHAM4 global model of the Max-Planck-Institute for Meteorology (Koch and Feser, 2006). The specific REMO simulation used here was performed with nudging of large scale meteorological fields (von Storch et al, 2000) to keep the simulated state close to the driving state at larger scales, while allowing the model to freely generate regional-scale weather within Europe (Feser and Weisse, 2001).…”

Section: Biogeosciencesmentioning

confidence: 99%

How errors on meteorological variables impact simulated ecosystem fluxes: a case study for six French sites

et al. 2012

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Abstract. We analyze how biases of meteorological drivers impact the calculation of ecosystem CO 2 , water and energy fluxes by models. To do so, we drive the same ecosystem model by meteorology from gridded products and by meteorology from local observation at eddy-covariance flux sites. The study is focused on six flux tower sites in France spanning across a climate gradient of 7-14 • C annual mean surface air temperature and 600-1040 mm mean annual rainfall, with forest, grassland and cropland ecosystems. We evaluate the results of the ORCHIDEE process-based model driven by meteorology from four different analysis data sets against the same model driven by site-observed meteorology. The evaluation is decomposed into characteristic time scales. The main result is that there are significant differences in meteorology between analysis data sets and local observation. The phase of seasonal cycle of air temperature, humidity and shortwave downward radiation is reproduced correctly by all meteorological models (average R 2 = 0.90). At sites located in altitude, the misfit of meteorological drivers from analysis data sets and tower meteorology is the largest. We show that dayto-day variations in weather are not completely well reproduced by meteorological models, with R 2 between analysis data sets and measured local meteorology going from 0.35 to 0.70. The bias of meteorological driver impacts the flux simulation by ORCHIDEE, and thus would have an effect on regional and global budgets. The forcing error, defined by the simulated flux difference resulting from prescribing modeled instead of observed local meteorology drivers to OR-CHIDEE, is quantified for the six studied sites at different time scales. The magnitude of this forcing error is compared to that of the model error defined as the modeled-minusobserved flux, thus containing uncertain parameterizations, parameter values, and initialization. The forcing error is on average smaller than but still comparable to model error, with the ratio of forcing error to model error being the largest on daily time scale (86 %) and annual time scales (80 %). The forcing error incurred from using a gridded meteorological data set to drive vegetation models is therefore an important component of the uncertainty budget of regional CO 2 , water and energy fluxes simulations, and should be taken into consideration in up-scaling studies.

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Section: Biogeosciencesmentioning

confidence: 99%

How errors on meteorological variables impact simulated ecosystem fluxes: a case study for six French sites

et al. 2012

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“…The prognostic variables are surface air pressure, temperature, horizontal wind components, specific humidity and cloud water. The physics scheme applied is a version of the global model ECHAM4 physics of the Max-Planck-Institute for meteorology adapted for the regional model (Koch and Feser, 2006). The model simulation was computed with additional "nudging of large scales" (von Storch et al, 2000).…”

Section: Model Inputsmentioning

confidence: 99%

“…temperature Precipitation radiation humidity Cosby et al (1984), Saxton et al (1986) Temperature (max,min, daily average) REMO Feser et al (2001), Koch and Feser (2006), REMO Jacob and Podzun (1997), Kalnay et al (1997) examine the changes in terrestrial CO 2 exchange. This simple division to compare model output is arbitrary and does not follows ecosystem or bioclimatic zones boundaries.…”

Section: Modelmentioning

confidence: 99%

Analyzing the causes and spatial pattern of the European 2003 carbon flux anomaly using seven models

et al. 2008

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Abstract. Globally, the year 2003 is associated with one of the largest atmospheric CO 2 rises on record. In the same year, Europe experienced an anomalously strong flux of CO 2 from the land to the atmosphere associated with an exceptionally dry and hot summer in Western and Central Europe. In this study we analyze the magnitude of this carbon flux anomaly and key driving ecosystem processes using simulations of seven terrestrial ecosystem models of different complexity and types (process-oriented and diagnostic). We address the following questions: (1) how large were deviations in the net European carbon flux in 2003 relative to a shortterm baseline (1998)(1999)(2000)(2001)(2002) C for Western Europe and between 24 and -129 Tg C for Central Europe depending on the model used. All models responded to a dipole pattern of the climate anomaly in 2003. In Western and Central Europe NEP was reduced due to heat and drought. In contrast, lower than normal temperatures and higher air humidity decreased NEP over Northeastern Europe. While models agree on the sign of changes in simulated NEP and gross primary productivity in 2003 over Western and Central Europe, models diverge in the estimates of anomalies in ecosystem respiration. Except for two process models which simulate respiration increase, most models simulated a decrease in ecosystem respiration in 2003. The diagnostic models showed a weaker decrease in ecosystem respiration than the process-oriented models.Based on the multi-model simulations we estimated the total carbon flux anomaly over the 2003 growing season in Europe to range between -0.02 and -0.27 Pg C relative to the net carbon flux in 1998-2002.

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“…The hourly ground-level wind speed and surface air pressure fields cover Europe and the North Atlantic with 0.58 3 0.58 resolution (around 50-60 km). Koch and Feser (2006) compared satellite-retrieved wind data with surface winds simulated in REMO and found that REMO describes wind speeds realistically. Weisse et al (2005) show that surface wind fields and their statistics are homogeneous and reasonably well simulated over the sea in coastDat.…”

Section: Introductionmentioning

confidence: 99%

The Informational Value of Pressure-Based Single-Station Proxies for Storm Activity

Krueger

Storch

2012

Journal of Atmospheric and Oceanic Technology

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Air pressure readings and their variations are commonly used to make inferences about storm activity. More precisely, it is assumed that the variation of annual and seasonal statistics of several pressure-based proxies describes changes in the past storm climate qualitatively, an assumption that has yet to be proven.A systematic evaluation of the informational content of five pressure-based proxies for storm activity based on single-station observations of air pressure is presented. The number of deep lows, lower percentiles of pressure, the frequency of absolute pressure tendencies above certain thresholds, as well as mean values and high percentiles of absolute pressure tendencies is examined. Such an evaluation needs long and homogeneous records of wind speed, something that is not available from observations. Consequently, the proxies are examined by using datasets of ground-level wind speeds and air pressure from the NCEP-driven and spectrally nudged regional model, REMO. The proxies are gauged against the 95th and 99th percentile time series of ground-level wind speeds to quantify the relation between pressure-based proxies and storminess. These analyses rely on bootstrap and binomial hypothesis testing. The analyses of single-station-based proxies indicate that the proxies are generally linearly linked to storm activity, and that absolute pressure tendencies have the highest informational content. Further, it is investigated as to whether the proxies have the potential for describing storminess over larger areas, also with regard to surface conditions. It is found that absolute pressure tendencies have improved informational value when describing storm activity over larger areas, while low pressure readings do not show improved informational value.

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Relationship between SAR-Derived Wind Vectors and Wind at 10-m Height Represented by a Mesoscale Model

Cited by 39 publications

References 21 publications

How errors on meteorological variables impact simulated ecosystem fluxes: a case study for six French sites

How errors on meteorological variables impact simulated ecosystem fluxes: a case study for six French sites

Analyzing the causes and spatial pattern of the European 2003 carbon flux anomaly using seven models

The Informational Value of Pressure-Based Single-Station Proxies for Storm Activity

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