TY  - JOUR
AB  - Assessing the capacity of numerical models to produce viable tropical cyclones, as well as assessing the climatological behavior of simulated tropical cyclones, requires an objective tracking method. These make use of parameter thresholds to determine whether a detected feature, such as a vorticity maximum or a warm core, is strong enough to indicate a tropical cyclone. The choice of parameter thresholds is generally subjective. This study proposes and assesses the parallel use of many threshold parameter combinations, combining a number of weaker and stronger values. The tracking algorithm succeeds in tracking tropical cyclones within the model data, beginning at their aggregation stage or shortly thereafter and ending when they interact strongly with extratropical flow and transition into extratropical cyclones or when their warm core decays. The sensitivity of accumulated cyclone energy to tracking errors is assessed. Tracking errors include the faulty initial detection and termination of valid tropical cyclones and systems falsely identified as tropical cyclones. They are found to not significantly impact the accumulated cyclone energy. Thus, the tracking algorithm produces an adequate estimate of the accumulated cyclone energy within the underlying data.
AU  - Enz, B.M.*
AU  - Engelmann, J.P.
AU  - Lohmann, U.*
C1  - 68205
C2  - 53617
CY  - Bahnhofsallee 1e, Gottingen, 37081, Germany
SP  - 5093-5112
TI  - Use of threshold parameter variation for tropical cyclone tracking.
JO  - Geosci. Model. Dev.
VL  - 16
IS  - 17
PB  - Copernicus Gesellschaft Mbh
PY  - 2023
SN  - 1991-959X
ER  - 

TY  - JOUR
AB  - Global biogeochemical ocean models are invaluable tools to examine how physical, chemical, and biological processes interact in the ocean. Satellite-derived ocean color properties, on the other hand, provide observations of the surface ocean, with unprecedented coverage and resolution. Advances in our understanding of marine ecosystems and biogeochemistry are strengthened by the combined use of these resources, together with sparse in situ data. Recent modeling advances allow the simulation of the spectral properties of phytoplankton and remote sensing reflectances, bringing model outputs closer to the kind of data that ocean color satellites can provide. However, comparisons between model outputs and analogous satellite products (e.g., chlorophyll a) remain problematic. Most evaluations are based on point-by-point comparisons in space and time, where spuriously large errors can occur from small spatial and temporal mismatches, whereas global statistics provide no information on how well a model resolves processes at regional scales. Here, we employ a unique suite of methodologies, the Probability Density Functions to Evaluate Models (PDFEM), which generate a robust comparison of these resources. The probability density functions of physical and biological properties of Longhurst's provinces are compared to evaluate how well a model resolves related processes. Differences in the distributions of chlorophyll a concentration (mg m(-3)) provide information on matches and mismatches between models and observations. In particular, mismatches help isolate regional sources of discrepancy, which can lead to improving both simulations and satellite algorithms. Furthermore, the use of radiative transfer in the model to mimic remotely sensed products facilitates model-observation comparisons of optical properties of the ocean.
AU  - Jonsson, B.F.*
AU  - Follett, C.L.*
AU  - Bien, J.*
AU  - Dutkiewicz, S.*
AU  - Hyun, S.*
AU  - Kulk, G.*
AU  - Forget, G.L.*
AU  - Müller, C.L.
AU  - Racault, M.F.*
AU  - Hill, C.N.*
AU  - Jackson, T.*
AU  - Sathyendranath, S.*
C1  - 69390
C2  - 53857
CY  - Bahnhofsallee 1e, Gottingen, 37081, Germany
SP  - 4639-4657
TI  - Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite-derived chlorophyll.
JO  - Geosci. Model. Dev.
VL  - 16
IS  - 16
PB  - Copernicus Gesellschaft Mbh
PY  - 2023
SN  - 1991-959X
ER  - 

TY  - JOUR
AB  - The symbiosis between plants and Ectomycorrhizal fungi (ECM) is shown to considerably influence the carbon (C) and nitrogen (N) fluxes between the soil, rhizosphere, and plants in boreal forest ecosystems. However, ECM are either neglected or presented as an implicit, undynamic term in most ecosystem models, which can potentially reduce the predictive power of models. In order to investigate the necessity of an explicit consideration of ECM in ecosystem models, we implement the previously developed MYCOFON model into a detailed process-based, soil-plant-atmosphere model, Coup-MYCOFON, which explicitly describes the C and N fluxes between ECM and roots. This new Coup-MYCOFON model approach (ECM explicit) is compared with two simpler model approaches: one containing ECM implicitly as a dynamic uptake of organic N considering the plant roots to represent the ECM (ECM implicit), and the other a static N approach in which plant growth is limited to a fixed N level (nonlim). Parameter uncertainties are quantified using Bayesian calibration in which the model outputs are constrained to current forest growth and soil C / N ratio for four forest sites along a climate and N deposition gradient in Sweden and simulated over a 100-year period. The "nonlim" approach could not describe the soil C / N ratio due to large overestimation of soil N sequestration but simulate the forest growth reasonably well. The ECM "implicit" and "explicit" approaches both describe the soil C / N ratio well but slightly underestimate the forest growth. The implicit approach simulated lower litter production and soil respiration than the explicit approach. The ECM explicit Coup-MYCOFON model provides a more detailed description of internal ecosystem fluxes and feedbacks of C and N between plants, soil, and ECM. Our modeling highlights the need to incorporate ECM and organic N uptake into ecosystem models, and the nonlim approach is not recommended for future long-term soil C and N predictions. We also provide a key set of posterior fungal parameters that can be further investigated and evaluated in future ECM studies.
AU  - He, H.*
AU  - Meyer, A.
AU  - Jansson, P.-E.*
AU  - Svensson, M.*
AU  - Rütting, T.*
AU  - Klemedtsson, L.*
C1  - 53210
C2  - 44479
CY  - Gottingen
SP  - 725-751
TI  - Simulating ectomycorrhiza in boreal forests: Implementing ectomycorrhizal fungi model MYCOFON in CoupModel (v5).
JO  - Geosci. Model. Dev.
VL  - 11
IS  - 2
PB  - Copernicus Gesellschaft Mbh
PY  - 2018
SN  - 1991-959X
ER  -