MIMI v1.0 was designed for use within Earth system models to simulate the 3-D emission, atmospheric processing, and deposition of iron and its soluble fraction. Understanding the iron cycle is important due to its role as an essential micronutrient for ocean phytoplankton; its supply limits primary productivity in many of the world's oceans. Human activity has perturbed the iron cycle, and MIMI is capable of diagnosing many of these impacts; hence, it is important for future climate studies.

We have improved several aspects of atmospheric sulfur cycling in SOCOL-AER, an aerosol–chemistry–climate model. The newly implemented features in SOCOL-AERv2 include interactive deposition schemes, improved sulfur mass conservation, and expanded tropospheric chemistry. SOCOL-AERv2 shows better agreement with stratospheric aerosol observations and sulfur deposition networks compared to SOCOL-AERv1. SOCOL-AERv2 can be used to study impacts of sulfate aerosol on climate, chemistry, and ecosystems.

One of the consequences of changes in the shape of Earth's orbit over time (in addition to pacing glacial–interglacial variations) is changes in the length of months or seasons. The well-known paleo calendar effect that results can produce patterns in comparisons of present-day and paleoclimate model simulations that could be mistaken for real climate changes. We illustrate the source of those patterns and describe an approach and set of programs for routinely adjusting for the effect.

Operational forecasting of the ocean state – e.g. used for ship route planning, sea rescue, and oil spill drift models – relies on data (forcing) obtained from weather forecasting. Unfortunately, the so-called meteorological analysis step introduces a discontinuity, which affects the ocean models adversely. In the present paper, a straightforward method to deal with the issue is introduced. Practical examples are given to illuminate the scale of the problem.

Many land surface models rely on solutions derived from two-stream approximations utilizing leaf-level optical properties, many of which have not been formally reviewed or published. Using plant functional type groupings of the Community Land Model (CLM), we found large deviations between measured and CLM default near-infrared optical properties, implying that the modeled shortwave radiation budget including surface albedo may be expected to change after updating the biased parameters.

This study assesses the assimilation of cloud water path retrievals in three phases (ice, supercooled, and liquid), derived from Meteosat-8, into a limited-area model using an ensemble Kalman filter (EnKF). The ability of the method to improve cloud analyses in the southwest Indian Ocean and short-term forecasts of global horizontal irradiance on Réunion Island is demonstrated using the Data Assimilation Research Testbed (DART) and the Weather Research and Forecasting (WRF) model.

We have developed an openly accessible web-based platform for visualization and promotion of easy access to one-dimensional hydrodynamic lake model output data updated in near-real time (simstrat.eawag.ch). This platform was developed for 54 lakes in Switzerland, with potential for adaptation to other regional areas or even at a global worldwide scale using appropriate forcing input data.

To determine the effects of land cover change on climate, researchers must be able to quantify the net change in energy (radiation) at the top of the atmosphere caused by changes in surface reflectance (albedo). Historically, this was done with sophisticated models that require detailed input datasets only available to specialists. Here we combine existing remotely sensed datasets and a new formulation to create a new model that is accurate, transparent, and easy to use.

We measure how computational performance of the global FESOM2 ocean model (formulated on an unstructured mesh) changes with the increase in the number of computational cores. We find that for many components of the model the performance increases linearly but we also identify two bottlenecks: sea ice and ssh submodules. We show that FESOM2 is on par with the state-of-the-art ocean models in terms of throughput that reach 16 simulated years per day for eddy resolving configuration (1/10°).

The response of barrier islands to sea level rise depends on their ability to move landward through the transport of sediment from the beach to the back barrier. The BRIE model simulates these processes and the resulting landward movement of barrier islands. The novelty of the BRIE model is the incorporation of tidal inlets (gaps between barrier islands) that can transport sediment landward and therefore help keep barrier islands above sea level.

A reflectivity operator was developed for directly assimilating radar reflectivity involving contributions from ice species with the variational data assimilation method. Its current version was implemented in WRFDA 3.9.1. This operator allows for not only the dry snow/graupel but also the wet species so that it can effectively obtain the rainwater, snow, and graupel analysis which improved the short-term precipitation forecasts compared to those of the experiment without DA.

In this study, we propose an additional climate model validation procedure that assesses whether causality signals between model drivers and responses are consistent with those observed in nature. Specifically, we suggest the method of conditional dispersion as the best approach to directly measure the causality between model forcing and response. Our results show that there is a strong causal signal from the carbon dioxide series to the global temperature series.

This paper presents a new model code that can be used to date the flow of hot fluids in the crust and the age of hot springs. It does so by modelling the thermal effects of fluid flow in the subsurface and by comparing the results with low-temperature thermochronology, which is a widely used method to quantify the temperature history of minerals and rocks. The model also demonstrates the effects of the depth and angle of permeable faults on temperatures of hot springs.

We assess the differences of six stomatal conductance formulations, embedded into a land–vegetation model JSBACH, on 10 boreal coniferous evergreen forest sites. We calibrate the model parameters using all six functions in a multi-year experiment, as well as for a separate drought event at one of the sites, using the adaptive population importance sampler. The analysis reveals weaknesses in the stomatal conductance formulation-dependent model behaviour that we are able to partially amend.

This research aimed at finding a compression method suitable for the ground processing of CFOSAT and SWOT satellite datasets. Lossless algorithms did not allow enough compression. That is why we began studying lossy alternatives. This work introduces the digit rounding algorithm which reduces the volume of scientific datasets keeping only the significant digits in each sample value. The number of digits kept is relative to each sample so that both small and high values are similarly preserved.

The paper mainly has two contributions. First, a post-processor framework is proposed to improve hydrologic model accuracy. The key is to characterize possible connections between model inputs and errors. Based on results, it is also possible to replace the time-consuming model calibration step using our post-processor framework. Second, a window selection method is proposed to handle nonstationary data. A window size is chosen containing stable data using a measure named DS proposed by us.

We conducted a comprehensive sensitivity analysis to understand behaviors of a demographic vegetation model within a land surface model. By running the model 5000 times with changing input parameter values, we found that (1) the photosynthetic capacity controls carbon fluxes, (2) the allometry is important for tree growth, and (3) the targeted carbon storage is important for tree survival. These results can provide guidance on improved model parameterization for a better fit to observations.

This paper presents a new numerical model able to simulate for the first time the evolution of Earth's surface at a global scale under different precipitation, sea level, and tectonic conditions. This is significant as it can help to bridge the gap between local- and global-scale predictions of Earth's past and future variations.