The ERA5 global reanalysis

An intermediate-complexity, quasi–physically based, meteorological model (MicroMet) has been developed to produce high-resolution (e.g., 30-m to 1-km horizontal grid increment) atmospheric forcings required to run spatially distributed terrestrial models over a wide variety of landscapes. The following eight variables, required to run most terrestrial models, are distributed: air temperature, relative humidity, wind speed, wind direction, incoming solar radiation, incoming longwave radiation, surface pressure, and precipitation. To produce these distributions, MicroMet assumes that at least one value of each of the following meteorological variables are available for each time step, somewhere within, or near, the simulation domain: air temperature, relative humidity, wind speed, wind direction, and precipitation. These variables are collected at most meteorological stations. For the incoming solar and longwave radiation, and surface pressure, either MicroMet can use its submodels to generate these fields, or it can create the distributions from observations as part of a data assimilation procedure. MicroMet includes a preprocessor component that analyzes meteorological data, then identifies and corrects potential deficiencies. Since providing temporally and spatially continuous atmospheric forcing data for terrestrial models is a core objective of MicroMet, the preprocessor also fills in any missing data segments with realistic values. Data filling is achieved by employing a variety of procedures, including an autoregressive integrated moving average calculation for diurnally varying variables (e.g., air temperature). To create the distributed atmospheric fields, spatial interpolations are performed using the Barnes objective analysis scheme, and subsequent corrections are made to the interpolated fields using known temperature–elevation, wind–topography, humidity–cloudiness, and radiation–cloud–topography relationships.

A Meteorological Distribution System for High Resolution Terrestrial Modeling (MicroMet)

SnowModel is a spatially distributed snow-evolution modeling system designed for application in landscapes, climates, and conditions where snow occurs. It is an aggregation of four submodels: MicroMet defines meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowPack simulates snow depth and water-equivalent evolution, and SnowTran-3D accounts for snow redistribution by wind. Since each of these submodels was originally developed and tested for nonforested conditions, details describing modifications made to the submodels for forested areas are provided. SnowModel was created to run on grid increments of 1 to 200 m and temporal increments of 10 min to 1 day. It can also be applied using much larger grid increments, if the inherent loss in high-resolution (subgrid) information is acceptable. Simulated processes include snow accumulation; blowing-snow redistribution and sublimation; forest canopy interception, unloading, and sublimation; snow-density evolution; and snowp...

A Distributed Snow Evolution Modeling System (SnowModel)

[1] The extratropical upper troposphere and lower stratosphere (Ex-UTLS) is a transition region between the stratosphere and the troposphere. The Ex-UTLS includes the tropopause, a strong static stability gradient and dynamic barrier to transport. The barrier is reflected in tracer profiles. This region exhibits complex dynamical, radiative, and chemical characteristics that place stringent spatial and temporal requirements on observing and modeling systems. The Ex-UTLS couples the stratosphere to the troposphere through chemical constituent transport (of, e.g., ozone), by dynamically linking the stratospheric circulation with tropospheric wave patterns, and via radiative processes tied to optically thick clouds and clear-sky gradients of radiatively active gases. A comprehensive picture of the Ex-UTLS is presented that brings together different definitions of the tropopause, focusing on observed dynamical and chemical structure and their coupling. This integral view recognizes that thermal gradients and dynamic barriers are necessarily linked, that these barriers inhibit mixing and give rise to specific trace gas distributions, and that there are radiative feedbacks that help maintain this structure. The impacts of 21st century anthropogenic changes to the atmosphere due to ozone recovery and climate change will be felt in the Ex-UTLS, and recent simulations of these effects are summarized and placed in context.

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The extratropical upper troposphere and lower stratosphere

. In hydrological climate-change impact studies, regional climate models (RCMs) are commonly used to transfer large-scale global climate model (GCM) data to smaller scales and to provide more detailed regional information. Due to systematic and random model errors, however, RCM simulations often show considerable deviations from observations. This has led to the development of a number of correction approaches that rely on the assumption that RCM errors do not change over time. It is in principle not possible to test whether this underlying assumption of error stationarity is actually fulfilled for future climate conditions. In this study, however, we demonstrate that it is possible to evaluate how well correction methods perform for conditions different from those used for calibration with the relatively simple differential split-sample test. For five Swedish catchments, precipitation and temperature simulations from 15 different RCMs driven by ERA40 (the 40 yr reanalysis product of the European Centre for Medium-Range Weather Forecasts (ECMWF)) were corrected with different commonly used bias correction methods. We then performed differential split-sample tests by dividing the data series into cold and warm respective dry and wet years. This enabled us to cross-evaluate the performance of different correction procedures under systematically varying climate conditions. The differential split-sample test identified major differences in the ability of the applied correction methods to reduce model errors and to cope with non-stationary biases. More advanced correction methods performed better, whereas large deviations remained for climate model simulations corrected with simpler approaches. Therefore, we question the use of simple correction methods such as the widely used delta-change approach and linear transformation for RCM-based climate-change impact studies. Instead, we recommend using higher-skill correction methods such as distribution mapping.

Is bias correction of Regional Climate Model (RCM) simulations possible for non-stationary conditions?

Evaluation of variability among different precipitation products in the Northern Great Plains

A physics-based miniensemble of Weather Research and Forecasting model simulations of climate change over the Great Lakes Basin has been constructed, by dynamically downscaling a single global Community Earth System Model 1 simulation driven by the Representative Concentration Pathways 8.5 scenario. The analysis pipeline is successfully verified by comparison of the results with observations for the historical period (1979–1994) and then applied to produce future projections (2045–2060). By midcentury, in this miniensemble, the future change in rainfall distribution is projected to correspond to an increase of total rainfall (median increase of between 13 and 19%) characterized by a fattening of the tail of the distribution (median increase of between 14 and 29% of the amplitude of a 50 year extreme rainfall event). Average rainfall intensity changes are shown to accurately follow the “Clausius–Clapeyron” thermodynamically expected 7% increase per degree of surface warming, whereas heavy rainfall changes are found to lie between 7 and 10% per degree of surface warming. This further increase can be explained by two effects in the Great Lakes region: midtropospheric warming is projected to be larger than surface warming and heavy rainfall events are projected to originate from higher altitude where additional moisture is available. Details of the physics configuration play only a secondary role in determining the future precipitation changes, primarily through their impact on future temperature changes. The uncertainty in the future projection of precipitation and its extremes therefore depends primarily upon the uncertainty in projected future warming which will require implementation of a larger ensemble of projections to be more accurately assessed.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2014JD021855

Climate change impacts on Great Lakes Basin precipitation extremes

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2018WR024381

Simulating Climate Change Impacts on Surface Water Resources Within a Lake-Affected Region Using Regional Climate Projections

Global horizontal wavenumber kinetic energy spectra and spectral fluxes of rotational kinetic energy and enstrophy are computed for a range of vertical levels using a T799 ECMWF operational analysis. Above 250 hPa, the kinetic energy spectra exhibit a distinct break between steep and shallow spectral ranges, reminiscent of dual power-law spectra seen in aircraft data and high-resolution general circulation models. The break separates a large-scale “balanced” regime in which rotational flow strongly dominates divergent flow and a mesoscale “unbalanced” regime where divergent energy is comparable to or larger than rotational energy. Between 230 and 100 hPa, the spectral break shifts to larger scales (from n = 60 to n = 20, where n is spherical harmonic index) as the balanced component of the flow preferentially decays. The location of the break remains fairly stable throughout the stratosphere. The spectral break in the analysis occurs at somewhat larger scales than the break seen in aircraft data. ...

/pdf/the-troposphere-to-stratosphere-transition-in-kinetic-energy-1o800j5a68.pdf

Andre R. Erler

Papers

Evaluation of variability among different precipitation products in the Northern Great Plains

Climate change impacts on Great Lakes Basin precipitation extremes

Simulating Climate Change Impacts on Surface Water Resources Within a Lake-Affected Region Using Regional Climate Projections

The Troposphere-to-Stratosphere Transition in Kinetic Energy Spectra and Nonlinear Spectral Fluxes as Seen in ECMWF Analyses

Evaluating Climate Change Impacts on Soil Moisture and Groundwater Resources Within a Lake‐Affected Region