Relationships between wind speed and gas transfer, combined with knowledge of the partial pressure difference of CO2 across the air-sea interface are frequently used to determine the CO2 flux between the ocean and the atmosphere. Little attention has been paid to the influence of variability in wind speed on the calculated gas transfer velocities and the possibility of chemical enhancement of CO2 exchange at low wind speeds over the ocean. The effect of these parameters is illustrated using a quadratic dependence of gas exchange on wind speed which is fit through gas transfer velocities over the ocean determined by the natural-14C disequilibrium and the bomb-14C inventory methods. Some of the variability between different data sets can be accounted for by the suggested mechanisms, but much of the variation appears due to other causes. Possible causes for the large difference between two frequently used relationships between gas transfer and wind speed are discussed. To determine fluxes of gases other than CO2 across the air-water interface, the relevant expressions for gas transfer, and the temperature and salinity dependence of the Schmidt number and solubility of several gases of environmental interest are included in an appendix.

Relationship between wind speed and gas exchange over the ocean

Precipitation downscaling improves the coarse resolution and poor representation of precipitation in global climate models and helps end users to assess the likely hydrological impacts of climate change. This paper integrates perspectives from meteorologists, climatologists, statisticians, and hydrologists to identify generic end user (in particular, impact modeler) needs and to discuss downscaling capabilities and gaps. End users need a reliable representation of precipitation intensities and temporal and spatial variability, as well as physical consistency, independent of region and season. In addition to presenting dynamical downscaling, we review perfect prognosis statistical downscaling, model output statistics, and weather generators, focusing on recent developments to improve the representation of space-time variability. Furthermore, evaluation techniques to assess downscaling skill are presented. Downscaling adds considerable value to projections from global climate models. Remaining gaps are uncertainties arising from sparse data; representation of extreme summer precipitation, subdaily precipitation, and full precipitation fields on fine scales; capturing changes in small-scale processes and their feedback on large scales; and errors inherited from the driving global climate model.

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Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user

General circulation models (GCMs) suggest that rising concentrations of greenhouse gases may have significant consequences for the global climate. What is less clear is the extent to which local (s...

/pdf/downscaling-general-circulation-model-output-a-review-of-2wkqyp0se8.pdf

Downscaling general circulation model output: a review of methods and limitations

General Circulation Models (GCMs) suggest that rising concentrations of greenhouse gases will have significant implications for climate at global and regional scales. Less certain is the extent to which meteorological processes at individual sites will be affected. So-called ‘downscaling’ techniques are used to bridge the spatial and temporal resolution gaps between what climate modellers are currently able to provide and what impact assessors require. This paper describes a decision support tool for assessing local climate change impacts using a robust statistical downscaling technique. Statistical DownScaling Model (sdsm) facilitates the rapid development of multiple, low-cost, single-site scenarios of daily surface weather variables under current and future regional climate forcing. Additionally, the software performs ancillary tasks of predictor variable pre-screening, model calibration, basic diagnostic testing, statistical analyses and graphing of climate data. The application of sdsm is demonstrated with respect to the generation of daily temperature and precipitation scenarios for Toronto, Canada by 2040–2069.  2002 Elsevier Science Ltd. All rights reserved.

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sdsm — a decision support tool for the assessment of regional climate change impacts

https://hal-ineris.archives-ouvertes.fr/ineris-00961872/document

Modelling air quality in street canyons : a review

http://redac.eng.usm.my/EAH/Literature/PlateJHydrology2002.pdf

Flood risk and flood management

A multidimensional stochastic model is developed for the space-time distribution of daily precipitation. The rainfall is linked to the atmospheric circulation patterns using conditional distributions and conditional spatial covariance functions. The model is a transformed conditional multivariate autoregressive AR(I) model, with parameters depending on the atmospheric circulation pattern. The model reproduces both the local rainfall occurrence probabilities and the distribution of the rainfall amounts at given locations, and the spatial dependence described with the help of cross-covariances of the transformed series. Parameter estimation methods based on the moments of the observed data are developed. A simulation procedure for the model is also presented. Its link to atmospheric circulation patterns makes it suitable for local precipitation simulation under stationary and nonstationary arrivals of atmospheric circulation patterns such as climate change. The model is applied using the classification scheme of the German Weather Service which is available for the time period 1881–1990. Precipitation data measured at 44 different stations for the time period 1977–1990 in the catchment of the river Ruhr (Germany) are used to demonstrate the model.

Space-time model for daily rainfall using atmospheric circulation patterns

Wind-tunnel study of concentration fields in street canyons

Hydrological variables and processes usually exhibit a large spatial variability. Often this variability includes aspects of organization and randomness. Because any hydrological modeling has to deal with the question of spatial variability, methods that quantify the effects of spatial variability are valuable. Moreover, it is important to identify the situations where the spatial variability can be reduced (e.g., by using an “effective” value). For a small and well-instrumented catchment in a loess area in southwest Germany effects of spatial variability of the initial soil moisture and soil hydraulic properties on the runoff are investigated. The analysis is performed with a process-oriented rainfall runoff model. It is shown that organization in spatial patterns of soil moisture and soil properties may have a dominant influence on the catchment runoff. The simulations suggest that spatial variability can result in a complex, event dependent, behavior. It cannot be expected that a model with inputs based on mean parameters or mean initial conditions leads to mean outputs for heterogeneous fields. The analysis of different events shows the changing influence of spatial variability on the runoff with changing storm size. For very small and for large events spatial variability plays a negligible role. A large influence is found for medium-sized events.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/97WR02204

An analysis of the effects of spatial variability of soil and soil moisture on runoff

Prepared as an account of work by the United States Government, this report talks about the Aerodynamic Characteristics of Atmospheric Boundary Layers.

/pdf/aerodynamic-characteristics-of-atmospheric-boundary-layers-3j0xg36ker.pdf

Erich J. Plate

Papers

Flood risk and flood management

Space-time model for daily rainfall using atmospheric circulation patterns

Wind-tunnel study of concentration fields in street canyons

An analysis of the effects of spatial variability of soil and soil moisture on runoff

Aerodynamic Characteristics of Atmospheric Boundary Layers