Jørn Kristiansen

Is there a cosmic ray signal in recent variations in global cloudiness and cloud radiative forcing

In order to evaluate a recent hypothesis of a coupling between galactic cosmic rays, clouds, and climate we have investigated temporal variations in global cloudiness and radiative fluxes at the top of the atmosphere. For this purpose we have used the best available global data sets, i.e., those of the International Satellite Cloud Climatology Project (ISCCP) and the Earth Radiation Budget Experiment (ERBE), respectively. Both globally and over midlatitude oceans only, we find a decrease in total cloud coverage between 1986 and 1990 of 2%, while between 1990 and 1993 there is a slightly smaller decrease. When the results are related to temporal variations in cosmic ray activity, we do not find support for a coupling between cosmic rays, total cloudiness, and radiative forcing of climate. A possible exception is low marine clouds at midlatitudes, characterized by few cloud condensation nuclei and a large net cooling effect, but no physical mechanism is known which might explain a connection between cosmic rays and low clouds. The net radiative effect of clouds during the period 1985–1989 shows an enhanced cooling effect despite a reduction in both total and low cloud cover. This contradicts the simple relationship between cloud cover and radiation assumed in the cosmic-ray-cloud-climate hypothesis. The interpretation of the results is rendered difficult by the short time series of ISCCP and ERBE data and by uncertainties concerning instrument calibrations and changes of satellites. When a 43-year time series of synoptic observations over sea is related to cosmic rays over the same period, a weak, negative correlation is found.

AROME-MetCoOp: A Nordic Convective-Scale Operational Weather Prediction Model

AbstractSince October 2013 a convective-scale weather prediction model has been used operationally to provide short-term forecasts covering large parts of the Nordic region. The model is now operated by a bilateral cooperative effort [Meteorological Cooperation on Operational Numerical Weather Prediction (MetCoOp)] between the Norwegian Meteorological Institute and the Swedish Meteorological and Hydrological Institute. The core of the model is based on the convection-permitting Applications of Research to Operations at Mesoscale (AROME) model developed by Meteo-France. In this paper the specific modifications and updates that have been made to suit advanced high-resolution weather forecasts over the Nordic regions are described. This includes modifications in the surface drag description, microphysics, snow assimilation, as well as an update of the ecosystem and surface parameter description. Novel observation types are introduced in the operational runs, including ground-based Global Navigation Satellite...

Optimal atmospheric forcing perturbations for the Cold Ocean Warm Land pattern

The atmospheric Integrated Forecast System model from the European Centre for Medium-Range Weather Forecasts is used to calculate forcing perturbations which are optimal in producing atmospheric response patterns resembling the ‘cold-ocean-warm-land’ (COWL) flow regime over 4 d. Similar initial state perturbations are computed for comparison. COWL is relevant for recent climate change. The perturbations are optimal in a tangent-linear sense but are validated by non-linear calculations. Calculations cover 836 cases during 22 winter seasons. The method effectively estimates flow-dependant perturbations which produce response patterns resembling COWL. The optimal forcing is more geographically confined with relatively smaller remote amplitudes and larger spatial scale than the initial state perturbations. The quality of the 4-d response is highly dependent on the actual optimal perturbation. Averaging over just a few cases drastically reduces this optimal property, but the long-term climate response of an average forcing does produce signatures of the COWL regime. The results are discussed in view of Palmer’s non-linear dynamical perspective on climate change, and several key elements are confirmed: the climate sensitivity is flow dependent; efficient forcing structures do not resemble the response (non-normality); sensitivity and predictability are negatively correlated; and flow characteristics for high sensitivity differ from those for low sensitivity.

Characteristics of a Convective-Scale Weather Forecasting System for the European Arctic

AbstractIn this study a 1-yr dataset of a convective-scale atmospheric prediction system of the European Arctic (AROME-Arctic) is compared with the ECMWF’s medium-range forecasting, ensemble forecasting, and reanalysis systems, by using surface and radiosonde observations of wind and temperature. The focus is on the characteristics of the model systems in the very short-term forecast range (6–15 h), but without a specific focus on lead-time dependencies. In general, AROME-Arctic adds value to the representation of the surface characteristics. The atmospheric boundary layer thickness, during stable conditions, is overestimated in the global models, presumably because of a too diffusive turbulence scheme. Instead, AROME-Arctic shows a realistic mean thickness compared to the radiosonde observations. All models behave similarly for the upper-air verification and surprisingly, as well, in forecasting the location of a polar low in the short-range forecasts. However, when comparing with the largest wind speeds...

Soil Field Model Interoperability: Challenges and Impact on Screen Temperature Forecast Skill during the Nordic Winter

AbstractThe high-resolution (4-km grid length) Met Office (UKMO) Unified Model forecasts driven by the coarser-resolution (8-km grid length) High-Resolution Limited-Area Model (HIRLAM), UM4, often produce significantly colder screen-level (2 m) temperatures in winter over Norway than forecast with HIRLAM itself. To diagnose the main error source of this cold bias this study focuses on the forecast initial and lateral boundary conditions, particularly the initialization of soil moisture and temperature. The soil variables may be used differently by land surface schemes of varying complexity, representing a challenge to model interoperability. In a set of five experiments, daily UM4 forecasts are driven by alternating initial and lateral boundary conditions from two different parent models: HIRLAM and Met Office North Atlantic and Europe (NAE). The experiment period is November 2007. Points for scientific examination into the topics of model interoperability and sensitivity to soil initial conditions are id...