scholarly journals Weather model verification using Sodankylä mast measurements

2016 ◽  
Vol 5 (1) ◽  
pp. 75-84 ◽  
Author(s):  
Markku Kangas ◽  
Laura Rontu ◽  
Carl Fortelius ◽  
Mika Aurela ◽  
Antti Poikonen
Keyword(s):  
Weather Forecasting ◽  
Longwave Radiation ◽  
Model Verification ◽  
Environmental Research ◽  
Research Centre ◽  
Cold Bias ◽  
Finnish Meteorological Institute ◽  
Radiation Fluxes ◽  
Weather Model ◽  
Nwp Model

Abstract. Sodankylä, in the heart of Arctic Research Centre of the Finnish Meteorological Institute (FMI ARC) in northern Finland, is an ideal site for atmospheric and environmental research in the boreal and sub-Arctic zone. With temperatures ranging from −50 to +30 °C, it provides a challenging testing ground for numerical weather forecasting (NWP) models as well as weather forecasting in general. An extensive set of measurements has been carried out in Sodankylä for more than 100 years. In 2000, a 48 m-high micrometeorological mast was erected in the area. In this article, the use of Sodankylä mast measurements in NWP model verification is described. Starting in 2000, with the NWP model HIRLAM and Sodankylä measurements, the verification system has now been expanded to include comparisons between 12 NWP models and seven measurement masts, distributed across Europe. A case study, comparing forecasted and observed radiation fluxes, is also presented. It was found that three different radiation schemes, applicable in NWP model HARMONIE-AROME, produced somewhat different downwelling longwave radiation fluxes during cloudy days, which however did not change the overall cold bias of the predicted screen-level temperature.

scholarly journals Weather model verification using Sodankylä mast measurements

2015 ◽  
Vol 5 (2) ◽  
pp. 577-598
Author(s):  
M. Kangas ◽  
L. Rontu ◽  
C. Fortelius ◽  
M. Aurela ◽  
A. Poikonen
Keyword(s):  
Weather Forecasting ◽  
Model Verification ◽  
Environmental Research ◽  
Wave Radiation ◽  
Research Centre ◽  
Cold Bias ◽  
Finnish Meteorological Institute ◽  
Radiation Fluxes ◽  
Weather Model ◽  
Nwp Model

Abstract. Sodankylä, in the heart of Arctic Research Centre of the Finnish Meteorological Institute (FMI ARC) in northern Finland, is an ideal site for atmospheric and environmental research in the boreal and sub-arctic zone. With temperatures ranging from −50 to +30 °C, it provides a challenging testing ground for numerical weather forecasting (NWP) models as well as weather forecasting in general. An extensive set of measurements has been carried out in Sodankylä for more than 100 years. In 2000, a 48 m high micrometeorological mast was erected in the area. In this article, the use of Sodankylä mast measurements in NWP model verification is described. Started in 2000 with NWP model HIRLAM and Sodankylä measurements, the verification system has now been expanded to include comparisons between 12 NWP models and seven measurement masts. A case study, comparing forecasted and observed radiation fluxes, is also presented. It was found that three different radiation schemes, applicable in NWP model HARMONIE-AROME, produced during cloudy days somewhat different downwelling long-wave radiation fluxes, which however did not change the overall cold bias of the predicted screen-level temperature.

scholarly journals Characterizing energy budget variability at a Sahelian site: a test of NWP model behaviour

2017 ◽  
Vol 17 (24) ◽  
pp. 15095-15119 ◽  
Author(s):  
Anna Mackie ◽  
Paul I. Palmer ◽  
Helen Brindley
Keyword(s):  
Energy Budget ◽  
Radiation Flux ◽  
Linear Models ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Daily Average ◽  
Radiation Fluxes ◽  
Nwp Model

Abstract. We use observations of surface and top-of-the-atmosphere (TOA) broadband radiation fluxes determined from the Atmospheric Radiation Measurement programme mobile facility, the Geostationary Earth Radiation Budget (GERB) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) instruments and a range of meteorological variables at a site in the Sahel to test the ability of the ECMWF Integrated Forecasting System cycle 43r1 to describe energy budget variability. The model has daily average biases of −12 and 18 W m−2 for outgoing longwave and reflected shortwave TOA radiation fluxes, respectively. At the surface, the daily average bias is 12(13) W m−2 for the longwave downwelling (upwelling) radiation flux and −21(−13) W m−2 for the shortwave downwelling (upwelling) radiation flux. Using multivariate linear models of observation–model differences, we attribute radiation flux discrepancies to physical processes, and link surface and TOA fluxes. We find that model biases in surface radiation fluxes are mainly due to a low bias in ice water path (IWP), poor description of surface albedo and model–observation differences in surface temperature. We also attribute observed discrepancies in the radiation fluxes, particularly during the dry season, to the misrepresentation of aerosol fields in the model from use of a climatology instead of a dynamic approach. At the TOA, the low IWP impacts the amount of reflected shortwave radiation while biases in outgoing longwave radiation are additionally coupled to discrepancies in the surface upwelling longwave flux and atmospheric humidity.

scholarly journals Characterising energy budget variability at a Sahelian site: a test of NWP model behaviour

2017 ◽  
Author(s):  
Anna Mackie ◽  
Paul I. Palmer ◽  
Helen Brindley
Keyword(s):  
Energy Budget ◽  
Linear Models ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Shortwave Radiation ◽  
Broadband Radiation ◽  
Radiation Fluxes ◽  
Forecasting System ◽  
Multivariate Linear Models ◽  
Nwp Model

Abstract. We use observations of surface and top-of-the-atmosphere (TOA) broadband radiation fluxes determined from the Atmospheric Radiation Measurement program Mobile Facility, and GERB/SEVIRI,and a range of meteorological variables, at a site in the Sahel to test the ability of the ECMWF Integrated Forecasting System cycle 43r1 to describe energy budget variability. The model has daily average bias of −12 W m-2 and 18 W m-2 for outgoing longwave and reflected shortwave TOA radiation fluxes, respectively. Using multivariate linear models of observation minus model differences, we attribute radiation flux discrepancies to physical processes, and link surface and TOA fluxes. We find that model biases in surface radiation fluxes are mainly due to a low bias in ice-water path (IWP), poor description of surface albedo, and model-observation differences in surface temperature. At the TOA, the low IWP impacts the amount of reflected shortwave radiation while biases in outgoing longwave radiation are additionally coupled to discrepancies in the surface upwelling longwave flux and atmospheric humidity.

TOMOREF operator as a tool to improve weather forecasts

2021 ◽  
Author(s):  
Natalia Hanna ◽  
Estera Trzcina ◽  
Maciej Kryza ◽  
Witold Rohm
Keyword(s):  
Data Assimilation ◽  
Weather Forecasting ◽  
Positive Impact ◽  
Precipitation Event ◽  
Initial State ◽  
Total Delay ◽  
Numerical Weather ◽  
Numerical Weather Model ◽  
Weather Model ◽  
Tomography Data

<p>The numerical weather model starts from the initial state of the Earth's atmosphere in a given place and time. The initial state is created by blending the previous forecast runs (first-guess), together with observations from different platforms. The better the initial state, the better the forecast; hence, it is worthy to combine new observation types. The GNSS tomography technique, developed in recent years, provides a 3-D field of humidity in the troposphere. This technique shows positive results in the monitoring of severe weather events. However, to assimilate the tomographic outputs to the numerical weather model, the proper observation operator needs to be built.</p><p>This study demonstrates the TOMOREF operator dedicated to the assimilation of the GNSS tomography‐derived 3‐D fields of wet refractivity in a Weather Research and Forecasting (WRF) Data Assimilation (DA) system. The new tool has been tested based on wet refractivity fields derived during a very intense precipitation event. The results were validated using radiosonde observations, synoptic data, ERA5 reanalysis, and radar data. In the presented experiment, a positive impact of the GNSS tomography data assimilation on the forecast of relative humidity (RH) was noticed (an improvement of root‐mean‐square error up to 0.5%). Moreover, within 1 hour after assimilation, the GNSS data reduced the bias of precipitation up to 0.1 mm. Additionally, the assimilation of GNSS tomography data had more influence on the WRF model than the Zenith Total Delay (ZTD) observations, which confirms the potential of the GNSS tomography data for weather forecasting.</p>

scholarly journals Sodankylä manual snow survey program

2016 ◽  
Vol 5 (1) ◽  
pp. 163-179 ◽  
Author(s):  
Leena Leppänen ◽  
Anna Kontu ◽  
Henna-Reetta Hannula ◽  
Heidi Sjöblom ◽  
Jouni Pulliainen
Keyword(s):  
Snow Water Equivalent ◽  
Measurement Techniques ◽  
Liquid Water Content ◽  
The Arctic ◽  
Research Centre ◽  
Future Research ◽  
Forest Zone ◽  
Finnish Meteorological Institute ◽  
Snow Properties ◽  
Snow Water

Abstract. The manual snow survey program of the Arctic Research Centre of the Finnish Meteorological Institute (FMI-ARC) consists of numerous observations of natural seasonal taiga snowpack in Sodankylä, northern Finland. The easily accessible measurement areas represent the typical forest and soil types in the boreal forest zone. Systematic snow measurements began in 1909 with snow depth (HS) and snow water equivalent (SWE). In 2006 the manual snow survey program expanded to cover snow macro- and microstructure from regular snow pits at several sites using both traditional and novel measurement techniques. Present-day snow pit measurements include observations of HS, SWE, temperature, density, stratigraphy, grain size, specific surface area (SSA) and liquid water content (LWC). Regular snow pit measurements are performed weekly during the snow season. Extensive time series of manual snow measurements are important for the monitoring of temporal and spatial changes in seasonal snowpack. This snow survey program is an excellent base for the future research of snow properties.

scholarly journals Estimation of Net Radiation using satellite based data inputs

2014 ◽  
Vol XL-8 ◽  
pp. 307-313 ◽  
Author(s):  
S. V. S. Sai Krishna ◽  
P. Manavalan ◽  
P. V. N. Rao
Keyword(s):  
Outgoing Longwave Radiation ◽  
Surface Air Temperature ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Shortwave Radiation ◽  
Net Radiation ◽  
Clear Sky ◽  
Statistical Measures ◽  
Indian Land ◽  
Radiation Fluxes

Daily net surface radiation fluxes are estimated for Indian land mass at spatial grid intervals of 0.1 degree. Two approaches are employed to obtain daily net radiation for four sample days viz., November 19, 2013, December 16, 2013, January 8, 2014 and March 20, 2014. Both the approaches compute net shortwave and net longwave fluxes, separately and sum them up to obtain net radiation. The first approach computes net shortwave radiation using daily insolation product of Kalpana VHRR and 15 days time composited broadband albedo product of Oceansat OCM2. The net outgoing longwave radiation is computed using Stefan Boltzmann equation corrected for humidity and cloudiness. In the second approach, instantaneous clear-sky net-shortwave radiation is estimated using computed clear-sky incoming shortwave radiation and the gridded MODIS 16-day time composited albedo product. The net longwave radiation is obtained by estimating outgoing and incoming longwave radiation fluxes, independently. In this, MODIS derived surface emissivity and skin temperature parameters are used for estimating outgoing longwave radiation component. In both the approaches, surface air temperature data required for estimation of net longwave radiation fluxes are extracted from India Meteorological Department’s (IMD) Automatic Weather Station (AWS) records. Estimates by the two different approaches are evaluated by comparing daily net radiation fluxes with CERES based estimates corresponding to the sample days, through statistical measures. The estimated all sky daily net radiation using the first approach compared well with CERES SYN1deg daily average net radiation with r<sup>2</sup> values of the order of 0.7 and RMS errors of the order of 8&ndash;16 w/m<sup>2</sup>.

scholarly journals Evaluation of Upper Indus Near-Surface Climate Representation by WRF in the High Asia Refined Analysis

2019 ◽  
Vol 20 (3) ◽  
pp. 467-487 ◽  
Author(s):  
David M. W. Pritchard ◽  
Nathan Forsythe ◽  
Hayley J. Fowler ◽  
Greg M. O’Donnell ◽  
Xiao-Feng Li
Keyword(s):  
Regional Climate ◽  
Critical Role ◽  
Critical Evaluation ◽  
Longwave Radiation ◽  
Indus Basin ◽  
Shortwave Radiation ◽  
Cold Bias ◽  
Near Surface ◽  
High Asia ◽  
High Bias

Abstract Data paucity is a severe barrier to the characterization of Himalayan near-surface climates. Regional climate modeling can help to fill this gap, but the resulting data products need critical evaluation before use. This study aims to extend the appraisal of one such dataset, the High Asia Refined Analysis (HAR). Focusing on the upper Indus basin (UIB), the climatologies of variables needed for process-based hydrological and cryospheric modeling are evaluated, leading to three main conclusions. First, precipitation in the 10-km HAR product shows reasonable correspondence with most in situ measurements. It is also generally consistent with observed runoff, while additionally reproducing the UIB’s strong vertical precipitation gradients. Second, the HAR shows seasonally varying bias patterns. A cold bias in temperature peaks in spring but reduces in summer, at which time the high bias in relative humidity diminishes. These patterns are concurrent with summer overestimation (underestimation) of incoming shortwave (longwave) radiation. Finally, these seasonally varying biases are partly related to deficiencies in cloud, snow, and albedo representations. In particular, insufficient cloud cover in summer leads to the overestimation of incoming shortwave radiation. This contributes to the reduced cold bias in summer by enhancing surface warming. A persistent high bias in albedo also plays a critical role, particularly by suppressing surface heating in spring. Improving representations of cloud, snow cover, and albedo, and thus their coupling with seasonal climate transitions, would therefore help build upon the considerable potential shown by the HAR to fill a vital data gap in this immensely important basin.

scholarly journals Effects of Drifting Snow on Surface Radiation Budget in the Katabatic Wind Zone, Antarctica

1985 ◽  
Vol 6 ◽  
pp. 238-241 ◽  
Author(s):  
Takashi Yamanouchi ◽  
Sadao Kawaguchi
Keyword(s):  
Wind Speed ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Radiative Properties ◽  
Radiation Budget ◽  
Katabatic Wind ◽  
Drifting Snow ◽  
Radiation Fluxes ◽  
Snow Drift ◽  
The Difference

Effects of drifting snow are examined from measurements of radiation fluxes at Mizuho Station in the katabatic wind zone, Antarctica. A good correlation is found between the difference of downward longwave fluxes measured at two heights and wind speed used as an index of drifting snow. The wind increases the downward flux at a rate of 2 W m-2/m s-2 when wind speed is higher than 13 m/s. Drifting snow suppresses the net longwave cooling at the surface. Direct solar radiation is depleted greatly by the drifting snow; however, the global flux decreases only slightly, compensated by the large increase of the diffuse flux, at a rate of about 1% for each 1 m/s increase in wind speed. At Mizuho Station, the effect on longwave radiation prevails throughout the year. The relation between snow drift content and wind speed is obtained from shortwave optical depth measurements as a function of wind speed. A simple parameterization of radiative properties is given.

scholarly journals TURAC—A New Instrument Package for Radiation Budget Measurements and Cloud Detection

2005 ◽  
Vol 22 (10) ◽  
pp. 1473-1479 ◽  
Author(s):  
C. Ruckstuhl ◽  
R. Philipona
Keyword(s):  
Numerical Algorithms ◽  
Cloud Amount ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Cloud Detection ◽  
Radiation Fluxes ◽  
New Instrument ◽  
Temperature And Humidity ◽  
Flux Measurements

Abstract Atmospheric radiation flux measurements and the resulting surface radiation budget are important quantities for greenhouse effect and climate change investigations. Accurate net shortwave and longwave fluxes, in conjunction with numerical algorithms, also allow monitoring of the radiative effect of clouds and the nowcasting of the cloud amount. To achieve certain advantages on the accuracy of flux measurements a new instrument is developed that measures downward and upward shortwave and longwave radiation with the same sensors. Two high-quality instruments—a pyranometer for shortwave and a pyrgeometer for longwave measurements—are mounted on a pivotable sensor head, which is rotated up and down in 10-min intervals. To keep the instrument domes free from dew and ice, and to minimize the pyranometer thermal offset, both sensors are ventilated with slightly heated air. Additionally, a ventilated temperature and humidity sensor is integrated in the new instrument. The combination of measurements of radiation fluxes, temperature, and humidity allows for instrument use for autonomous and automatic cloud amount detection. The Temperature, Humidity, Radiation and Clouds (TURAC) sensor has been successfully tested under harsh alpine winter conditions, as well as under moderate lowland conditions. Comparisons to reference instruments showed all radiation fluxes to be within a maximum bias and rms difference of 1.6% or 1.4 W m−2 on daily averages.

scholarly journals The concept of socio-environmental transformations in prehistoric and archaic societies in the Holocene: An introduction to the special issue

The Holocene ◽  
2019 ◽  
Vol 29 (10) ◽  
pp. 1517-1530 ◽  
Author(s):  
Johannes Müller ◽  
Wiebke Kirleis
Keyword(s):  
Collaborative Research ◽  
Spatial Scales ◽  
Environmental Research ◽  
Research Centre ◽  
Detailed Data ◽  
Special Issue ◽  
The Holocene ◽  
Archaeological Methods ◽  
Temporal And Spatial

Transformations of human societies and environments are closely interwoven. Due to improved possibilities of paleoecological reconstruction and archaeological methods, we are now in a position to empirically collect detailed data from a variety of records. The Collaborative Research Centre 1266 ‘Scales of Transformation’ has developed a concept in which both deductive and inductive transformation dimensions are compared on different temporal and spatial scales. This concept includes the connection between the environmental and social spheres, which are often inseparable. Accordingly, a holistic principle of socio-environmental research is developed, which is exemplified by the contributions to this special issue of The Holocene.

Sign in / Sign up

Export Citation Format

Share Document