ABSTRACT In the region of European Alps, national and regional meteorological services operate rain‐gauge networks, which together, constitute one densest in situ observation systems a large‐scale high‐mountain region. Data from these networks are consistently analyzed, this study, to develop pan‐Alpine grid dataset describe region's mesoscale precipitation climate, including occurrence heavy long dry periods. The analyses based on collation high‐resolution data seven Alpine countries, with...

The influence of uncertainties in gridded observational reference data on regional climate model (RCM) evaluation is quantified a pan‐European scale. Three different sets are considered: the coarse‐resolved E‐OBS set, compilation high‐resolution products (HR) and European‐scale MESAN reanalysis. Five ERA‐Interim‐driven RCM experiments EURO‐CORDEX initiative evaluated against each these references over eight European sub‐regions considering range performance metrics for mean daily temperature...

Abstract Gridded analyses of observed precipitation are an important data resource for environmental modelling, climate model evaluation and monitoring. In Europe, datasets that resolve the rich mesoscale variations widely exist national territories, but similar covering entire continent more recent. Here, we evaluate daily in two newly available pan‐European datasets: E‐OBS (v19.0e), a statistical analysis from rain‐gauge data, ERA5, new global reanalysis ECMWF. Special interest is on how...

Abstract. The conventional climate gridded datasets based on observations only are widely used in atmospheric sciences; our focus this paper is and hydrology. On the Norwegian mainland, seNorge2 provides high-resolution fields of daily total precipitation for applications requiring long-term at regional or national level, where challenge to simulate small-scale processes often taking place complex terrain. dataset constitutes a valuable meteorological input snow hydrological simulations; it...

A research-based understanding of permafrost distribution at a sufficient spatial resolution is important to meet the demands science, education and society. We present new map for Norway, Sweden Finland that provides more detailed updated description in this area than previously available. implemented CryoGRID1 model 1 km2 resolution, forced by operationally gridded data-set daily air temperature snow cover Finland, Norway Sweden. Hundred realisations were run each grid cell, based on...

Abstract. seNorge_2018 is a collection of observational gridded datasets over Norway for daily total precipitation: mean, maximum, and minimum temperatures. The time period covers 1957 to 2017, the data are presented high-resolution terrain-following grid with 1 km spacing in both meridional zonal directions. seNorge family developed at Norwegian Meteorological Institute (MET Norway) has 20-year-long history its newest member, first providing maximum used wide range applications climatology,...

Abstract Citizen weather stations are rapidly increasing in prevalence and becoming an emerging source of information. These low-cost consumer-grade devices provide observations real time form parts dense networks that capture high-resolution meteorological Despite these benefits, their adoption into operational prediction systems has been slow. However, MET Norway recently introduced from Netatmo’s network the postprocessing near-surface temperature forecasts for Scandinavia, Finland,...

This article describes a two‐step spatial interpolation method for 2 m temperature. A scale‐separation approach based on statistical (specifically modification of classical optimal (OI)) has been implemented. The presented makes use in situ observations only and used to build the seNorge2 dataset hourly daily averaged temperature over Norwegian mainland. main original contribution is blending several fields, each representing OI background subregion, into single deterministic regional (i.e....

Abstract Regional reanalyses constitute valuable new data sources for climatological applications by providing consistent meteorological parameter fields commonly requested, e.g., wind speed, solar radiation, temperature and precipitation. Within the European project Uncertainties in Ensembles of ReAnalyses (UERRA) three different numerical weather prediction (NWP) models have been employed to generate regional subsequent surface reanalysis products. The uncertainties individual products...

There are few commonly used indicators that describe the state of Earth’s global hydrological cycle and here we propose three to capture how an increased greenhouse effect influences associated rainfall patterns. They are: i) 24-hr total rainfall, ii) surface area with daily precipitation, iii) mean precipitation intensity. With a recent progress in both satellite observations reanalyses, can now estimate provide new insights into intensity changes over time. Based on ERA5 reanalysis, find...

Abstract Surface air temperature (t2m) data are essential for understanding climate dynamics and assessing the impacts of change. Reanalysis products, which combine observations with retrospective short‐range weather forecasts, can provide consistent comprehensive datasets. ERA5 represents state‐of‐the‐art in global reanalyses supplies initial boundary conditions higher‐resolution regional designed to capture finer‐scale atmospheric processes. However, these products require validation,...

Abstract We conducted an analysis of hydrological cycle variations across 13 regions varying sizes distributed different continents. The is based on five reanalysis datasets daily precipitation, all produced by the European Centre Medium‐Range Weather Forecasts (ECMWF): ERA5 high‐resolution, ensemble, CERA‐20C, ERA20‐C and ERA20‐CM. examined several climate indicators, including mean 75th 99th percentiles, precipitation area fraction fractions with precipitations exceeding 10 20 mm....

Abstract An objective analysis technique is applied to a local, high‐resolution meteorological observation network in the presence of complex topography. The choice optimal interpolation (OI) makes it possible implement standard spatial algorithm efficiently. At same time OI constitutes basis develop, perspective, full multivariate data assimilation scheme. In absence background model field, simple and effective de‐trending procedure implemented. Three‐dimensional correlation functions are...

Abstract. In science, poor quality input data will invariably lead to faulty conclusions, as in the spirit of saying “garbage in, garbage out”. Atmospheric sciences make no exception and correct is crucial obtain a useful representation real world meteorological, climatological hydrological applications. Titan computer program for automatic control meteorological that has been designed serve real-time operational applications process massive amounts observations measured by networks weather...

Abstract Both the total amount of precipitation falling on Earth’s surface and fraction area which it falls represent two key global climate indicators for hydrological cycle. We show that receiving daily is closely connected to statistics local wet-day frequency mean intensity, based ERA5 reanalysis. Our analysis statistical distribution temporal intensity $$\mu$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>μ</mml:mi> </mml:math> revealed a close link between (1) its...

ABSTRACT Regional climate models represent a valuable tool in impact analyses. Their ability to accurately estimate current and future conditions is increasingly important. In Norway precipitation of special interest. Heavy precipitation, particularly over short durations, responsible for enormous damages infrastructure such as roads railways, hence information on fine spatial temporal scale crucial. We evaluate the seven regional model simulations 0.11° resolution from CORDEX ensemble...

Abstract. Estimation of extreme event distributions and depth-duration-frequency (DDF) curves is achieved at any target site by repeated sampling among all available raingauge data in the surrounding area. The estimate computed over a gridded domain Northern Italy, using precipitation time series from 1929 to 2011, including historical analog stations present-day automatic observational network. presented local regionalisation naturally overcomes traditional station-point methods, with their...

A spatial consistency test (SCT) is applied to temperature observations of a high-resolution meteorological network composed automatic surface weather stations. The SCT's purpose twofold: preventing gross errors (GEs) from entering numerical elaborations and returning flag an external quality-control system. algorithm based on Bayesian concepts exploits the existing objective analysis scheme by comparing each observed value with corresponding cross-validation (CV) value. Local data density...

Abstract Reanalysis and satellite data indicate a decreasing precipitation area in recent decades, affecting local water resources intensities. We have used CMIP6 simulations to test the hypothesis of shrinking warming climate. Our analyses reveal that SSP5-8.5 projections show robust decrease between 50 °S °N, globally 75% simulations. The new findings support observed relationship, although lesser extent than earlier found reanalysis data. find poleward shift precipitation, increasing...

Abstract Climate models show that global warming will disproportionately influence high‐latitude regions and indicate drastic changes in, among others, seasonal snow cover. However, current continental simulations covering these are often run at coarse grid resolutions, potentially introducing large errors in computed fluxes states. To quantify some of errors, we have assessed the sensitivity an energy‐balance model to resolution using a multiparametrization framework for spatial domain...

Abstract Strong historical and predicted future warming over high-latitudes prompt significant effects on agricultural forest ecosystems. Thus, there is an urgent need for spatially-detailed information of current thermal growing season (GS) conditions their past changes. Here, we deployed a large network weather stations, high-resolution geospatial environmental data semi-parametric regression to model the spatial variation in multiple GS variables (i.e. beginning, end, length, degree day...

Abstract. In recent years, the use of mesoscale meteorological network data has been growing. An Optimal Interpolation (OI) method is used to interpolate on a regular grid hourly averaged values temperature, relative humidity, wind vector, atmospheric pressure, and cumulated precipitation. For all variables, except precipitation, background (i.e. first guess) information obtained by detrending observations using geographical parameters. M. Lema radar-derived best estimate precipitation rate...

The 1981–2010 monthly precipitation climatologies for Norway at 1 km resolution are presented. They computed by an interpolation procedure (HCLIM+RK) combining the output from a numerical model with in situ observations. Specifically, regional climate data set HCLIM‐AROME, based on dynamical downscaling of global ERA‐Interim reanalysis onto 2.5 resolution, is considered together 2009 rain‐gauges located within domain. defined superimposing grid normals and kriging station residuals. combined...