Random uncertainties and vertical error correlations are estimated for three independent data sets. The three collocated data sets are (1) refractivit…Random uncertainties and vertical error correlations are estimated for three independent data sets. The three collocated data sets are (1) refractivity profiles of radio occultation measurements retrieved from the Metop-A and B and COSMIC-1 missions, (2) refractivity derived from GRUAN-processed RS92 sondes, and (3) refractivity profiles derived from ERAS forecast fields. The analysis is performed using a generalization of the so-called three-cornered hat method to include off-diagonal elements such that full error covariance matrices can be calculated. The impacts from various sources of representativeness error on the uncertainty estimates are analysed. The estimated refractivity uncertainties of radio occultations, radiosondes, and model data are stated with reference to the vertical representation of refractivity in these data sets. The existing theoretical estimates of radio occultation uncertainty are confirmed in the middle and upper troposphere and lower stratosphere, and only little dependence on latitude is found in that region. In the lower troposphere, refractivity uncertainty decreases with latitude. These findings have implications for both retrieval of tropospheric humidity from radio occultations and for assimilation of radio occultation data in numerical weather prediction models and reanalyses.more
The net Arctic sea-ice area (SIA) can be estimated from the sea-ice concentration (SIC) by passive microwave measurements from satellites. To be a tru…The net Arctic sea-ice area (SIA) can be estimated from the sea-ice concentration (SIC) by passive microwave measurements from satellites. To be a truly useful metric, for example of the sensitivity of the Arctic sea-ice cover to global warming, we need, however, reliable estimates of its uncertainty. Here we retrieve this uncertainty by taking into account the spatial and temporal error correlations of the underlying local sea-ice concentration products. As 1 example year, we find that in 2015 the average observational uncertainties of the SIA are 306 000 km2 for daily estimates, 275 000 km2 for weekly estimates, and 164 000 km2 for monthly estimates. The sea-ice extent (SIE) uncertainty for that year is slightly smaller, with 296 000 km2 for daily estimates, 261 000 km2 for weekly estimates, and 156 000 km2 for monthly estimates. These daily uncertainties correspond to about 7 % of the 2015 sea-ice minimum and are about half of the spread in estimated SIA and SIE from different passive microwave SIC products. This shows that random SIC errors play a role in SIA uncertainties comparable to inter-SIC-product biases. We further show that the September SIA, which is traditionally the month with the least amount of Arctic sea ice, declined by 105 000±9000 km2 a−1 for the period from 2002 to 2017. This is the first estimate of a SIA trend with an explicit representation of temporal error correlations.more
Solar radiation can be estimated by a variety of methods in an attempt to overcome the limitations of on-ground records. Novel methods are often appea…Solar radiation can be estimated by a variety of methods in an attempt to overcome the limitations of on-ground records. Novel methods are often appearing but these are rarely compared to others from a different approach. This study surveys the main types of estimation methods for daily Global Horizontal Irradiation (GHI), and then, one characteristic technique per group is selected, discarding possible hybrid approaches: a parametric model based on temperatures and precipitation (Antonanzas model), a statistical model (XGBoost), interpolated ground-based measurements (Ordinary Kriging (OK)), a satellite-based dataset (CM-SAF-SARAH), and a reanalysis dataset (ERA-Interim). The techniques are evaluated in relation to the seasonal variation, the clearness index and the spatial performance at 38 grounds stations in central Spain from 2001 to 2013.
Three different tiers of estimations were obtained being SARAH and OK the best performing methods overall. The SARAH dataset (MAE=1.10±0.13 MJ/m2, MBE=0.22±0.36 MJ/m2) generated estimates with the lowest spread, but led to a slight overestimation in low-altitude flat areas. The OK (MAE=1.10±0.25 MJ/m2, MBE=0.00±0.31 MJ/m2) outperformed SARAH in these flat areas (high density of stations), but at the expense of a higher variability. Alternatively, SARAH surpassed Ordinary Kriging (OK) when the distance to the closest station exceeded 20–30 km. The ERA-Interim reanalysis and the XGBoost were in the second tier of estimations, and the parametric model yielded the worst results overall. ERA-Interim exhibited a systematic overestimation. The locally trained Antonanzas and XGBoost struggled to model the atmospheric transmissivity, showing large positive errors in spring months and a small underestimation of clear-sky days. Finally, a summary with the strengths and weaknesses of the five methods provides a deeper understanding for the selection of the adequate estimation approach.more
The productivity response of a peatland ecosystem in Rzecin, Poland, was determined based on varying aerosols abundant in the atmosphere. The study wa…The productivity response of a peatland ecosystem in Rzecin, Poland, was determined based on varying aerosols abundant in the atmosphere. The study was done with the use of a multifactorial model that combined atmo-spheric and ecosystem modules to describe plant photosynthetic ability from different perspectives. The Gross Ecosystem Production (GEP) was calculated for real conditions in the period from May through September 2018. This period was characterized by increased air temperatures (1.4 degrees C) and reduced precipitation (17%), when compared to the long-term averages (1981-2010) for the studied area. This also aligned with expected direction of climate change predictions. The multifactorial model was used to show that, depending on the aerosol situation, the peatland ecosystem may react with an average increase (8.2%) as well as a decrease (6%) of GEP during the growing season. The modification of atmospheric optical properties with a step-wise increase of aerosol optical depth (AOD) by 0.2 in relation to the observed value, resulted in the increase of diffuse index (DI) of circa 22%, the decrease of photosynthetic photon flux density (PPFD) of circa 5%, and the increase of GEP of circa 8% in each of analyzed months. The GEP reduction (6%) was caused by the absorbing aerosol presence characterized by low single scattering albedo (SSA) value. Consequently, the CO2 uptake process could not be maximized by the ecosystem due to reduced levels of available radiant energy. Conversely, the effect of non-absorbing aerosols presence on GEP was found negligible due to the continental clean aerosols prevailed in the air mass during the study period. Generally speaking, the estimation of the effects of aerosol optical properties on Rzecin peatland production shows that more absorbing aerosols occurrence cause GEP reduction while AOD rise results in GEP gain.more
Abstract. Marine stratocumulus (Sc) clouds play an essential role in the earth radiation budget. Here, we compare liquid water path (LWP), cloud optic…Abstract. Marine stratocumulus (Sc) clouds play an essential role in the earth radiation budget. Here, we compare liquid water path (LWP), cloud optical thickness (τ), and cloud droplet effective radius (re) retrievals from 2 years of collocated Spinning Enhanced Visible and Infrared Imager (SEVIRI), Moderate Resolution Imaging Spectroradiometer (MODIS), and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) observations; estimate the effect of biomass burning smoke on passive imager retrievals; and evaluate the diurnal cycle of South Atlantic marine Sc clouds.The effect of absorbing aerosols from biomass burning on the retrievals was investigated using the aerosol index (AI) obtained from the Ozone Monitoring Instrument (OMI). SEVIRI and MODIS LWPs were found to decrease with increasing AI relative to TMI LWP, consistent with well-known negative visible/near-infrared (VIS/NIR) retrieval biases in τ and re. In the aerosol-affected months of July–August–September, SEVIRI LWP – based on the 1.6 µm re – was biased low by 14 g m−2 ( ∼ 16 %) compared to TMI in overcast scenes, while MODIS LWP showed a smaller low bias of 4 g m−2 ( ∼ 5 %) for the 1.6 µm channel and a high bias of 8 g m−2 ( ∼ 10 %) for the 3.7 µm channel compared to TMI. Neglecting aerosol-affected pixels reduced the mean SEVIRI–TMI LWP bias considerably. For 2 years of data, SEVIRI LWP had a correlation with TMI and MODIS LWP of about 0.86 and 0.94, respectively, and biases of only 4–8 g m−2 (5 %–10 %) for overcast cases.The SEVIRI LWP diurnal cycle was in good overall agreement with TMI except in the aerosol-affected months. Both TMI and SEVIRI LWP decreased from morning to late afternoon, after which a slow increase was observed. Terra and Aqua MODIS mean LWPs also suggested a similar diurnal variation. The relative amplitude of the 2-year-mean and seasonal-mean LWP diurnal cycle varied between 35 % and 40 % from morning to late afternoon for overcast cases. The diurnal variation in SEVIRI LWP was mainly due to changes in τ, while re showed only little diurnal variability.more
The devastating drought in the Sahel during the 70s and the 80s is among the most undisputed and largest recent climate event recognized by the resear…The devastating drought in the Sahel during the 70s and the 80s is among the most undisputed and largest recent climate event recognized by the research community. This dramatic climate event has generated numerous sensitivity analyses on land-atmosphere feedback mechanisms with contradicting conclusions on surface albedo response to precipitation changes. Recent improvements in the calibration and quantitative exploitation of archived Meteosat data for the retrieval of surface albedo have permitted to compare surface albedo of 1884, the driest year of the 80s, with year 2003 which had similar precipitation rate than conditions prevailing prior to the 80s drought. This analysis reveals detailed information on the geographical extension and magnitude of the surface albedo increase during from the 80s drought. A mean zonal increase in broadband surface albedo of about 0.06 between 1984 and 2003 has been estimated from the analysis of Meteosat observations. Regions particularly affected by the 1980s drought are essentially located into a narrow band of about 2° width along 16°N running from 18°W up to 20°E. Within this geographical area, surface albedo changes are not homogeneous and largest differences might locally exceed 0.15 whereas other places remained almost unaffected. The variety of previously published results might be explained by these important spatial variations observed around 16°N.more
The European climatological high-resolution gauge-adjusted radar precipitation dataset, EURADCLIM, addresses the need for an accurate (sub)daily preci…The European climatological high-resolution gauge-adjusted radar precipitation dataset, EURADCLIM, addresses the need for an accurate (sub)daily precipitation product covering 78 % of Europe at a high spatial resolution. A climatological dataset of 1 and 24 h precipitation accumulations on a 2 km grid is derived for the period 2013 through 2020. The starting point is the European Meteorological Network (EUMETNET) Operational Program on the Exchange of Weather Radar Information (OPERA) gridded radar dataset of 15 min instantaneous surface rain rates, which is based on data from, on average, 138 ground-based weather radars. First, methods are applied to further remove non-meteorological echoes from these composites by applying two statistical methods and a satellite-based cloud-type mask. Second, the radar composites are merged with the European Climate Assessment & Dataset (ECA&D) with potentially similar to 7700 rain gauges from National Meteorological and Hydrological Services (NMHSs) in order to substantially improve its quality. Characteristics of the radar, rain gauge and satellite datasets are presented, as well as a detailed account of the applied algorithms. The clutter-removal algorithms are effective while removing few precipitation echoes. The usefulness of EURADCLIM for quantitative precipitation estimation (QPE) is confirmed by comparison against rain gauge accumulations employing scatter density plots, statistical metrics and a spatial verification. These show a strong improvement with respect to the original OPERA product. The potential of EURADCLIM to derive pan-European precipitation climatologies and to evaluate extreme precipitation events is shown. Specific attention is given to the remaining artifacts in and limitations of EURADCLIM. Finally, it is recommended to further improve EURADCLIM by applying algorithms to 3D instead of 2D radar data and by obtaining more rain gauge data for the radar-gauge merging. The EURADCLIM 1 and 24 h precipitation datasets are publicly available at https://doi.org/10.21944/7ypj-wn68 (Overeem et al., 2022a) and https://doi.org/10.21944/1a54-gg96 (Overeem et al., 2022b).more
Most radiation schemes in weather and climate models use the “correlated k distribution” (CKD) method to treat gas absorption, which approximates a br…Most radiation schemes in weather and climate models use the “correlated k distribution” (CKD) method to treat gas absorption, which approximates a broadband spectral integration by N pseudo-monochromatic calculations. Larger N means more accuracy and a wider range of gas concentrations can be simulated but at greater computational cost. Unfortunately, the tools to perform this efficiency-accuracy trade-off (e.g. to generate separate CKD models for applications such as short-range weather forecasting to climate modelling) are unavailable to the vast majority of users of radiation schemes. This paper describes the experimental protocol for the Correlated K-Distribution Model Intercomparison Project (CKDMIP), whose purpose is to use benchmark line-by-line calculations: (1) to evaluate the accuracy of existing CKD models, (2) to explore how accuracy varies with N for CKD models submitted by CKDMIP participants, (3) to understand how different choices in the way that CKD models are generated affect their accuracy for the same N, and (4) to generate freely available datasets and software facilitating the development of new gas-optics tools. The datasets consist of the high-resolution longwave and shortwave absorption spectra of nine gases for a range of atmospheric conditions, realistic and idealized. Thirty-four concentration scenarios for the well-mixed greenhouse gases are proposed to test CKD models from palaeo- to future-climate conditions. We demonstrate the strengths of the protocol in this paper by using it to evaluate the widely used Rapid Radiative Transfer Model for General Circulation Models (RRTMG).more