Solar resource data derived from satellite imagery are widely available nowadays, either as an open-source or paid database. This article is intended …Solar resource data derived from satellite imagery are widely available nowadays, either as an open-source or paid database. This article is intended to assess open-source databases, which cover the region of Indonesia. Here, four known solar resource databases, which spatially cover the Indonesian archipelago, have been used, namely, Prediction of Worldwide Energy Resource (POWER), Surface Solar Radiation–Heliosat-East (SARAH-E), CM SAF Cloud, Albedo, Radiation edition 2 (CLARA-A2), and SolarGIS. In addition, a minor portion of the Meteonorm database by Meteotest, around five sample points across Indonesia, has been assessed in terms of coherency to the four mentioned databases. Correlation coefficient and relative bias of the multiyear monthly mean annual cycle global horizontal irradiation (GHI) between pairs of databases are inspected. Three out of four databases are then validated through the available irradiation ground measurement data provided by the World Radiation Data Centre (WRDC). The correlation between each pair varies mostly between 0.7 and 1, which shows that the four databases to a certain extent agree on how the intermonthly variation would behave throughout the year. On the other hand, the validation result reveals that the three databases, i.e., POWER, CLARA-A2, and SARAH-E, are suffering from positive bias error ranging from 3% to 7%. Despite that fact, the correlation between measured and estimated values is still acceptable with SARAH-E showing the best performance among the three. Careful selections and adjustment enable the possibility of these databases to be utilized as a tool for depicting interannual and intermonthly variations of solar irradiation throughout the Indonesian archipelago.more
Four parameterizations, distinguishing between land and ocean, have been developed to simulate global distributions of thundercloud streamer corona di…Four parameterizations, distinguishing between land and ocean, have been developed to simulate global distributions of thundercloud streamer corona discharges (also known as Blue LUminous Events or BLUEs) mainly producing bluish optical emissions associated with the second positive system of N2 accompanied by no (or hardly detectable) 777.4 nm light emission. BLUEs occur globally about 12 times less frequently (Soler et al., 2022) than lightning flashes. The four schemes are based on non-linear functions of the cloud-top height (CTH), the product of the convective available potential energy (CAPE) and total precipitation (TP), the product of CAPE and specific cloud liquid water content (CLWC), and the product of CAPE and specific cloud snow water content (CSWC). Considering that thunderstorms occur on hourly timescales, these parameterizations have been tested using hourly ERA5 data (except for CTH, not available in ERA5) for the meteorological variables considered, finding that the proposed BLUE schemes work fine and are consistent with observations by the Atmosphere–Space Interactions Monitor (ASIM). Moreover, the parameterizations have been implemented in a global chemistry–climate model that generates annual and seasonal global distributions for present-day and end of 21st century climate scenarios. Present-day predictions are in reasonable agreement with recent observations by the ASIM. Predictions for the end of the 21st century suggest BLUE occurrence rates that range between 13 % higher (∼ 3 % K−1) and 52 % higher (∼ 13 % K−1) than present-day average occurrences of BLUEs.more
We present the largest sensitivity study to date for cloud cover using the Weather Forecasting and Research model (WRF V3.7.1) on the European domain.…We present the largest sensitivity study to date for cloud cover using the Weather Forecasting and Research model (WRF V3.7.1) on the European domain. The experiments utilize the meteorological part of a large-ensemble framework, ESIAS-met (Ensemble for Stochastic Integration of Atmospheric Simulations). This work demonstrates the capability and performance of ESIAS for large-ensemble simulations and sensitivity analysis. The study takes an iterative approach by first comparing over 1000 combinations of microphysics, cumulus parameterization, planetary boundary layer (PBL) physics, surface layer physics, radiation scheme, and land surface models on six test cases. We then perform more detailed studies on the long-term and 32-member ensemble forecasting performance of select combinations. The results are compared to CM SAF (Climate Monitoring Satellite Application Facility) satellite images from EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). The results indicate a high sensitivity of clouds to the chosen physics configuration. The combination of Goddard, WRF single moments 6 (WSM6), or CAM5.1 microphysics with MYNN3 (Mellor-Yamada Nakanishi Niino level 3) or ACM2 (Asymmetrical Convective Model version 2) PBL performed best for simulating cloud cover in Europe. For ensemble-based probabilistic simulations, the combinations of WSM6 and SBU-YLin (Stony Brook University Y. Lin) microphysics with MYNN2 and MYNN3 performed best.more
The SM2RAIN algorithm developed a simple analytical relationship by inverting the soil-water equation to estimate rainfall through the knowledge of so…The SM2RAIN algorithm developed a simple analytical relationship by inverting the soil-water equation to estimate rainfall through the knowledge of soil moisture. The recently developed SM2RAIN-NWF algorithm offers an improvement in estimating rainfall by integrating the SM2RAIN algorithm and the net water flux (NWF) model. The Advanced Scatterometer (ASCAT) soil moisture products were used to estimate rainfall and evaluate the reliability of the SM2RAIN-NWF algorithm compared to the SM2RAIN on a national scale. Besides, the impact of Land cover-Soil texture-Climate (LSC) characteristics and the intensity of rainfall (four classes of intensity) on the performance of algorithms were discussed. Five performance metrics, including Correlation Coefficient (R), Kling–Gupta (KGE), Root Mean Square Error (RMSE), False Alarm Ration (FAR), and Probability of Detection (POD) were used to validate the estimated cumulative 5-, 14-, and 30-day rainfall. Furthermore, the effect of evapotranspiration (ET) and drainage terms were investigated in the performance of rainfall estimation through the SM2RAIN-NWF algorithm for the first time on a national scale. Results showed the rainfall estimations through the SM2RAIN-NWF algorithm improved approximately up to 7.5% in each accumulation (e.g. rainfall aggregation intervals (AGGR) 5 to 14 and 14 to 30) based on R and KGE indices. In addition, the SM2RAIN-NWF improved rainfall estimations up to 50% based on the KGE index in the southern half of Iran (arid and semi-arid climate) compared to the SM2RAIN estimates. The comprehensive evaluation and uncertainty analysis of rainfall estimations under the supervised classification of 11 LSC and 4 rainfall classes also showed the calibration of the SM2RAIN-NWF was highly affected by environmental and climatic circumstances. Uncertainty analysis showed the SM2RAIN-NWF algorithm can estimate rainfall more consistently in the five LSC classes namely 1) barren-clay loam-arid-desert, 2) barren-loam-arid-steppe, 3) barren-clay loam-arid-steppe, 4) urban-clay loam-arid-desert, and 5) urban-loam-arid-steppe. Similarly, estimating rainfall in the region with precipitation under 267 mm/year can be retrieved more reliably through the SM2RAIN-NWF algorithm. Results obtained from the ET analysis revealed an insignificant (more
This paper addresses long-term historical changes in solar irradiance in West Africa (3 to 20∘ N and 20∘ W to 16∘ E) and the implications for photovol…This paper addresses long-term historical changes in solar irradiance in West Africa (3 to 20∘ N and 20∘ W to 16∘ E) and the implications for photovoltaic systems. Here, we use satellite irradiance (Surface Solar Radiation Data Set – Heliosat, Edition 2.1 – SARAH-2.1) and temperature data from a reanalysis (ERA5) to derive photovoltaic yields. Based on 35 years of data (1983–2017), the temporal and regional variability as well as long-term trends in global and direct horizontal irradiance are analyzed. Furthermore, a detailed time series analysis is undertaken at four locations.
According to the high spatial resolution SARAH-2.1 data record (0.05∘×0.05∘), solar irradiance is largest (up to a 300 W m−2 daily average) in the Sahara and the Sahel zone with a positive trend (up to 5 W m−2 per decade) and a lower temporal variability (more
Khaykin, S. M.; Funatsu, B. M.; Hauchecorne, A.; Godin-Beekmann, S.; Claud, C.; Keckhut, P.; Pazmino, A.; Gleisner, H.; Nielsen, J. K.; Syndergaard, S.; Lauritsen, K. B.
Temperature changes in the lower and middle stratosphere during 2001–2016 are evaluated using measurements from GPS Radio Occultation (RO) and Advance…Temperature changes in the lower and middle stratosphere during 2001–2016 are evaluated using measurements from GPS Radio Occultation (RO) and Advanced Microwave Sounding Unit (AMSU) aboard the Aqua satellite. After downsampling of GPS-RO profiles according to the AMSU weighting functions, the spatially and seasonally resolved trends from the two data sets are in excellent agreement. The observations indicate that the middle stratosphere has cooled in the time period 2002–2016 at an average rate of −0.14 ± 0.12 to −0.36 ± 0.14 K/decade, while no significant change was found in the lower stratosphere. The meridionally and vertically resolved trends from high-resolution GPS-RO data exhibit a marked interhemispheric asymmetry and highlight a distinct boundary between tropospheric and stratospheric temperature change regimes matching the tropical thermal tropopause. The seasonal pattern of trend reveals significant opposite-sign structures at high and low latitudes, providing indication of seasonally varying change in stratospheric circulation.more