Photovoltaic power potential in West Africa using long-term satellite data

Author(s):
Neher, Ina; Crewell, Susanne; Meilinger, Stefanie; Pfeifroth, Uwe; Trentmann, Jörg
Publication title: Atmospheric Chemistry and Physics
2020
 | Volume: 20 | Issue: 21
2020
DOI: 10.5194/acp-20-12871-2020
Abstract:
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
Application Atmosphere CM-SAF Climate Data Records

Postmillennium changes in stratospheric temperature consistently resolved by GPS radio occultation and AMSU observations: Temperature Change from GPS-RO and AMSU

Author(s):
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.
Publication title: Geophysical Research Letters
2017
 | Volume: 44 | Issue: 14
2017
DOI: 10.1002/2017GL074353
Abstract:
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
Application Atmosphere Climate Data Records ROM-SAF

Potential cloud precipitation capacity in typical regions over China

Author(s):
Mo, Shuying; Zhao, Pengguo; Zhao, Chuanfeng; Zhou, Yunjun
Publication title: Atmospheric Research
2024
 | Volume: 311
2024
DOI: 10.1016/j.atmosres.2024.107653
Abstract:
Based on the CLoud, Albedo and RAdiation dataset, AVHRR-based, version 2 (CLARA-A2), Tropical Rainfall Measuring Mission 3B43 (TRMM-3B43), and Europea… Based on the CLoud, Albedo and RAdiation dataset, AVHRR-based, version 2 (CLARA-A2), Tropical Rainfall Measuring Mission 3B43 (TRMM-3B43), and European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) reanalysis data, the potential cloud precipitation capacity (PCPA) of typical regions in China is compared, and the relationship between impact factors and PCPA is discussed. Results have suggested that the Tarim Basin (TB) has scarce cloud water resources, while cloud water path (CWP) values are higher in South China (SC) and Sichuan Basin (SB) under the influence of the East Asian monsoon. Moreover, different typical regions of China exhibit varying dependencies on the ice water path (IWP) and liquid water path (LWP). There is a strong correlation between the IWP and precipitation in the Tibet Plateau (TP), Northeast China (NE), SC, and SB. The precipitation in TB demonstrates a more pronounced correlation with the LWP. Through a comparison of the correlation between PCPA and influencing factors in different typical regions of China, it is found that convective available potential energy (CAPE), surface latent heat flux (SLHF), surface sensible heat flux (SSHF), and 0–3 km relative humidity (RH) exhibit stronger correlation with PCPA than 2 m temperature (T2m) and 2–5 km vertical wind shear (SHEAR). Further investigation revealed that the joint effect of CAPE, RH, and SLHF has a pronounced effect on PCPA, particularly during spring and autumn. Additionally, the PCPA of TP exhibits significant dependency on the joint effect of these three influential factors. Furthermore, the ratio of LWP to IWP (RLI) also affects PCPA. In spring and autumn, the PCPA of TB and NC exhibits a positive correlation with RLI, whereas the PCPA of TP, SC, NE, and SB shows a negative correlation with RLI. In summer, the PCPA of TB and SC exhibits a notably negative correlation with RLI. This study deepens the understanding of the formation mechanism of cloud precipitation in typical regions of China, provides the basis for climate forecast and improves the accuracy of weather forecast. more
Application Atmosphere CM-SAF Climate Data Records

Polar stratospheric nitric acid depletion surveyed from a decadal dataset of IASI total columns

Author(s):
Wespes, Catherine; Ronsmans, Gaetane; Clarisse, Lieven; Solomon, Susan; Hurtmans, Daniel; Clerbaux, Cathy; Coheur, Pierre-François
Publication title: Atmospheric Chemistry and Physics
2022
 | Volume: 22 | Issue: 16
2022
DOI: 10.5194/acp-22-10993-2022
Abstract:
Abstract. In this paper, we exploit the first 10-year data record (2008–2017) of nitric acid (HNO3) total columns measured by the IASI-A/MetOp infrare… Abstract. In this paper, we exploit the first 10-year data record (2008–2017) of nitric acid (HNO3) total columns measured by the IASI-A/MetOp infrared sounder, characterized by an exceptional daily sampling and a good vertical sensitivity in the lower-to-mid stratosphere (around 50 hPa), to monitor the relationship between the temperature decrease and the observed HNO3 loss that occurs each year in the Antarctic stratosphere during the polar night. Since the HNO3 depletion results from the formation of polar stratospheric clouds (PSCs), which trigger the development of the ozone (O3) hole, its continuous monitoring is of high importance. We verify here, from the 10-year time evolution of HNO3 together with temperature (taken from reanalysis at 50 hPa), the recurrence of specific regimes in the annual cycle of IASI HNO3 and identify (for each year) the day and the 50 hPa temperature (“drop temperature”) corresponding to the onset of strong HNO3 depletion in the Antarctic winter. Although the measured HNO3 total column does not allow for the uptake of HNO3 by different types of PSC particles along the vertical profile to be differentiated, an average drop temperature of 194.2 ± 3.8 K, close to the nitric acid trihydrate (NAT) existence threshold (∼ 195 K at 50 hPa), is found in the region of potential vorticity lower than −10 × 10−5 Km2kg-1s-1 (similar to the 70–90∘ S equivalent latitude region during winter). The spatial distribution and interannual variability of the drop temperature are investigated and discussed. This paper highlights the capability of the IASI sounder to monitor the evolution of polar stratospheric HNO3, a key player in the processes involved in the depletion of stratospheric O3. more
AC-SAF Application Atmosphere

Potential Modulation of Aerosol on Precipitation Efficiency in Southwest China

Author(s):
Zhao, Pengguo; Liu, Xiaoran; Zhao, Chuanfeng
Publication title: Remote Sensing
2024
 | Volume: 16 | Issue: 8
2024
DOI: 10.3390/rs16081445
Abstract:
The aerosol–cloud–precipitation correlation has been a significant scientific topic, primarily due to its remarkable uncertainty. However, the possibl… The aerosol–cloud–precipitation correlation has been a significant scientific topic, primarily due to its remarkable uncertainty. However, the possible modulation of aerosol on the precipitation capacity of clouds has received limited attention. In this study, we utilized multi-source data on aerosol, cloud properties, precipitation, and meteorological factors to investigate the impact of aerosols on precipitation efficiency (PE) in the Sichuan Basin (SCB) and Yun-nan-Guizhou Plateau (YGP), where the differences between terrain and meteorological environment conditions were prominent. In the two study regions, there were significant negative correlations between the aerosol index (AI) and PE in spring, especially in the YGP, while the correlations between the AI and PE in other seasons were not as prominent as in spring. In spring, aerosol significantly inhibited both the liquid water path (LWP) and the ice water path (IWP) in the YGP, but negatively correlated with the IWP and had no significant relationship with the LWP in the SCB. Aerosol inhibited precipitation in the two regions mainly by reducing cloud droplet effective radius, indicating that warm clouds contributed more to precipitation in spring. The suppressive impact of aerosols on precipitation serving as the numerator of PE is greater than that of the cloud water path as the denominator of PE, resulting in a negative correlation between aerosol and PE. The AI–PE relationship is significantly dependent on meteorological conditions in the YGP, but not in the SCB, which may be related to the perennial cloud cover and stable atmosphere in the SCB. In the future, as air quality continues to improve, precipitation efficiency may increase due to the decrease in aerosol concentration, and of course, the spatio-temporal heterogeneity of the aerosol–cloud–precipitation relationship may become more significant. more
Application Atmosphere CM-SAF Climate Data Records

Precipitation efficiency of cloud and its influencing factors over the Tibetan plateau

Author(s):
Zhao, P.; Xiao, H.; Liu, J.; Zhou, Y.
Publication title: International Journal of Climatology
2021
2021
DOI: 10.1002/joc.7251
Abstract:
The basic characteristics of cloud water, precipitation, and the dependence of precipitation efficiency (PE) on the influencing factors over the Tibet… The basic characteristics of cloud water, precipitation, and the dependence of precipitation efficiency (PE) on the influencing factors over the Tibetan Plateau (TP) are investigated. Results found that the liquid water path shows a significant downward trend in winter over the TP, and the ice water path shows a significant upward trend in the pre-monsoon and winter seasons and a significant downward trend in the monsoon season in the western TP from 1998 to 2015. In the eastern TP, the precipitation in the monsoon season also shows a significant downward trend, which may be related to the weakening of the South Asian monsoon. Results have determined that precipitation depends more on the ice water cloud than on the liquid water cloud over the TP. Moreover, the convective available potential energy (CAPE) and the low-tropospheric relative humidity (RH) are two environmental factors that have a prominent influence on the PE. During the monsoon season, higher CAPE and RH were conducive to a larger PE over the TP. The results suggest that the CAPE has a positive effect on the PE, which means that the PE is directly dependent on the convective precipitation, mainly due to the frequent convective activity and dominant convective precipitation over the TP. © 2021 Royal Meteorological Society more
Application Atmosphere CM-SAF Climate Data Records

Precipitation regime classification based on cloud-top temperature time series for spatially-varied parameterization of precipitation models

Author(s):
Lu, S.; ten Veldhuis, M.-C.; van de Giesen, N.; Heemink, A.; Verlaan, M.
Publication title: Remote Sensing
2020
 | Volume: 12 | Issue: 2
2020
DOI: 10.3390/rs12020289
Abstract:
Satellite and reanalysis precipitation products perform poorly over regions with low-density ground observation networks. In order to improve space-de… Satellite and reanalysis precipitation products perform poorly over regions with low-density ground observation networks. In order to improve space-dependent parameterization of precipitation estimation models in data-scarce environments, the delineation boundaries of precipitation regimes should be accurately identified. Existing approaches to characterize precipitation regimes by seasonal or other climatological properties do not account for small scale spatial-temporal variability. Precipitation time series can be used to account for this small-scale variability in regime classification. Unfortunately, precipitation products with global coverage perform poorly at small time scales over data scarce regions. A methodology of using satellite-based cloud-top temperature (CTT) time series as a proxy of precipitation time series for precipitation regime classification was developed, and its potential and uncertainty were analyzed. A precipitation regime in this study was defined on the basis of characteristic small-scale temporal distribution and variability of precipitation at a given place. Dynamic time warping was used to calculate the distance between two time series. Criteria to select the optimal temporal scale of time series for clustering and the number of clusters were also developed. The method was validated over Germany and applied to Tanzania, characterized by complex climatology and low density ground observations. This approach was evaluated against precipitation regime classification based on a satellite precipitation product. Results show that CTT outcompetes satellite-based precipitation for classification of precipitation regime classification. The CTT-based classification can be used as precursor to spatially adapted precipitation estimation algorithms where parameters are calibrated by gauge data or other ground-based precipitation observations, and parameterization can be used for satellite-precipitation estimates, precipitation forecasts in numerical or stochastic weather models, etc. © 2020 by the authors. more
Application Atmosphere CM-SAF Climate Data Records

Predicted sea-ice loss will terminate Iceland's driftwood supply by 2060 CE

Author(s):
Kolar, Tomas; Rybnicek, Michal; Eggertsson, Olafur; Kirdyanov, Alexander; Cejka, Tomas; Cermak, Petr; Zid, Tomas; Vavrcik, Hanus; Buentgen, Ulf
Publication title: GLOBAL AND PLANETARY CHANGE
2022
 | Volume: 213
2022
DOI: 10.1016/j.gloplacha.2022.103834
Abstract:
Driftwood supply was a pivotal factor for the Norse expansion in medieval times and still exhibits an essential resource for Arctic settlements. The p… Driftwood supply was a pivotal factor for the Norse expansion in medieval times and still exhibits an essential resource for Arctic settlements. The physical causes and societal consequences of long-term changes in the distribution of Arctic driftwood are, however, poorly understood. Here, we use dendrochronology to reconstruct the age and origin of 289 driftwood samples that were collected at remote shorelines in northeast Iceland. Based on 240 reference tree-ring width chronologies from the boreal forest zone, and an overall provenance success of 73%, we show that most of the driftwood is pine and larch from the Yenisei catchment in central Siberia. Our study reveals an abrupt decline in the amount of driftwood reaching Iceland since the 1980s, which is corroborated by the experience of local farmers and fishers. Despite the direct and indirect effects of changes in both, logging activity across Siberia as well as Arctic Ocean currents, the predicted amount of sea-ice loss under anthropogenic global warming is likely to terminate Iceland's driftwood supply by 2060 CE. more
Application Climate Data Records Cryosphere OSI-SAF

Predicting September Arctic Sea Ice: A Multimodel Seasonal Skill Comparison

Author(s):
Bushuk, M.; Ali, S.; Bailey, D.A.; Bao, Q.; Batté, L.; Bhatt, U.S.; Blanchard-Wrigglesworth, E.; Blockley, E.; Cawley, G.; Chi, J.; Counillon, F.; Coulombe, P.G.; Cullather, R.I.; Diebold, F.X.; Dirkson, A.; Exarchou, E.; Göbel, M.; Gregory, W.; Guemas, V.; Hamilton, L.; He, B.; Horvath, S.; Ionita, M.; Kay, J.E.; Kim, E.; Kimura, N.; Kondrashov, D.; Labe, Z.M.; Lee, W.; Lee, Y.J.; Li, C.; Li, X.; Lin, Y.; Liu, Y.; Maslowski, W.; Massonnet, F.; Meier, W.N.; Merryfield, W.J.; Myint, H.; Acosta Navarro, J.C.; Petty, A.; Qiao, F.; Schröder, D.; Schweiger, A.; Shu, Q.; Sigmond, M.; Steele, M.; Stroeve, J.; Sun, N.; Tietsche, S.; Tsamados, M.; Wang, K.; Wang, J.; Wang, W.; Wang, Y.; Wang, Y.; Williams, J.; Yang, Q.; Yuan, X.; Zhang, J.; Zhang, Y.
Publication title: Bulletin of the American Meteorological Society
2024
 | Volume: 105 | Issue: 7
2024
DOI: 10.1175/BAMS-D-23-0163.1
Abstract:
This study quantifies the state of the art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multimodel dataset of retrospec… This study quantifies the state of the art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multimodel dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 17 dynamical models. Prediction skill is compared over the period 2001–20 for predictions of pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on 1 June, 1 July, 1 August, and 1 September. This diverse set of statistical and dynamical models can individually predict linearly detrended pan-Arctic SIE anomalies with skill, and a multimodel median prediction has correlation coefficients of 0.79, 0.86, 0.92, and 0.99 at these respective initialization times. Regional SIE predictions have similar skill to pan-Arctic predictions in the Alaskan and Siberian regions, whereas regional skill is lower in the Canadian, Atlantic, and central Arctic sectors. The skill of dynamical and statistical models is generally comparable for pan-Arctic SIE, whereas dynamical models outperform their statistical counterparts for regional and local predictions. The prediction systems are found to provide the most value added relative to basic reference forecasts in the extreme SIE years of 1996, 2007, and 2012. SIE prediction errors do not show clear trends over time, suggesting that there has been minimal change in inherent sea ice predictability over the satellite era. Overall, this study demonstrates that there are bright prospects for skillful operational predictions of September sea ice at least 3 months in advance. SIGNIFICANCE STATEMENT: The observed decline of Arctic sea ice extent has created an emerging need for predictions of sea ice on seasonal time scales. This study provides a comparison of September Arctic sea ice seasonal prediction skill across a diverse set of dynamical and statistical prediction models, quantifying the state of the art in the rapidly growing sea ice prediction research community. We find that both dynamical and statistical models can skillfully predict September Arctic sea ice 0–3 months in advance on pan-Arctic, regional, and local spatial scales. Our results demonstrate that there are bright prospects for skillful operational seasonal predictions of Arctic sea ice and highlight a number of crucial prediction system design aspects to guide future improvements. © 2024 American Meteorological Society. more
Application Climate Data Records Cryosphere OSI-SAF

Prescriptive analytics for low and high water management in German waterways

Author(s):
Brum, M.; Meißner, D.; Klein, B.; Hohenrainer, J.; Schwanenberg, D.; Patzke, S.
Publication title: At-Automatisierungstechnik
2024
 | Volume: 72 | Issue: 6
2024
DOI: 10.1515/auto-2024-0013
Abstract:
The real-time management of multi-purpose storage reservoirs aims at an efficient operation of existing hydraulic infrastructure. This management proc… The real-time management of multi-purpose storage reservoirs aims at an efficient operation of existing hydraulic infrastructure. This management process can be structured as a prescriptive analytics setup that considers both current and predicted system states to recommend actions and outline potential implications. In application to a reservoir and river system, it combines hydrological modelling components for the system schematization, observations and data assimilation for the identification of the current system state, meteorological and hydrological predictions as well as optimization-based techniques to support decision-making regarding reservoir operations. In this paper, we present the application of such a framework to the short-term management of the Eder and Diemel storage reservoirs. These reservoirs are operated by the German Federal Waterways and Shipping Administration (WSV) with the primary goal to support navigation in the River Weser during low flow periods. In addition, partially conflicting objectives such as flood protection, energy generation and recreation are considered. The implementation includes an explicit consideration of forecast uncertainty and its impact on the decision-making by using probabilistic forecasts in combination with a multi-stage stochastic optimization approach. We demonstrate the applicability of the approach based on low and high water use cases. Special attention is paid on the benefits of the probabilistic forecast in combination with the multi-stage stochastic optimization versus a deterministic setup. It provides an explicit translation of the forecast uncertainty in the decision variables, in this case the reservoir releases helping the operators to better anticipate the range of future release decisions. Furthermore, the stochastic approach is expected to provide more stable decisions in an operational setting, based on more stable forecasts by considering various possible realizations of the future instead of picking a single one, which gets random after 4-5 days. © 2024 Walter de Gruyter GmbH, Berlin/Boston. more
Application Atmosphere CM-SAF Climate Data Records
Subscribe to