Small island ecosystems are threatened by climate change in several ways. This includes the Galapagos archipelago in the Tropical Eastern Pacific, where limited freshwater makes the islands dependent on atmospheric supply through precipitation. However, precipitation distribution remains highly uncertain due to the lack of operational observation systems, and it is unclear how climate change will affect availability. Given its location, climate impacts are closely tied to changes in El Nino Southern Oscillation extremes during El Nino and La Nina years. Using a new measurement network incorporating a vertical rain radar profiler, we investigated seasonal rainfall changes (hot and cool) by analyzing El Nino/La Nina-like years, serving as surrogate for a locally warmer and locally cooler world. Our analysis demonstrates that in a locally warmer world, precipitation is increasing in both seasons. Rainfall characteristics and satellite-retrievals convective cloud frequency indicate more convective activity, intensifying heavy rainfall, especially during the hot season. In the cool season, drizzle is replaced by light rain throughout the vertical profile. In a locally cooler world, the hot season's typical midday rainfall maximum is replaced by oscillating, short-wavelength patterns and lower totals. Interestingly, the cool season in a La Nina-dominated world exhibits slightly higher rainfall than a neutral year, likely due to better condensation conditions of the advected moist air at lower air temperatures. Overall, results suggest improved total rainfall supply in a locally warmer world, but torrential rain could endanger the islands in the hot season. Furthermore, cool seasons shift from drizzle to light rain, though totals remain low overall.

The Central European Refined analysis (CER) was developed in 2016 as a high-resolution, reanalysis-based, gridded dataset for Central Europe. The second version (CER v2) aims to further improve the performance of the CER with a particular focus on precipitation data for the metropolitan region Berlin-Brandenburg. The simulation setup consists of two-way nested, cascaded domains for Germany (10 km grid spacing) and the region Berlin-Brandenburg (2 km grid spacing) and employs a daily re-initialization approach. Major changes from the precursor version include the use of ECMWF-ERA5 reanalysis forcing data and a newer WRF version, allowing for the production of longer time series. To further improve the precipitation performance for the CER v2 we performed sensitivity experiments with five cumulus and five microphysics schemes. The results of these test simulations were evaluated using one year of daily precipitation data at 244 stations of the German Weather Service (DWD) in the 2 km domain of the model. The best average performance was achieved for a combination of the conventional Kain-Fritsch cumulus and the Thompson microphysics scheme. Using this setup, we simulated the precipitation conditions for 30 years (1991-2020) and evaluated monthly and annual precipitation averages against station and radar data by the DWD. Here, the CER v2 showed a significant reduction in deviations and mean bias compared to the previous version. Based on the spatial resolution of the ERA5 data, we resampled the CER v2 and observational data to compare the performance of both datasets. We observed a wet bias in the ERA5 precipitation data for this region, which was significantly reduced in the CER v2. Results of monthly averages indicated a comparable performance to ERA5 data throughout most of the year. Deviations from the observational data were typically higher during the summer months. However, due to the significant bias reduction and the high spatial resolution, the CER v2 could provide important insights about the local- to mesoscale precipitation dynamic of this region.

Like many small oceanic islands, the Galapagos archipelago, renowned for its unique geographic location and exceptional endemic biodiversity, faces significant challenges under climate change. In particular, the atmospheric water supply for the ecosystem and the local population is under threat, with clouds and rain playing an important role in ensuring freshwater availability under climate change. Better planning of adaptation measures would require climate data on clouds as a prerequisite for precipitation and rainfall at high spatio-temporal resolution, which are not available in this area. Operational products such as satellite derived cloud and precipitation products or reanalysis data are widely used to compensate for the lack of local data availability but are often poorly suited for regional applications. In the current study, we aim to generate high quality area-wide cloud information to distinguish ecoclimatic cloud zones that may require different adaptation measures to climate change. To address this issue, we have developed a new physical rule-based cloud mask retrieval specifically tailored for the Galapagos Archipelago, based on data from the third generation GOES-16 Advanced Baseline Imager (ABI) geostationary satellite. The new Galapagos Rainfall Retrieval (GRR) cloudmask was tested against independent observational data and compared to both the operational GOES-16 ACM (ABI Clear sky Mask) and the MODIS cloudmask benchmark cloud mask. Our test results confirm that the GRR-cloudmask (Probability of Detection POD = 0.94, Critical Success Index CSI = 0.92-0.93) clearly outperforms the operational ACM-cloudmask (POD = 0.56-0.68, CSI = 0.55-0.67). Area-wide tests against the MODIS cloud mask showed a CSI of 0.72 and a POD of 0.74 for the ACM, which is superior to the GOES-16 ACM-cloudmask. We produced cloud frequency maps for all months and day slots and analysed cloud frequency using ancillary meteorological data. In general, the cool season (Jun-Dec) / night shows much higher cloud frequencies than the warm season (Jan-May) / daytime. However, regional cloud patterns differ along a west-to-east and south-tonorth gradient, depending on complex interactions of forcing parameters such as exposure to the main circulation, sea surface temperature zones, altitude and land cover. A k-mean cluster analysis resulted in nine ecoclimatic cloud zones over land, which are much more differentiated than the widely used four-zone classification. The results will help to develop more site-specific climate change adaptation planning for the iconic Galapagos National Park.

The Gal & aacute;pagos Archipelago exhibits a unique and high endemic biodiversity that is strongly affected by climate variability, mainly caused by the El Ni & ntilde;o-Southern Oscillation phenomenon. However, there exist few climate datasets for the islands and a long-term climate dataset at the meso-scale is not available. We present the Gal & aacute;pagos Archipelago Refined analysis data-set (GAR), a dynamically downscaled dataset of 2 h temporal resolution and 2 km horizontal grid spacing for the Gal & aacute;pagos Archipelago, that is based on ERA5 reanalysis data. The GAR is produced by the Weather Research and Forecasting Model (WRF V.4.3.3). Sensitivity experiments focused on precipitation and air temperature led to the selection of a suitable model setup for the region, which was developed using observational data from the Darwin Measurement Network (DMN) and the Charles Darwin Research Station (CDRS). We evaluated the performance of the model by reproducing the measured daily mean values at the Cerro Crocker (CC) and Puerto Ayora (PA) stations for the period from 01 April 2022 to 31 March 2023. The results show very strong correlations (rho(T,CC) = 0.94 and rho(T,PA) = 0.94) for air temperatures. For daily precipitation rates, measured by rain gauges, the GAR yields medium to strong correlation (p(Pg,CC )= 0.66 and p(Pg,PA) = 0.44). Specific humidity very strongly correlates with the measurements (p(SH,CC) = 0.88 and p(SH,PA) = 0.97). Analysis of the spatial patterns of precipitation, specific humidity, and temperature on the meso-scale indicated a strong dependency on altitude. Precipitation for the dry season is triggered mainly by orographic lifting, while wet season precipitation is driven by thermally induced convection. The GAR fulfils the need for high spatio-temporal resolution data on the Gal & aacute;pagos climate and serves as a valuable source for scientific research in this area. The GAR data are publicly available, and together with the downscaling approach evaluated here, this dataset can easily be extended into the future.

The Central Europe Refined Analysis (CER) was developed in 2016 as a high-resolution, reanalysis-based, gridded data set for Central Europe and the Berlin-Brandenburg metropolitan region of Germany in particular. The data set was successfully used for investigations of near-surface air temperatures, but showed inaccuracies in the simulated precipitation compared to station measurements. In this study we characterize the development of the second version of this data set (CER v2), which focused primarily on improving the performance of precipitation products. This new version uses an updated version of the WRF model and new ERA5 forcing data. Comprehensive sensitivity studies were carried out to optimize the physical parameterization of daily precipitation results. The combination of the Kain-Fritsch cumulus and the Thompson microphysics scheme was selected for the CER v2 due to the reduction of the domain average Mean Deviation (MD) by 77% and the Root Mean Squared Deviation (RMSD) by 18% when compared to the original CER setup. The validation of 30 years (1991-2020) of the CER v2 precipitation data against station data by the German Weather Service (DWD) revealed that the domain median RMSD was the lowest during the winter with seasonal median RMSD of 0.24 mm d-1 and the highest during the summer with 0.71 mm d-1 . The comparison against 20 years of radar data (2001-2020) identified the highest seasonal RMSD during the summer along the western and southern border of the model domain and in the northeast of Berlin with values above 1 mm d-1 . CER v2 data was compared to the CER v1 and ERA5 data for the time period of 2001-2018 on a resampled 0.25 degrees grid. In terms of the domain median RMSD and MD, the CER v2 outperformed the CER v1 and the ERA5 during the winter, spring and autumn. However during summer, the domain median CER v2 RMSD was 46% higher than for ERA5. One of the biggest advantages of the data set is the substantial reduction in the domain median annual MD, which was about 94% lower than for the ERA5 forcing data. Due to its longer available time series and increased performance compared to the previous version, the CER v2 could provide important insights about the local- to mesoscale precipitation dynamics of the study region and serve as a foundation for data-driven hydrological models.

Clouds play an important role in the climate system; nonetheless, the relationship between climate change in general and regional cloud occurrence is not yet well understood. This particularly holds for remote areas such as the iconic Galapagos archipelago in Ecuador. As a first step towards a better understanding, we analyzed the spatio-temporal patterns of cloud cover over Galapagos. We found that cloud frequency and distribution exhibit large inter- and intra-annual variability due to the changing influence of climatic drivers (trade winds, sea surface temperature, El Niño/La Niña events) and spatial variations due to terrain characteristics and location within the archipelago. The highest cloud frequencies occur in mid-elevations on the slopes exposed to the southerly trade winds (south-east slopes). Towards the highlands ( >900 m a.s.l), cloud frequency decreases, with a sharp leap towards high-level crater areas mainly on Isabela Island that frequently immerse into the trade inversion layer. With respect to the diurnal cycle, we found a lower cloud frequency over the islands in the evening than in the morning. Seasonally, cloud frequency is higher during the hot season (January–May) than in the cool season (June–December). However, spatial differences in cloudiness were more pronounced during the cool season months. We further analyzed two periods beyond average atmospheric forcing. During El Niño 2015, the cloud frequency was higher than usual, and differences between altitudes and aspects were less pronounced. La Niña 2007 led to negative anomalies in cloud frequency over the islands, with intensified differences between altitude and aspect.

<p>During heat waves, urban dwellers are exposed to elevated temperatures, especially during night-time when urban heat island (UHI) effects are most intense. Climate change is expected to further increase heat-stress hazards. There are only few studies that have investigated how UHI effects interfere with heat waves. Here, we present results from a sensitivity study in which we analyse non-linear effects of elevated meso-scale temperature forcing on micro-scale atmospheric processes. The study employs the large eddy simulation model PALM-4U. The ‘Tempelhofer Feld’ in Berlin, Germany, the largest park within the city, was used as study area. Starting point was a 24 h (plus 6 h spin-up) control simulation followed by a scenario simulation in which all temperature variables, not only air temperature, were increased by 1 K. The control simulation was configured to represent a real weather situation in an idealized form. Grid spacing was set to 10 m horizontally and 2 m vertically to resolve buildings and trees. A residential area to the east of the airport was simulated with a higher horizontal grid resolution of 2 m to investigate micro-scale atmospheric processes in more detail. The results show that the micro-scale response of near-surface air temperature to elevated meso-scale temperature forcing is not constant throughout the day with lower values during day-time and higher values during night-time, particularly in the early evening. In both simulations, the night-time inversion over the park continues into the settlement above the roof level. The study shows that there are weak non-linear effects leading to an amplification of the UHI during night-time. However, as linear effects dominate, adaptation measures with regard to heat stress may be planned on the basis of current weather and climate conditions, additionally documented by observational data, and subsequently evaluated by urban climate monitoring.</p>

In the Intergovernmental Panel on Climate Change report (IPCC), “Climate Change 2022: Impacts, Adaptation and Vulnerability” it is stated that more frequent and intense extreme events due to climate change have a significant impact on the loss and damage of nature and people, which particularly holds for precipitation. In the Galápagos archipelago, the primary source of water supply is rainfall, hence rainfall plays an important role for biodiversity and people in this iconic but remote region. The main assumption for Galapagos is that water supply is dominated by the cool season’s light Garúa rainfall originating from the Pacific stratus, which will significantly decrease under global warming conditions. At the same time, rainfall in the warm season shows large variability, particularly during extreme ENSO (El Niño-Southern Oscillation) events. While in the current decade, a decrease of strong El Niño rainfall events was observed in the eastern tropical Pacific, most (but not all) climate model projections of the CMIP6 ensemble reveal stronger El Niño rainfall under future warming. To date, short and long-term rainfall dynamics in the Galápagos are not well understood, largely due to a lack of consistent spatially-time series of meteorological in-situ observations. The research project DARWIN ("Dynamics of precipitation in transition: The water source for the Galápagos Archipelago under climate change") has recently established 11 Automatic weather stations (AWS) covering a W-E and luff-lee transects over three islands (Isabela, S. Cruz, S. Cristóbal). The location of the stations is to consider different local and regional precipitation formation mechanisms. We seek to resolve influences of the Equatorial Counter Current and the Humboldt Current, as well as the topographic exposition towards the main airstream. Furthermore, the altitudinal gradients concerning vertical dynamics of the trade inversion are considered. One main goal of the DARWIN project is to produce area-wide rainfall information by satellite retrievals and WRF dynamical downscaling. While warm-season rainfall is mainly driven by intense convection events, cool-season Garúa is assumed to be more in the drizzle intensity range. The area-wide techniques must thus properly model the very different types of occurring rain intensities in the cool and warm seasons. Hence, the observations from the AWS used as test and training data must be as accurate as possible. Beyond standard meteorology, we focus on different advanced observation principles (light, optical, radar, gauge) and their intercomparison, and warrant high-resolution measurements (up to one minute) including a vertical profiling of rainfall. The AWS stations in the Garúa zone are additionally equipped by a harp-type fog collector. The poster will present the overall structure of the project and some first results of the AWS network, with a focus on temporally high-resolution rainfall dynamics during different weather situations and precipitation types along the transects.

The hydroclimate of the Tibetan Plateau (TP) and Central Asia (CA) plays a crucial role in sustaining surface water reservoirs and thus water resources in the respective regions. In this study, we investigate the changes in Asian hydroclimate and its driving forces during specific time intervals in the last 3 Ma. We conduct high‐resolution (∼0.75° per grid cell) general circulation model ECHAM‐5 experiments with boundary conditions for the mid‐Pliocene (∼3 Ma), the Last Glacial Maximum (LGM; ∼21 ka), the mid‐Holocene (∼6 ka), and the pre‐industrial. Results suggest that seasonally relatively high precipitation rates (>1 mm day −1 ) were longer in the mid‐Pliocene and shorter in the LGM, relative to the pre‐industrial. We calculate different monsoon indices to detect changes in the intensity, strength and duration of the East Asian summer monsoon (EASM), South Asian summer monsoon (SASM), and the Indian summer monsoon (ISM), and construct climatologies of mid‐latitude high‐level westerly jet (WJ) stream occurrences based on the ECHAM5 wind fields. Our results suggest that in warm periods (e.g., mid‐Pliocene or interglacial), the WJ migrates northward earlier in the year (April) and reaches higher latitudes than in the pre‐industrial, resulting in a wetter TP and CA. During cooler periods (e.g., LGM or glacial), the WJ migrates northward later in the year (June) and remains over lower latitudes, resulting in a drier TP and CA. Increased/decreased local precipitation in TP and CA for the mid‐Pliocene/LGM experiments correlates strongly with (a) intensity, strength and duration of the EASM, SASM, and the ISM and (b) WJ latitudinal position.

<p>In the Intergovernmental Panel on Climate Change report (IPCC), “Climate Change 2022: Impacts, Adaptation and Vulnerability” it is stated that more frequent and intense extreme events due to climate change have a significant impact on the loss and damage of nature and people, which particularly holds for precipitation.</p><p>In the Galápagos archipelago, the primary source of water supply is rainfall, hence rainfall plays an important role for biodiversity and people in this iconic but remote region. The main assumption for Galapagos is that water supply is dominated by the cool season’s light Garúa rainfall originating from the Pacific stratus, which will significantly decrease under global warming conditions. At the same time, rainfall in the warm season shows large variability, particularly during extreme ENSO (El Niño-Southern Oscillation) events. While in the current decade, a decrease of strong El Niño rainfall events was observed in the eastern tropical Pacific, most (but not all) climate model projections of the CMIP6 ensemble reveal stronger El Niño rainfall under future warming.</p><p>To date, short and long-term rainfall dynamics in the Galápagos are not well understood, largely due to a lack of consistent spatially-time series of meteorological in-situ observations. The research project DARWIN ("Dynamics of precipitation in transition: The water source for the Galápagos Archipelago under climate change") has recently established 11 Automatic weather stations (AWS) covering a W-E and luff-lee transects over three islands (Isabela, S. Cruz, S. Cristóbal). The location of the stations is to consider different local and regional precipitation formation mechanisms. We seek to resolve influences of  the Equatorial Counter Current and the Humboldt Current, as well as the topographic exposition towards the main airstream. Furthermore, the altitudinal gradients concerning vertical dynamics of the trade inversion are considered. One main goal of the DARWIN project is to produce area-wide rainfall information by satellite retrievals and WRF dynamical downscaling. </p><p>While warm-season rainfall is mainly driven by intense convection events, cool-season Garúa is assumed to be more in the drizzle intensity range. The area-wide techniques must thus properly model the very different types of occurring rain intensities in the cool and warm seasons. Hence, the observations from the AWS used as test and training data must be as accurate as possible. Beyond standard meteorology, we focus on different advanced observation principles (light, optical, radar, gauge) and their intercomparison, and warrant high-resolution measurements (up to one minute) including a vertical profiling of rainfall. The AWS stations in the Garúa zone are additionally equipped by a harp-type fog collector.         </p><p>The poster will present the overall structure of the project and some first results of the AWS network, with a focus  on temporally high-resolution rainfall dynamics during  different weather situations and precipitation types along the transects.</p>

These repository data contain netcdf files for each of the four high-resolution (~0.75° per grid cell) general circulation model (GCM) ECHAM-5 experiments with boundary conditions for the mid-Pliocene (~3 Ma; ECHAM5_PLIO_1d_aprl_aprc_q_v_u_Asia.nc), the Last Glacial Maximum (LGM; ~21 ka; ECHAM5_LGM_1d_aprl_aprc_q_v_u_Asia.nc), the mid-Holocene (~6 ka; ECHAM5_MH_1d_aprl_aprc_q_v_u_Asia.nc), and the pre-industrial (ECHAM5_PI_1d_aprl_aprc_q_v_u_Asia.nc). Each file contains 3D fields of specific humidity and winds, as well as precipitation (large-scale and convective) for Asian region.

The Qaidam Basin (QB) in the northeastern Tibetan Plateau held a megalake system during the Pliocene. Today, the lower elevations in the basin are hyperarid. To understand to what extent the climate plays a role in the maintenance of the megalake system during the Pliocene, we applied the Weather Research and Forecasting model for dynamical downscaling of ECHAM5 global climate simulations for the present day and the mid‐Pliocene. When imposing the mid‐Pliocene climate on the QB with its modern land surface settings, the annual water balance ( ΔS ), that is, the change in terrestrial water storage within the QB, increases. This positive imbalance of ΔS induced solely by the changes in the large‐scale climate state would lead to a readjustment of lake extent, until a new equilibrium state is reached, where loss due to evaporation over lake areas compensates for the input by runoff and precipitation. Atmospheric water transport (AWT) analysis at each border of the QB reveals that this imbalance of ΔS is caused by stronger moisture influx across the western border in winter, spring, and autumn and weaker moisture out‐flux across the eastern border in summer. These changes in AWT are associated with the strengthening of the midlatitude westerlies in all seasons, except for summer, and the intensification of the East Asian Summer Monsoon. Given that the mid‐Pliocene climate is an analog to the projected warm climate of the near future, our study contributes to a better understanding of climate change impacts in central Asia.

In the Pliocene, the Qaidam Basin in the northeastern Tibetan Plateau contained a freshwater mega-lake system. The lake system disappeared and the lower parts of the basin now feature hyperarid conditions. What led to the collapse of the lake system and could it appear again in the future? Understanding the sensitivity of the basin’s water balance to changes in atmospheric conditions is crucial for answering this question. We employed the Weather Research and Forecasting model for the dynamical downscaling of two time slices. These were simulated by ECHAM5-wiso atmospheric general circulation model under different boundary conditions, representing present day and Pliocene climate. We present a comparison study analyzing how the basin‘s water balance changes, when we put the Qaidam basin catchment area with its modern geographical features into the Pliocene climate environment. Furthermore, we investigate large scale controls of the basin’s water balance. We find that (1) the Basin’s water balance is more positive or less negative under Pliocene climate; (2) the atmospheric water transport from the west into the basin to be stronger under Pliocene than under present day conditions except for the summer months, while at the same time the influence of the Indian Summer Monsoon is weaker. The analysis suggests that minor changes in atmospheric boundary conditions can have substantial effects on the basin’s water balance.