Reply on RC1

Abstract. Projections of changes in extreme droughts under future climate conditions are associated with large uncertainties, owing to the complex genesis of droughts and large model uncertainty in the atmospheric dynamics. In this study we investigate the impact of global warming on soil moisture drought severity in west-central Europe by employing pseudo global warming (PGW) experiments, which project the 1980–2020 period in a globally warmer world. The future analogues of present-day drought episodes allow for investigation of changes in drought severity conditional on the historic day-to-day evolution of the atmospheric circulation. The 2018 west-central European drought is the most severe drought in the 1980–2020 reference period in this region. Under 1.5, 2 and 3 ∘C global warming, this drought episode experiences strongly enhanced summer temperatures but a fairly modest soil moisture drying response compared to the change in climatology. This is primarily because evaporation is already strongly moisture-constrained during present-day conditions, limiting the increase in evaporation and thus the modulation of the temperature response under PGW. Increasing precipitation in winter, spring and autumn limits or prevents an earlier drought onset and duration. Nevertheless, the drought severity, defined as the cumulative soil moisture deficit volume, increases considerably, with 20 % to 39 % under 2 ∘C warming. The extreme drought frequency in the 1980–2020 period strongly increases under 2 ∘C warming. Several years without noticeable droughts under present-day conditions show very strong drying and warming. This results in an increase in 2003-like drought occurrences, compounding with local summer temperature increases considerably above 2 ∘C. Even without taking into account a (potentially large) dynamical response to climate change, drought risk in west-central Europe is strongly enhanced under global warming. Owing to increases in drought frequency, severity and compounding heat, a reduction in recovery times between drought episodes is expected to occur. Our physical climate storyline provides evidence complementing conventional large-ensemble approaches and is intended to contribute to the formulation of effective adaptation strategies.

<p>Climate projections indicate an increasing risk of dry and hot episodes in Central Europe, including in Switzerland. However, models display a large spread in projections of changes in summer drying, highlighting the importance of related observations to evaluate climate models and constrain projections. Land hydrological variables play an essential role for these projections. This is particularly the case for soil moisture and land evaporation, which are directly affecting the development of droughts and heatwaves in both present and future.</p><p>The recent 2020 spring as well as 2015 and 2018 summer droughts in Switzerland have highlighted the importance of monitoring and assessing changes of soil moisture and land evaporation, which are strongly related to drought impacts on agriculture, forestry, and ecosystems. The country was affected by major drought and heatwave conditions in 2015 and 2018. While the meteorological conditions started to recover at the end of the summer, the soil moisture conditions (and runoff) continued to be anomalously low for most of the fall. This illustrates the decoupling between meteorological drought and soil moisture drought conditions related to the intrinsic memory of the soil.</p><p>The only Switzerland-wide soil moisture monitoring programme currently in place is the SwissSMEX (Swiss Soil Moisture Experiment) measurement network. It was initiated in 2008 and comprises 19 soil moisture measurement profiles at 17 different sites (grassland, forest and arable land). Since 2017, seven grassland SwissSMEX sites were complemented with land evaporation measurements from mini-lysimeters.</p><p>First, a quality assessment and inter-comparison of the in-situ soil moisture and land evaporation observations at 12 grassland sites revealed substantial discrepancies between different sensor types in terms of absolute values and data availability. A standard procedure for processing and interpreting the SwissSMEX data is thus being established. Second, analyses have been carried out comparing the SwissSMEX measurements with gridded remote-sensing and reanalysis products that provide near real time soil moisture data. In particular, the European Space Agency (ESA) Climate Change Initiative (CCI) surface soil moisture product (ESA-CCI soil moisture) as well as the new ECMWF reanalysis ERA5 are considered. The seasonal evolution of the soil moisture anomalies (with respect to the long-term mean) show for 2020 two pronounced phases of dryness. These are consistently represented in SwissSMEX in-situ observations and ERA5. Also the other recent drought events of 2015 and 2018 show a similar temporal evolution in both datasets. The response of ESA-CCI surface soil moisture is less pronounced, more variable and also dependent on the measurement methodology, i.e., active or passive microwave remote sensing.</p><p>These first analyses provide useful insights in order to provide near-real time monitoring, enhance process understanding at the national scale and a better preparedness for future droughts.</p>

In the context of climate change characterized by rising temperature and more extreme precipitation regimes, drought is one of the most relevant natural disasters. This paper presents maps of global drought frequency, duration, and severity for the periods 1951-1970, 1971-1990, and 1991-2010, to give an overview of the respective drought hot spots. Drought frequency is defined as the number of drought events occurred, drought duration as the number of months in drought conditions, and drought severity as the sum of the integral area below zero of each event. Because drought is mainly driven by rainfall deficits, we chose the Standardized Precipitation Index (SPI) as the base indicator to derive drought-related quantities. SPI-12 has been calculated on a monthly basis using a Gamma distribution fitted to a 60-year baseline period (1951-2010). Global grids (0.5 ◦ × 0.5 ◦ ) of the Full Data Reanalysis Version 6.0 dataset provided by the Global Precipitation Climatology Centre (GPCC) have been used as precipitation data input. The regions most exposed to prolonged and severe droughts during 1951-1970 were the Central United States, the Argentinian Pampas, Russia, and Central Australia; during 1971-1990 they were Southern Chile, the Sahel, and Siberia; during 1991-2010 they were the Amazon Forest, the Congo River Basin, Mongolia, North Eastern China, and Borneo. A linear trend analysis between 1951 and 2010 shows a small global increase in each drought component, but drought frequency decreased in the Northern Hemisphere. The increase in drought frequency, duration, and severity is found to be significant in Africa, Eastern Asia, Mediterranean region, and Southern Australia, while the Americas and Russia show a decrease in each drought component.

Arctic precipitation is predicted to increase in the coming century, due to a combination of enhanced northward atmospheric moisture transport and local surface evaporation from ice-free seas. However, large model uncertainties, limited long-term observations, and high spatiotemporal variability limit our understanding of these mechanisms, emphasizing the need for paleoclimate records of precipitation changes. Here we use lipid biomarkers in lake sediments to reconstruct precipitation seasonality in northern Spitsbergen, Svalbard. We measured the hydrogen isotopic ratios (δ2H) of n-alkanoic acids (C20–C30) from sedimentary leaf waxes in lake Austre Nevlingen, Spitsbergen. We interpret δ2H values of mid-chain (C22) and long-chain (C28) n-alkanoic acids to represent δ2H of lake and soil water, respectively. Austre Nevlingen lake water δ2H reflects amount-weighted mean annual precipitation δ2H. In contrast, soil water is mostly recharged by summer rainfall, and therefore reflects δ2H values of summer precipitation. Austre Nevlingen leaf wax δ2H values are 2H-depleted in the Early Holocene, suggesting high winter precipitation amounts. This coincides with high summer insolation, strong Atlantic water advection and reduced spring sea-ice cover in surrounding waters. Winter precipitation continued to dominate until c. 6 cal. kyr BP. After 6 cal. kyr BP, the trend in the biomarker record is not as clear. This could be related to colder conditions causing longer duration of seasonal lake-ice cover, thereby influencing the precipitation seasonality registered by the lake water. The Austre Nevlingen record suggests a close relationship between precipitation seasonality and regional ocean surface conditions, consistent with simulations suggesting that Arctic winter sea-ice loss will lead to increased local evaporation.

QUANTIFYING PEATLAND CARBON DYNAMICS USING MECHANISTICALLY-BASED BIOGEOCHEMISTRY MODELS

Dry spells are sequences of days without precipitation. They can have negative implications for societies, including water security and agriculture. For example, changes in their duration and within-year timing can pose a threat to food production and wildfire risk. Conversely, wet spells are sequences of days with precipitation above a certain threshold, and changes in their duration and within-year timing can impact agriculture, flooding or the prevalence of water-related vector-borne diseases. Here we assess changes in the duration and within-year timing of extreme dry and wet spells over 60 years (1958–2017) using a consistent global land surface precipitation dataset of 5093 rain gauge locations. The dataset allowed for detailed spatial analyses of the United States, Europe and Australia. While many locations exhibit statistically significant changes in the duration of extreme dry and wet spells, the changes in the within-year timing are less often significant. Our results show consistencies with observations and projections from state-of-the-art climate and water resources research. In addition, we provide new insights regarding trends in the timing of extreme dry and wet spells, an aspect being equally important for possible future implications of extremes in a changing climate, which has not yet received the same level of attention and is characterized by larger uncertainty.

Extreme weather events have been increasing as global temperatures rise. Semi-enclosed basins such as the Black Sea and the Mediterranean are particularly susceptible to extreme weather due to their unique topographic features and land-sea distribution. Extreme precipitation events on the north-facing slopes of the mountains in the Black Sea Region occur due to relatively cold air interacting with the warm sea and being orographically lifted over the mountains. On August 10-12 2021, a deadly flash flood occurred on the coast of the Black Sea in Northern Türkiye which resulted in excessive precipitation (200-450 mm) causing loss of lives of 97 people and leaving 228 injured. We investigated extreme weather event which occurred near the Black Sea along with future climate conditions using the Pseudo-Global Warming method. In order to analyze the event, we used a numerical weather prediction model (WRF) in convection-permitting 3 km horizontal resolution with a domain covering the Black Sea and surrounding area. The model simulations are driven by ECMWF Reanalysis 5th Generation (ERA5) data for initial and boundary conditions. To derive climate change signals, we used 25 CMIP6 Earth System Models and eliminating the rest of the models that have no ocean model component over the Black Sea. The signals are computed for three different future periods (2025–2049, 2050–2074, and 2075–2099) relative to the 1990–2014 historical period. Each climate change signal which represents different periods were added to ERA5 6-hourly data as ensemble means. In the first future period (2025-2049), sea surface temperature (SST) in August is projected to increase by 1.7 °C, and by the end of the period (2075-2099), SST is expected to rise by 5 °C over the Black Sea. Additionally, while near-surface air temperatures in August are projected to increase by 1.5 °C to 2.5 °C initially, they are expected to rise by approximately 5.5 °C to 8.5 °C in the final period over the simulation domain. Moreover, near-surface relative humidity over land in August is simulated to decrease by nearly 10% in the last quarter of the century. The findings of this study will contribute to our understanding of how extreme precipitation events develop under future climate conditions and provide insights of the physical and dynamic processes that could drive these events in a warmer world.

The intense and moist winds in a tropical cyclone (TC) environment can produce strong mountain waves and enhanced precipitation over complex terrain, yet few studies have investigated how the orographic precipitation in a TC environment might respond to global warming. Here, we use large-eddy simulation to estimate the global warming–induced change in the precipitation near an idealized mountain (1 km maximum height) with pseudo global warming. Two regions exhibit enhanced precipitation, one over the mountain and the other in the downstream region 25–45 km away from the mountain. The enhanced precipitation in both regions is related to the seeder–feeder mechanism, although the enhancement in the downstream regions differs from the conventional definition and is referred to as the pseudo-seeder–feeder mechanism (PSF). In the PSF, mountain waves generate an intense cloud formation center in the midtroposphere above the lee slope, and the resulting hydrometeors drift downstream, intensifying downstream convection when they fall into proper locations. Under warming, the overmountain precipitation maximum exhibits minimal changes, while the downstream precipitation maximum exhibits a large sensitivity of 18% K−1. The small sensitivity of the first precipitation peak is due to the canceling effects of thermodynamic and dynamic changes. The large sensitivity in the downstream region is mainly due to the strengthening of the wave-induced midtroposphere cloud formation center, which supplies more hydrometeors to the downstream region and enhances precipitation efficiency through the enhanced PSF mechanism. However, the downstream precipitation sensitivity varies with mountain geometry. Higher mountain height enhances precipitation but lowers the sensitivity to warming. Significance Statement The combination of typhoon environment and orography can produce intense precipitation and thereby severe flooding risks. Here, we investigate the global warming response of orographic precipitation in a typhoon environment with idealized, high-resolution simulations. The experiments suggest that under warming, a precipitation maximum may emerge in the downstream region of a mountain or strengthen and shift upwind if it already exists in the current climate. This surprising amplification of downstream-region precipitation is related to the enhancement of the midtropospheric cloud generation caused by mountain waves and has critical implications for flooding risk management in mountainous regions.

The severity of the impacts of (convective) rainfall extremes in the past year alone, e.g., storm Boris and the flooding in middle Europe, or the flooding in the Valencia region, is mind blowing. With several hundreds of millimeters of rain falling in often fewer than 48 hours, the flooding was locally very disruptive, or even catastrophic. While often embedded in large-scale and reasonably well predictable (but anomalous) flow conditions, the level of small-scale detail and the role of smaller-scale (convective) processes that ultimately determine whether the situation "gets out of hand" - or not - is challenging both observation networks, and the NWP and climate-modelling centers. In this presentation we take the example of storm Boris that caused widespread flooding in Middle Europe in September 2024 to illustrate that only by simulating the event at very high resolution the true changes in the impacts are revealed. Using a pseudo-global warming (PGW) framework in which the event is placed in historic and possible future climate conditions, we show that on a local scale the response strongly exceeds the regional response. By subsequently matching the patterns to underlying population densities an impression is obtained of how this leads to a greatly elevated impact on society.Different frameworks have been developed to analyse, attribute and project extreme events often immediately after, or even prior to the event. The regional PGW framework we are adopting here is but one of the several existing approaches based on analysing 'counterfactuals', i.e., simulating the event in a different climate. Another framework is that of dynamic analogues which relies on deriving paste-to-present or present-to-future changes, by selecting and comparing similar (observed or modelled) events based on large-scale flow similarity. In this approach therefore, the event is also captured. Structural similarity in terms of flow conditions is not required by the approach of world-weather attribution (WWA). The WWA-approach examines changing frequency and intensity of local or regional extremes using non-stationary extreme-value analysis of observational and model data, and blends these two lines of information. All methods have their advantages and disadvantages. At best, these methods give overlapping results, but in practice they highlight different aspects of the (past or future) changes. This forces one to think how to combine or merge the output from the different methodologies to provide society with the most relevant information and to better anticipate on the future changes. 

This project focuses on uncertainty in streamflow forecasting under climate change conditions. The objective is to develop easy to use methodologies that can be applied across a range of river basins to estimate changes in water availability for realistic projections of climate change. There are three major components to the project: Empirical downscaling of regional climate change projections from a range of Global Climate Models; Developing a methodology to use present day information on the climate controls on the parameterizations in streamflow models to adjust the parameterizations under future climate conditions (a trading-space-for-time approach); and Demonstrating a bottom-up approach to establishing streamflow vulnerabilities to climate change. The results reinforce the need for downscaling of climate data for regional applications, and further demonstrates the challenges of using raw GCM data to make local projections. In addition, it reinforces the need to make projections across a range of global climate models. The project demonstrates the potential for improving streamflow forecasts by using model parameters that are adjusted for future climate conditions, but suggests that even with improved streamflow models and reduced climate uncertainty through the use of downscaled data, there is still large uncertainty is the streamflow projections. The most useful output from the project is the bottom-up vulnerability driven approach to examining possible climate and land use change impacts on streamflow. Here, we demonstrate an inexpensive and easy to apply methodology that uses Classification and Regression Trees (CART) to define the climate and environmental parameters space that can produce vulnerabilities in the system, and then feeds in the downscaled projections to determine the probability top transitioning to a vulnerable sate. Vulnerabilities, in this case, are defined by the end user.

The low-latitude highland (LLH) of Southeast Asia is a hot spot of soil–atmosphere coupling, and variations in the soil temperature and moisture in this region have a significant effect on the regional climate. In this study, the characteristics of the soil–atmosphere coupling were analyzed, two decoupling numerical tests were designed, and the impacts of the soil temperature and moisture on the regional climate in the LLH were assessed. Finally, the key factors of the soil–atmosphere coupling were explored, and their contributions to air temperature and precipitation were evaluated. The primary conclusions are as follows. (1) The soil–atmosphere coupling in the LLH is primarily characterized by the soil moisture-limited regime in dry seasons (spring and winter) and the energy-limited regime in the wet seasons (summer and autumn), indicating that there is a seasonal difference in the soil–atmosphere coupling within the LLH. (2) The quantitative assessments conducted via numerical simulation revealed that the soil temperature–atmosphere coupling has the greatest impacts on the average air temperature and precipitation in winter and autumn, with changes of − 0.08 °C and 0.13 mm d−1 (35.5% and 1.4% variability), respectively. In contrast, the soil moisture–atmosphere coupling has the greatest impacts on the average air temperature and precipitation in summer, with changes of 0.20 °C and 0.13 mm d−1 (14.4% and − 3.0% variability), respectively. (3) Regarding the air temperature, the soil temperature mainly controls the net longwave radiation in the dry season and the net shortwave radiation in the wet season, with significant contributions exceeding 36.6%. The soil moisture regulates the sensible heat flux in both the dry and wet seasons, with significant contributions exceeding 32.8%. Regarding precipitation, both the soil temperature and moisture mainly affect evapotranspiration in the dry and wet seasons, with significant contributions exceeding 25.9%.

Avian communities of arid ecosystems may be particularly vulnerable to global climate change due to the magnitude of projected change for desert regions and the inherent challenges for species residing in resource limited ecosystems. How arid-zone birds will be affected by rapid increases in air temperature and increased drought frequency and severity is poorly understood because avian responses to climate change have primarily been studied in the relatively mesic northern temperate regions. We studied the effects of increasing air temperature and aridity on a Burrowing Owl (Athene cunicularia) population in the southwestern United States from 1998 to 2013. Over 16 years, the breeding population declined 98.1%, from 52 pairs to 1 pair, and nest success and fledgling output also declined significantly. These trends were strongly associated with the combined effects of decreased precipitation and increased air temperature. Arrival on the breeding grounds, pair formation, nest initiation, and hatch dates all showed significant delays ranging from 9.4 to 25.1 days over 9 years, which have negative effects on reproduction. Adult and juvenile body mass decreased significantly over time, with a loss of 7.9% mass in adult males and 10.9% mass in adult females over 16 years, and a loss of 20.0% mass in nestlings over 8 years. Taken together, these population and reproductive trends have serious implications for local population persistence. The southwestern United States has been identified as a climate change hotspot, with projections of warmer temperatures, less winter precipitation, and an increase in frequency and severity of extreme events including drought and heat waves. An increasingly warm and dry climate may contribute to this species' decline and may already be a driving force of their apparent decline in the desert southwest.

Study RegionThe study covers sites across Great Britain. Study FocusSoil moisture information is important for a range of applications including flood and drought monitoring, seasonal hydrological forecasting, and agricultural management. However, spatially distributed soil moisture estimates for sub-surface soils are scarce despite their importance. The Grid-to-Grid hydrological model (G2G) was primarily developed to simulate river flows at a national scale, but can also output simulated depth-integrated soil moisture on a 1 km grid. Here, we evaluate G2G soil moisture simulations against in situ neutron probe (NP) observations at 85 sites across Great Britain, to evaluate whether modelled soil moisture outputs have value and to identify areas for improvement. New Hydrological Insights for the Region:Despite large uncertainties in observed soil moisture within a site, there was a good temporal correlation between observed and modelled soil moisture, with Pearson correlation values exceeding 0.7 for 77% of sites. However, the model tended to under-predict soil moisture values (median bias of −12 cm/m) and over-predict variation (median standard deviation error of 2 cm/m). Model agreement with observations was generally better for areas with deep or mid-depth mineral soils and worst in areas of peat. Based on this evaluation against NP observations, we demonstrate that G2G soil moisture is a useful resource for estimating relative wetness of the soil, but not necessarily the soil moisture content values themselves.

Abstract. Understanding the influence of global warming on regional hydroclimatic extremes is challenging. To reduce the potential risk of extremes under future climate states, assessing the change in extreme climate events is important, especially in Asia, due to spatial variability of climate and its seasonal variability. Here, the changes in hydroclimatic extremes are assessed over the Asian monsoon region under global mean temperature warming targets of 1.5 and 2.0 ∘C above preindustrial levels based on representative concentration pathways (RCPs) 4.5 and 8.5. Analyses of the subregions classified using regional climate characteristics are performed based on the multimodel ensemble mean (MME) of five bias-corrected global climate models (GCMs). For runoff extremes, the hydrologic responses to 1.5 and 2.0 ∘C global warming targets are simulated based on the variable infiltration capacity (VIC) model. Changes in temperature extremes show increasing warm extremes and decreasing cold extremes in all climate zones with strong robustness under global warming conditions. However, the hottest extreme temperatures occur more frequently in low-latitude regions with tropical climates. Changes in mean annual precipitation and mean annual runoff and low-runoff extremes represent the large spatial variations with weak robustness based on intermodel agreements. Global warming is expected to consistently intensify maximum extreme precipitation events (usually exceeding a 10 % increase in intensity under 2.0 ∘C of warming) in all climate zones. The precipitation change patterns directly contribute to the spatial extent and magnitude of the high-runoff extremes. Regardless of regional climate characteristics and RCPs, this behavior is expected to be enhanced under the 2.0 ∘C (compared with the 1.5 ∘C) warming scenario and increase the likelihood of flood risk (up to 10 %). More importantly, an extra 0.5 ∘C of global warming under two RCPs will amplify the change in hydroclimatic extremes on temperature, precipitation, and runoff with strong robustness, especially in cold (and polar) climate zones. The results of this study clearly show the consistent changes in regional hydroclimatic extremes related to temperature and high precipitation and suggest that hydroclimatic sensitivities can differ based on regional climate characteristics and type of extreme variables under warmer conditions over Asia.

Extending the SCOPE model to combine optical reflectance and soil moisture observations for remote sensing of ecosystem functioning under water stress conditions