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Climate changes are top biodiversity shapers, both during the past and future. Mapping the most climatic stable and unstable zones on Earth could improve our understanding of biodiversity distribution and evolution. Here, we present a set of maps based on a global scale, high resolution (ca. 5¿km) new Climate Stability Index (CSI). The CSI considers bioclimatic variables for two different time ranges: (1) from Pliocene (3.3¿Ma) to the present (CSI-past map set), using 12 time periods of PaleoClim representing warm and cold cycles; and (2) from present to the year 2100 (CSI-future), using nine general circulation models of climate change of four periods available from WorldClim. We calculated standard deviation of the variables and selected an uncorrelated set for summing, normalizing and obtaining the CSI maps. Our approach is useful for fields such as biogeography, earth sciences, agriculture, or sociology. However, CSI is an index that can be re-calculated according to particular criteria and objectives (e.g. temperature variables); maps are, therefore, customizable to every user., Financial support from the Ministerio de Ciencia e Innovación (projects CGL2015-66703-P MINECO/FEDER, PID2019-105583GB-C21 funded by MCIN/AEI/10.13039/501100011033, and PID2020-119163GB-I00 funded by MCIN/AEI/10.13039/501100011033; and Ph.D. grant to S.H.M from project CGL2015-66703-P) and the Catalan government (“Ajuts a grups consolidats” 2017-SGR1116). This study has been performed under the Ph.D. program “Plant Biology and Biotechnology” of the Autonomous University of Barcelona (UAB). H.O. and T.M. were funded by the Environment Research and Technology Development Fund (JPMEERF20202002) of the Environmental Restoration and Conservation Agency of Japan., Background & Summary Methods Data Records Technical Validation Code availability References Acknowledgements Author information Ethics declarations Additional information Supplementary information Rights and permissions About this article

It has been claimed that COVID-19 public stimulus packages could be sufficient to meet the short-term energy investment needs to leverage a shift toward a pathway consistent with the 1.5 °C target of the Paris Agreement. Here, we provide complementary perspectives to reiterate that substantial, broad, and sustained policy efforts beyond stimulus packages will be needed for achieving the Paris Agreement long-term targets. Low-carbon investments will need to scale up and persist over the next several decades following short-term stimulus packages. The required total energy investments in the real world can be larger than the currently available estimates from integrated assessment models (IAMs). Existing databases from IAMs are not sufficient for analyzing the effect of public spending on emission reduction. To inform what role COVID-19 stimulus packages and public investments may play for reaching the Paris Agreement targets, explicit modelling of such policies is required.

Identifying and protecting refugia is a priority for conservation management under projected anthropogenic climate change. We have two main objectives: the first is to explore the spatial (East Asia) and temporal (Last Glacial Maximum to year 2070) distribution patterns of dominant Castanopsis species of evergreen broad-leaved forests, also the relation with their niche breadths; the second is to identify long-term stable refugia for preserving these species and provide a framework of conservation strategies. We find that there is an extraordinary richness with 32 dominant Castanopsis species, and they form both a geographically and climatically almost unbroken connection from ca. 5°N to 38°N, having thus ecological significance. During the Mid-Holocene and, particularly, the Last Glacial Maximum, the predicted suitable areas of the species as a whole were larger than those in the present. By 2070, potentially suitable areas with high richness of dominant Castanopsis species will be reduced by 94.5 % on average. No correlation between species niche breadths and distribution ranges is found, which could be due to regional climate stability. Mountains of southwestern and southern Yunnan in China are identified as climatically long-term stable refugia for 7¿9 Castanopsis species. We recommend that these refugia have the highest priority of conservation to prevent their extinction. Our suggested urgent measures include improving the effectiveness of currently protected Castanopsis species and expanding the network of protected areas to cover a larger fraction of the refugia, as well as ensuring Castanopsis species natural regeneration potential in fragmented and natural secondary forest areas., This study received financial support from the Major Program for Basic Research Project of Yunnan Province, China (202101BC070002), the Science and Technology Department of Yunnan University, China (2019YNU002), the Ministry of Science and Technology of China (2015FY210200-15), the Spanish Ministry of Science and Innovation (grant PID2020-119163GB-I00 funded by MCIN/AEI/10.13039/501100011033), the Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency of Japan (JPMEERF20202002), and the Northeastern Research Institute of Petrified Wood and Mineral Resources, Nakhon Ratchasima Rajabhat University, Thailand., Keywords 1. Introduction 2. Materials and methods 2.1. Data collection and notations 2.2. Ecological niche modeling 2.3. Data analyses 3. Results 3.1. Dominant Castanopsis species in East Asia today: richness and distribution patterns 3.2. Richness of dominant Castanopsis species shaped by climate change 3.3. Niche groups and niche breadths of dominant Castanopsis species 3.4. Climatically long-term stable refugia 4. Discussion 4.1. Richness of dominant Castanopsis species shaped by climate change 4.2. Niche groups and niche breadths of dominant Castanopsis species 4.3. Long-term stable refugia and conservation strategies 5. Conclusions CRediT authorship contribution statement Declaration of competing interest Acknowledgements Appendix A. Supplementary material References

33 pags., 23 figs., 5 tabs., The TROPOspheric Monitoring Instrument(TROPOMI), launched in October 2017 on board the Sentinel-5 Precursor (S5P) satellite, monitors the composition of the Earth's atmosphere at an unprecedented horizontal resolution as fine as 3.5×5.5 km2. This paper assesses the performances of the TROPOMI formaldehyde(HCHO) operational product compared to its predecessor, the OMI (Ozone Monitoring Instrument) HCHO QA4ECV product, at different spatial and temporal scales. The parallel development of the two algorithms favoured the consistency of the products, which facilitates the production of long-term combined time series. The main difference between the two satellite products is related to the use of different cloud algorithms, leading to a positive bias of OMI compared to TROPOMI of up to 30% in tropical regions. We show that after switching off the explicit correction for cloud effects, the two datasets come into an excellent agreement. For medium to large HCHO vertical columns(larger than 5×1015 molec. cm-2) the median bias between OMI and TROPOMI HCHO columns is not larger than 10% (, Part of the reported work was carried out in the framework of the Copernicus Sentinel-5 Precursor Mission Performance Centre (S5p MPC), contracted by the European Space Agency (ESA/ESRIN, contract no. 4000117151/16/I-LG) and supported by the Belgian Federal Science Policy Office (BELSPO), the Royal Belgian Institute for Space Aeronomy (BIRA-IASB) and the German Aerospace Centre (DLR). BIRA-IASB acknowledges national funding from BELSPO and ESA through the ProDEx projects TRACE-S5P (TRACE-S5P project) and TROVA. Part of this work was also carried out in the framework of the S5p Validation Team (S5PVT) AO projects NIDFORVAL (ID no. 28607, PI Gaia Pinardi, Corinne Vigouroux, BIRA-IASB). Multi-sensor HCHO developments have been funded by the EU FP7 QA4ECV project (grant no. 607405), in close cooperation with KNMI, University of Bremen, MPIC-Mainz and WUR. Work by Hitoshi Irie was supported by the Environment Research and Technology Development Fund (JPMEERF20192001 and JPMEERF20215005) of the Environmental Restoration and Conservation Agency of Japan, JSPS KAKENHI (grant numbers JP19H04235 and JP20H04320) and the JAXA 2nd Research Announcement on the Earth Observations (grant number 19RT000351).

Aerosol-induced absorption of shortwave radiation can modify the climate through local atmospheric heating, which affects lapse rates, precipitation, and cloud formation. Presently, the total amount of aerosol absorption is poorly constrained, and the main absorbing aerosol species (black carbon (BC), organic aerosols (OA), and mineral dust) are diversely quantified in global climate models. As part of the third phase of the Aerosol Comparisons between Observations and Models (AeroCom) intercomparison initiative (AeroCom phase III), we here document the distribution and magnitude of aerosol absorption in current global aerosol models and quantify the sources of intermodel spread, highlighting the difficulties of attributing absorption to different species. In total, 15 models have provided total present-day absorption at 550 nm (using year 2010 emissions), 11 of which have provided absorption per absorbing species. The multi-model global annual mean total absorption aerosol optical depth (AAOD) is 0.0054 (0.0020 to 0.0098; 550 nm), with the range given as the minimum and maximum model values. This is 28 % higher compared to the 0.0042 (0.0021 to 0.0076) multi-model mean in AeroCom phase II (using year 2000 emissions), but the difference is within 1 standard deviation, which, in this study, is 0.0023 (0.0019 in Phase II). Of the summed component AAOD, 60 % (range 36 %–84 %) is estimated to be due to BC, 31 % (12 %–49 %) is due to dust, and 11 % (0 %–24 %) is due to OA; however, the components are not independent in terms of their absorbing efficiency. In models with internal mixtures of absorbing aerosols, a major challenge is the lack of a common and simple method to attribute absorption to the different absorbing species. Therefore, when possible, the models with internally mixed aerosols in the present study have performed simulations using the same method for estimating absorption due to BC, OA, and dust, namely by removing it and comparing runs with and without the absorbing species. We discuss the challenges of attributing absorption to different species; we compare burden, refractive indices, and density; and we contrast models with internal mixing to models with external mixing. The model mean BC mass absorption coefficient (MAC) value is 10.1 (3.1 to 17.7) m2 g−1 (550 nm), and the model mean BC AAOD is 0.0030 (0.0007 to 0.0077). The difference in lifetime (and burden) in the models explains as much of the BC AAOD spread as the difference in BC MAC values. The difference in the spectral dependency between the models is striking. Several models have an absorption Ångstrøm exponent (AAE) close to 1, which likely is too low given current knowledge of spectral aerosol optical properties. Most models do not account for brown carbon and underestimate the spectral dependency for OA.

Dipentodon sinicus Dunn. (Dipentodonaceae) is a rare and threatened relict plant species usually found co-dominating with other relict plants in subtropical forest patches in highly fragmented habitats of southwestern China, northern Vietnam and northeastern Myanmar of East Asia. To date, its management and conservation strategies in the light of climate change have not been explored. We evaluated effects of climate change on the distribution of climatically suitable areas of D. sinicus as found prevailing during the last glacial maximum (LGM), the mid-Holocene and the present time, and predicted the distribution of climatically suitable habitats in 2070 throughout East Asia. The results as derived from ecological niche modeling (ENM) show the current distribution to be limited to the prehistoric (the mid-Holocene and LGM) refugia, and to indicate decreasing probability of presence and a reducing range of distribution for 2070. In addition, the suitable areas predicted with high probability (0.5–1) only account for on average 9.8% of the total area of potential habitats (threshold‒1) among the models for the year 2070, thereby indicating that D. sinicus is highly vulnerable. Under all the future scenarios for the year 2070, 69–74.2% of potential habitats in China would be outside protected areas. We assess and propose priorities for protected areas, and provide suggestions for conservation management strategies., This study received financial support from Science and Technology Department of Yunnan University, China (2019YNU002), the Ministry of Science and Technology of China (2015FY210200-15), Ajuts a Grups de Recerca Consolidats” (grants nos. 2014-SGR514-GREB and 2017-SGR1116) from the Generalitat de Catalunya (Spain), Applied Basic Research Foundation of Yunnan Province, China (Grant No. 2019FB058), the Environment Research and Technology Development Fund (JPMEERF15S11407) of the Environmental Restoration and Conservation Agency of Japan, and the Kakenhi Grant Number 15H02833., Highlights Abstract Keywords 1. Introduction 2. Material and methods 2.1. Species 2.2. Occurrence data and ecological niche modeling 3. Results 3.1. Model performance and present potential distribution 3.2. Projected distribution during the mid-Holocene (ca. 6000 yr BP) and LGM (ca. 21,000 yr BP) 3.3. Projected distribution under future climate (2070) 4. Discussion 4.1. Effects of climate change on spatial distribution patterns of D. sinicus 5. Recommendations for future conservation efforts and management Declaration of competing interest Acknowledgements Appendix A. Supplementary data References

Major mid-winter stratospheric sudden warmings (SSWs) are the largest instance of wintertime variability in the Arctic stratosphere. Because SSWs are able to cause significant surface weather anomalies on intra-seasonal timescales, several previous studies have focused on their potential future change, as might be induced by anthropogenic forcings. However, a wide range of results have been reported, from a future increase in the frequency of SSWs to an actual decrease. Several factors might explain these contradictory results, notably the use of different metrics for the identification of SSWs and the impact of large climatological biases in single-model studies. To bring some clarity, we here revisit the question of future SSW changes, using an identical set of metrics applied consistently across 12 different models participating in the Chemistry–Climate Model Initiative. Our analysis reveals that no statistically significant change in the frequency of SSWs will occur over the 21st century, irrespective of the metric used for the identification of the event. Changes in other SSW characteristics – such as their duration, deceleration of the polar night jet, and the tropospheric forcing – are also assessed: again, we find no evidence of future changes over the 21st century., Blanca Ayarzagüena was funded by the European Project 603557-STRATOCLIM under the FP7-ENV.2013.6.1-2 programme and “Ayudas para la contratación de personal postdoctoral en formación en docencia e investigación en departamentos de la Universidad Complutense de Madrid”. Blanca Ayarzagüena and Ulrike Langematz wish to acknowledge the Deutsche Forschungsgemeinschaft (DFG) within the research programme SHARP under the grant LA 1025/15-1. Lorenzo M. Polvani is grateful for the continued support of the US National Science Foundation. The work of Neal Butchart, Steven C. Hardiman, and Fiona M. O'Connor was supported by the Joint BEIS/Defra Met Office Hadley Centre Climate Programme (GA01101). Neal Butchart and Steven C. Hardiman were supported by the European Community within the StratoClim project (grant 603557). Olaf Morgenstern and Guang Zeng acknowledge the UK Met Office for use of the Met Office Unified Model (MetUM). This research was supported by the New Zealand Government's Strategic Science Investment Fund (SSIF) through the NIWA programme CACV. Olaf Morgenstern acknowledges funding by the New Zealand Royal Society Marsden Fund (grant 12-NIW-006) and by the Deep South National Science Challenge (http://www.deepsouthchallenge.co.nz, last access: 21 March 2018). The authors wish to acknowledge the contribution of New Zealand eScience Infrastructure (NeSI) high-performance computing (HPC) facilities to the results of this research. New Zealand's national facilities are provided by NeSI and funded jointly by NeSI's collaborator institutions and through the Ministry of Business, Innovation & Employment's Research Infrastructure programme (https://www.nesi.org.nz, last access: 21 March 2018). The EMAC simulations were performed at the German Climate Computing Centre (DKRZ) through support from the Bundesministerium für Bildung und Forschung (BMBF). DKRZ and its Scientific Steering Committee are gratefully acknowledged for providing the HPC and data archiving resources for the consortial project ESCiMo (Earth System Chemistry integrated Modelling). CCSRNIES's research was supported by the Environment Research and Technology Development Funds of the Ministry of the Environment (2-1303) and Environment Restoration and Conservation Agency (2-1709), Japan, and computations were performed on NEC-SX9/A(ECO) and NEC SX-ACE computers at the Center for Global Environmental Research, NIES. The authors wish to thank two anonymous referees for their helpful comments.