Regional Surface Temperature Research Articles

Calculating the Climatology and Anomalies of Surface Cloud Radiative Effect Using Cloud Property Histograms and Cloud Radiative Kernels

Cloud radiative kernels (CRK) built with radiative transfer models have been widely used to analyze the cloud radiative effect on top of atmosphere (TOA) fluxes, and it is expected that the CRKs would also be useful in the analyses of surface radiative fluxes, which determines the regional surface temperature change and variability. In this study, CRKs at the surface and TOA were built using the Rapid Radiative Transfer Model (RRTM). Longwave cloud radiative effect (CRE) at the surface is primarily driven by cloud base properties, while TOA CRE is primarily decided by cloud top properties. For this reason, the standard version of surface CRK is a function of latitude, longitude, month, cloud optical thickness (τ) and cloud base pressure (CBP), and the TOA CRK is a function of latitude, longitude, month, τ and cloud top pressure (CTP). Considering that the cloud property histograms provided by climate models are functions of CTP instead of CBP at present, the surface CRKs on CBP-τ histograms were converted to CTP-τ fields using the statistical relationship between CTP, CBP and τ obtained from collocated CloudSat and MODIS observations. For both climate model outputs and satellites observations, the climatology of surface CRE and cloud-induced surface radiative anomalies calculated with the surface CRKs and cloud property histograms are well correlated with those calculated from surface radiative fluxes. The cloud-induced surface radiative anomalies reproduced by surface CRKs and MODIS cloud property histograms are not affected by spurious trends that appear in Clouds and the Earth’s Radiant Energy System (CERES) surface irradiances products.

Statistical characteristics of extreme daily precipitation during 1501 BCE–1849 CE in the Community Earth System Model

Abstract. In this study, we analyze extreme daily precipitation during the pre-industrial period from 1501 BCE to 1849 CE in simulations from the Community Earth System Model version 1.2.2. A peak-over-threshold (POT) extreme value analysis is employed to examine characteristics of extreme precipitation and to identify connections of extreme precipitation with the external forcing and with modes of internal variability. The POT analysis shows that extreme precipitation with similar statistical characteristics, i.e., the probability density distributions, tends to cluster spatially. There are differences in the distribution of extreme precipitation between the Pacific and Atlantic sectors and between the northern high and southern low latitudes. Extreme precipitation during the pre-industrial period is largely influenced by modes of internal variability, such as El Niño–Southern Oscillation (ENSO), the Pacific North American, and Pacific South American patterns, among others, and regional surface temperatures. In general, the modes of variability exhibit a statistically significant connection to extreme precipitation in the vicinity to their regions of action. The exception is ENSO, which shows more widespread influence on extreme precipitation across the Earth. In addition, the regions with which extreme precipitation is more associated, either by a mode of variability or by the regional surface temperature, are distinguished. Regional surface temperatures are associated with extreme precipitation over lands at the extratropical latitudes and over the tropical oceans. In other regions, the influence of modes of variability is still dominant. Effects of the changes in the orbital parameters on extreme precipitation are rather weak compared to those of the modes of internal variability and of the regional surface temperatures. Still, some regions in central Africa, southern Asia, and the tropical Atlantic ocean show statistically significant connections between extreme precipitation and orbital forcing, implying that in these regions, extreme precipitation has increased linearly during the 3351-year pre-industrial period. Tropical volcanic eruptions affect extreme precipitation more clearly in the short term up to a few years, altering both the intensity and frequency of extreme precipitation. However, more apparent changes are found in the frequency than the intensity of extreme precipitation. After eruptions, the return periods of extreme precipitation increase over the extratropical regions and the tropical Pacific, while a decrease is found in other regions. The post-eruption changes in the frequency of extreme precipitation are associated with ENSO, which itself is influenced by tropical eruptions. Overall, the results show that climate simulations are useful to complement the information on pre-industrial extreme precipitation, as they elucidate statistical characteristics and long-term connections of extreme events with natural variability.

Understanding the surface temperature response and its uncertainty to CO<sub>2</sub>, CH<sub>4</sub>, black carbon, and sulfate

Abstract. Understanding the regional surface temperature responses to different anthropogenic climate forcing agents, such as greenhouse gases and aerosols, is crucial for understanding past and future regional climate changes. In modern climate models, the regional temperature responses vary greatly for all major forcing agents, but the causes of this variability are poorly understood. Here, we analyze how changes in atmospheric and oceanic energy fluxes due to perturbations in different anthropogenic climate forcing agents lead to changes in global and regional surface temperatures. We use climate model data on idealized perturbations in four major anthropogenic climate forcing agents (CO2, CH4, sulfate, and black carbon aerosols) from Precipitation Driver Response Model Intercomparison Project (PDRMIP) climate experiments for six climate models (CanESM2, HadGEM2-ES, NCAR-CESM1-CAM4, NorESM1, MIROC-SPRINTARS, GISS-E2). Particularly, we decompose the regional energy budget contributions to the surface temperature responses due to changes in longwave and shortwave fluxes under clear-sky and cloudy conditions, surface albedo changes, and oceanic and atmospheric energy transport. We also analyze the regional model-to-model temperature response spread due to each of these components. The global surface temperature response stems from changes in longwave emissivity for greenhouse gases (CO2 and CH4) and mainly from changes in shortwave clear-sky fluxes for aerosols (sulfate and black carbon). The global surface temperature response normalized by effective radiative forcing is nearly the same for all forcing agents (0.63, 0.54, 0.57, 0.61 K W−1 m2). While the main physical processes driving global temperature responses vary between forcing agents, for all forcing agents the model-to-model spread in temperature responses is dominated by differences in modeled changes in longwave clear-sky emissivity. Furthermore, in polar regions for all forcing agents the differences in surface albedo change is a key contributor to temperature responses and its spread. For black carbon, the modeled differences in temperature response due to shortwave clear-sky radiation are also important in the Arctic. Regional model-to-model differences due to changes in shortwave and longwave cloud radiative effect strongly modulate each other. For aerosols, clouds play a major role in the model spread of regional surface temperature responses. In regions with strong aerosol forcing, the model-to-model differences arise from shortwave clear-sky responses and are strongly modulated by combined temperature responses to oceanic and atmospheric heat transport in the models.

Piecewise Evolutionary Spectra: A Practical Approach to Understanding Projected Changes in Spectral Relationships Between Circulation Modes and Regional Climate Under Global Warming

AbstractRegional climate variability is strongly related to large‐scale circulation modes. However, little is known about changes in their spectral characteristics under climate change. Here, we introduce piecewise evolutionary spectra to quantify time‐varying variability and co‐variability of climate variables, and use ensemble periodograms to estimate these spectra. By employing a large ensemble of climate change simulations, we show that changes in the variability and relationships of the North Atlantic Oscillation (NAO) and regional surface temperatures are disparate on individual timescales. The relation between NAO and surface temperature over high‐latitude lands weakens the most on 20‐year timescales compared to shorter timescales, whereas the relation between NAO and temperature over subtropical North Africa strengthens more on shorter timescales than on 20‐year timescales. These projected evolution and timescale‐dependent changes shed new light on the controlling factors of circulation‐induced regional changes. Accounting for them can lead to the improvement of future regional climate predictions.

Identifying the sources of uncertainty in climate model simulations of solar radiation modification with the G6sulfur and G6solar Geoengineering Model Intercomparison Project (GeoMIP) simulations

Abstract. We present here results from the Geoengineering Model Intercomparison Project (GeoMIP) simulations for the experiments G6sulfur and G6solar for six Earth system models participating in the Climate Model Intercomparison Project (CMIP) Phase 6. The aim of the experiments is to reduce the warming that results from a high-tier emission scenario (Shared Socioeconomic Pathways SSP5-8.5) to that resulting from a medium-tier emission scenario (SSP2-4.5). These simulations aim to analyze the response of climate models to a reduction in incoming surface radiation as a means to reduce global surface temperatures, and they do so either by simulating a stratospheric sulfate aerosol layer or, in a more idealized way, through a uniform reduction in the solar constant in the model. We find that over the final two decades of this century there are considerable inter-model spreads in the needed injection amounts of sulfate (29 ± 9 Tg-SO2/yr between 2081 and 2100), in the latitudinal distribution of the aerosol cloud and in the stratospheric temperature changes resulting from the added aerosol layer. Even in the simpler G6solar experiment, there is a spread in the needed solar dimming to achieve the same global temperature target (1.91 ± 0.44 %). The analyzed models already show significant differences in the response to the increasing CO2 concentrations for global mean temperatures and global mean precipitation (2.05 K ± 0.42 K and 2.28 ± 0.80 %, respectively, for SSP5-8.5 minus SSP2-4.5 averaged over 2081–2100). With aerosol injection, the differences in how the aerosols spread further change some of the underlying uncertainties, such as the global mean precipitation response (−3.79 ± 0.76 % for G6sulfur compared to −2.07 ± 0.40 % for G6solar against SSP2-4.5 between 2081 and 2100). These differences in the behavior of the aerosols also result in a larger uncertainty in the regional surface temperature response among models in the case of the G6sulfur simulations, suggesting the need to devise various, more specific experiments to single out and resolve particular sources of uncertainty. The spread in the modeled response suggests that a degree of caution is necessary when using these results for assessing specific impacts of geoengineering in various aspects of the Earth system. However, all models agree that compared to a scenario with unmitigated warming, stratospheric aerosol geoengineering has the potential to both globally and locally reduce the increase in surface temperatures.

Economic Shock in a Climate Scenario and Its Impact on Surface Temperatures

AbstractA socio‐economic crisis was added to the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway 8.5 (RCP8.5) scenario. This idealized climate scenario was simulated using the Community Earth System Model version 1.2.2 to determine the transient climate response to a two‐year reduction of anthropogenic emissions. Global and regional (Asian, North American and European) mean surface temperatures (MSTs) were significantly warmer than baseline for 5 years. This was followed by cooler‐than‐baseline MSTs lasting for about two decades until the end of the simulation. Emission reduction of only carbon dioxide (CO2) resulted in multi‐decadal cooler‐than‐baseline MSTs. Emission reduction of aerosols and aerosol precursors resulted in strong short‐term warmer‐than‐baseline MSTs for the first five years after the start of the crisis. This was followed by weaker multi‐decadal warmer‐than‐baseline MSTs. The greatest warming occurred over Europe. This could be explained by the inter‐scenario differences in the state of the North Atlantic Oscillation. However, global, Asian and North American MSTs were all warmer than baseline.

Detecting Climate Signals Using Explainable AI With Single‐Forcing Large Ensembles

AbstractIt remains difficult to disentangle the relative influences of aerosols and greenhouse gases on regional surface temperature trends in the context of global climate change. To address this issue, we use a new collection of initial‐condition large ensembles from the Community Earth System Model version 1 that are prescribed with different combinations of industrial aerosol and greenhouse gas forcing. To compare the climate response to these external forcings, we adopt an artificial neural network (ANN) architecture from previous work that predicts the year by training on maps of near‐surface temperature. We then utilize layer‐wise relevance propagation (LRP) to visualize the regional temperature signals that are important for the ANN's prediction in each climate model experiment. To mask noise when extracting only the most robust climate patterns from LRP, we introduce a simple uncertainty metric that can be adopted to other explainable artificial intelligence (AI) problems. We find that the North Atlantic, Southern Ocean, and Southeast Asia are key regions of importance for the neural network to make its prediction, especially prior to the early‐21st century. Notably, we also find that the ANN predictions based on maps of observations correlate higher to the actual year after training on the large ensemble experiment with industrial aerosols held fixed to 1920 levels. This work illustrates the sensitivity of regional temperature signals to changes in aerosol forcing in historical simulations. By using explainable AI methods, we have the opportunity to improve our understanding of (non)linear combinations of anthropogenic forcings in state‐of‐the‐art global climate models.

Assessment of surface roughness and fractional vegetation coverage in the CoLM for modeling regional land surface temperature

The application of Land surface models (LSMs) at regional scales still faces challenges and large uncertainties exist in simulating regional energy fluxes and land surface temperature (LST). This is possibly caused by their poor representations of surface parameter properties (e.g., fractional vegetation coverage (FVC) and surface roughness length (z0m)) to effectively capture vegetation dynamics. In this study, satellite-based FVC and z0m schemes were incorporated into the Common Land Model (CoLM) and their impacts on modeling energy fluxes and associated LST were further assessed over grassland and forest areas in China. Our results show that the annual mean LST was obviously overestimated by the original CoLM for both grassland and forest. The overestimation was reduced by the revised CoLM when compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. Concerning the seasonal patterns, the revised model performed evidently better in simulating LST in summer than in winter. Additionally, the decreased simulation of LST was dominated by a reduction of the surface absorbed short-wave radiation when applying the revised FVC scheme over both grassland and forest, while the increased sensible/latent heat fluxes contributed most to the reduction of LST for the revised z0m scheme in grassland/forest, respectively, indicating that land surface energy partitioning is sensitive to the FVC and z0m parameterizations. Results from this study suggest that the use of satellite-based dynamics of FVC and z0m parameterizations in the CoLM provides a valuable improvement in regional applications.

Anthropogenic influence in observed regional warming trends and the implied social time of emergence

The attribution of climate change allows for the evaluation of the contribution of human drivers to observed warming. At the global and hemispheric scales, many physical and observation-based methods have shown a dominant anthropogenic signal, in contrast, regional attribution of climate change relies on physically based numerical climate models. Here we show, using state-of-the-art statistical tests, the existence of a common nonlinear trend in observed regional air surface temperatures largely imparted by anthropogenic forcing. All regions, continents and countries considered have experienced warming during the past century due to increasing anthropogenic radiative forcing. The results show that we now experience mean temperatures that would have been considered extreme values during the mid-20th century. The adaptation window has been getting shorter and is projected to markedly decrease in the next few decades. Our findings provide independent empirical evidence about the anthropogenic influence on the observed warming trend in different regions of the world.

Climate Impacts of COVID‐19 Induced Emission Changes

AbstractThe COVID‐19 pandemic led to dramatic changes in economic activity in 2020. We use estimates of emission changes for 2020 in two Earth System Models (ESMs) to simulate the impacts of the COVID‐19 economic changes. Ensembles of nudged simulations are used to separate small signals from meteorological variability. Reductions in aerosol and precursor emissions, chiefly black carbon and sulfate (SO4), led to reductions in total anthropogenic aerosol cooling through aerosol‐cloud interactions. The average overall Effective Radiative Forcing (ERF) peaks at +0.29 ± 0.15 Wm−2 in spring 2020. Changes in cloud properties are smaller than observed changes during 2020. Impacts of these changes on regional land surface temperature range up to +0.3 K. The peak impact of these aerosol changes on global surface temperature is very small (+0.03 K). However, the aerosol changes are the largest contribution to radiative forcing and temperature changes as a result of COVID‐19 affected emissions, larger than ozone, CO2 and contrail effects.

Synchronous Variations in Abundance and Distribution of Ommastrephes bartramii and Dosidicus gigas in the Pacific Ocean

An analysis was performed in this study to investigate synchronous fluctuations in abundance and distribution of Ommastrephes bartramii in the Northwest Pacific Ocean and Dosidicus gigas in the Southeast Pacific Ocean. The impacts of two Nino indices and regional water surface temperature on the two squids during 2006–2015 were evaluated, which possibly can explain the observed synchronicity. Catch per unit effort (CPUE) and the latitudinal gravity centers (LATG) of fishing effort were used to indicate squid abundance and distribution, respectively. The results indicated that both the CPUE and LATG showed highly interannual variations and synchronous fluctuation with significant negative associations between the two squid species from September to November. Strong positive cross-correlations with 2-month lag was found between sea surface temperature (SST) anomaly in the Nino 3.4 and Nino 1+2 regions, which have significant linkage with the SST on the fishing ground of O. bartramii and D. gigas, respectively. Moreover, the proportion of favorable-SST area (PFSST) and the latitudinal location of the optimal SST for O. bartramii and D. gigas were positively correlated with the CPUE and LATG, respectively. Increased O. bartramii PFSST clearly corresponded to decreased D. gigas PFSST in phase as well as the latitudinal location of the optimal SST from September to November over 2006–2015. Our findings suggest that synchronous changes in abundance and distribution of the two squids were due to simultaneous variations in the PFSST and the latitudinal location of the optimal SST front which were affected by the SSTA changes in the Nino 3.4 and Nino 1+2 regions.

North American cold events following sudden stratospheric warming in the presence of low Barents-Kara Sea sea ice

While the relationship between the Arctic sea ice loss and midlatitude winter climate has been well discussed, especially on the seasonal mean scale, it remains unclear whether the Arctic sea ice condition affects the predictability of North American cold weather on the subseasonal time scale. Here we find that, in the presence of low Barents-Kara Sea (BKS) sea ice, sudden stratospheric warmings (SSWs) can favor surface cold spells over North America at the subseasonal timescale based on observations and model experiments. A persistent ridge of wave-2 pattern emerges over the Bering Sea-Gulf of Alaska several weeks after the SSW onset, with a coherent structure from the stratosphere to the surface, which, in turn, is conducive to synoptic cold air outbreaks in Canada and midwestern USA. This highlights a planetary wave pathway relating to BKS sea ice changes, by which the stratospheric polar vortex impacts the regional surface temperature on the subseasonal scale. In contrast, this mechanism does not occur with positive BKS sea ice anomaly. These findings help to improve the subseasonal predictability over North America, especially under the background of rapid change of Arctic sea ice in a warming world.

Remote sensing inversion and spatial variation of land surface temperature over mining areas of Jixi, Heilongjiang, China.

BackgroundJixi is a typical mining city in China that has undergone dramatic changes in its land-use pattern of mining areas over the development of its coal resources. The impacts of coal mining activities have greatly affected the regional land surface temperature and ecological system.MethodsThe Landsat 8 Operational Land Imager (OLI) data from 2015 and 2019 were used from the Jiguan, Didao, and Chengzihe District of Jixi in Heilongjiang, China as the study area. The calculations to determine the land-use classification, vegetation coverage, and land surface temperature (LST) were performed using ArcGIS10.5 and ENVI 5.3 software packages. A correlation analysis revealed the impact of land-use type, vegetation coverage, and coal mining activities on LSTs.ResultsThe results show significant spatial differentiation in the LSTs of Jixi City. The LSTs for various land-use types were ranked from high to low as follows: mining land > construction land > grassland > cultivated land > forest land > water area. The LST was lower in areas with high vegetation coverage than in other areas. For every 0.1 increase in vegetation coverage, the LST is expected to drop by approximately 0.75 °C. An analysis of mining land patches indicates that the patch area of mining lands has a significant positive correlation with both the average and maximum patch temperatures. The average patch temperature shows a logarithmic increase with the growth of the patch area, and within 200,000 m2, the average patch temperature increases significantly. The maximum patch temperature shows a linear increase with the patch area growth, and for every 100,000 m2 increase in the patch area of mining lands, the maximum patch temperature increases by approximately 0.81 °C. The higher the average patch temperature of mining land, the higher the temperature in its buffer zone, and the greater its influence scope. This study provides a useful reference for exploring the warming effects caused by coal mining activities and the definition of its influence scope.

Surface Temperature Changes Projected by FGOALS Models under Low Warming Scenarios in CMIP5 and CMIP6

To meet the low warming targets proposed in the 2015 Paris Agreement, substantial reduction in carbon emissions is needed in the future. It is important to know how surface climates respond under low warming targets. The present study investigates the surface temperature changes under the low-forcing scenario of Representative Concentration Pathways (RCP2.6) and its updated version (Shared Socioeconomic Pathways, SSP1-2.6) by the Flexible Global Ocean-Atmosphere-Land System (FGOALS) models participating in phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively). In both scenarios, radiative forcing (RF) first increases to a peak of 3 W m−2 around 2045 and then decreases to 2.6 W m−2 by 2100. Global mean surface air temperature rises in all FGOALS models when RF increases (RF increasing stage) and declines or holds nearly constant when RF decreases (RF decreasing stage). The surface temperature change is distinct in its sign and magnitude between the RF increasing and decreasing stages over the land, Arctic, North Atlantic subpolar region, and Southern Ocean. Besides, the regional surface temperature change pattern displays pronounced model-to-model spread during both the RF increasing and decreasing stages, mainly due to large intermodel differences in climatological surface temperature, ice-albedo feedback, natural variability, and Atlantic Meridional Overturning Circulation change. The pattern of tropical precipitation change is generally anchored by the spatial variations of relative surface temperature change (deviations from the tropical mean value) in the FGOALS models. Moreover, the projected changes in the updated FGOALS models are closer to the multi-model ensemble mean results than their predecessors, suggesting that there are noticeable improvements in the future projections of FGOALS models from CMIP5 to CMIP6.

Regional surface temperature simulations over the Iberian Peninsula: evaluation and climate projections

The realism of a specific configuration of the WRF Regional Climate Model (RCM) to represent the observed temperature evolution over the Iberian Peninsula (IP) in the 1971–2005 period has been analyzed. The E-OBS observational dataset was used for this purpose. Also, the textit{added value} of the WRF simulations with respect to the IPSL Earth System Model (ESM) used to drive the WRF RCM was evaluated. In general, WRF presents lower temperatures than in the observations (negative biases) over the IP. These biases are comparatively larger than those of the driving ESM. Once the biases are corrected, WRF provides an added value in terms of a higher spatial representation. WRF introduces more variability in some regions in comparison to gridded observation. Warming trends according to the observations are also well represented by the RCM. In the second part of this study, the projections of future climate performed with both the ESM and the RCM were evaluated for the RCP4.5 and RCP8.5 scenarios during the 21st century. Although both models simulate temperature increases, the RCM simulates a smaller warming than the ESM after the mid-21st century, except for winter. Using the WRF model, the maximum temperature increase reaches 6, ^circ hbox {C} and 3, ^circ hbox {C} for RCP8.5 and RCP4.5 in the south east of the Iberian Peninsula by the end of the 21st century, respectively.

Late Pleistocene lake level history of Lake Mungo, Australia

Lake Mungo is a currently dry lake basin in the semi-arid zone of southeastern Australia. The transverse dune system on the downwind side contains a record of human occupation of international importance. It also contains one of the most continuous records of climate change over the last glacial cycle in the Australia desert. In this paper we provide a framework for the interpretation of lake level history from before the arrival of people (>41 ka) until after the establishment of the pastoral industry in the area. We present 83 optically stimulated luminescence ages from the Lake Mungo lunette. The lake level history is reconstructed from 34 stratigraphic sections along three transects through the lunette. The dating reveals considerable lake level fluctuations through time which occur over a depth range of ∼10 m in the basin. At its height, probably at multiple times before 20 ka, the lake held more than 1 km3 of water and at its final level at ∼19 ka, contained only 0.03 km3. The inception of Lake Mungo appears to have taken place during the mid-Pleistocene between ∼256 and 369 ka. During the last glacial cycle, Lake Mungo was almost continuously wetter than present from shortly after 60 ka until ∼19 ka. The Upper Mungo, Arumpo and Zanci units represent a succession of lake filling and drying events, briefly interspersed by soils. The final Zanci unit does not represent a single high lake phase, but an initial lake filling followed by a series of short-lived lake level events within a brief period of a few thousand years. At the conclusion of this event, the lake remained dry until the present day. Four OSL ages from a linear dune upwind of Lake Mungo indicates regional aeolian activity from ∼30 ka until present. Widespread erosion that produces the characteristic topography of the lunette began after the arrival of British pastoralists and traditional aboriginal ways of life overlapped briefly with this erosion. The presence of water in Lake Mungo closely corresponds to periods when regional surface temperature was colder than present during the late Pleistocene. Our new data supports a model that decreased evaporation and increased runoff were primarily responsible for increased availability of surface water in the hydrological cycle.

Coral Records at the Northern Edge of the Western Pacific Warm Pool Reveal Multiple Drivers of Sea Surface Temperature, Salinity, and Rainfall Variability Since the End of the Little Ice Age

AbstractReconstructions of key climate parameters prior to anthropogenic influences serve to constrain decadal to multicentury natural climate variability. In the western Pacific region, relatively few reconstructions exist north of the Western Pacific Warm Pool (WPWP), a region critical to global climate. In this study, we collected a coral core from Houbihu, southern Taiwan, and generated a 225‐year reconstruction of annual and wintertime sea surface temperature, dry season sea surface salinity, and wet season rainfall records derived from paired Porites Sr/Ca and δ18O profiles extending back to the end of the Little Ice Age (1850 CE). Multidecadal sea surface temperature trends generally track regional surface temperature reconstructions, indicating the dominant influence of solar and volcanic radiative forcings. Reconstructed dry season sea surface salinity reflects an advection signal linked to the East Asian Winter Monsoon and the Pacific Decadal Oscillation, both influencing variations in the Kuroshio Intrusion across the Luzon Strait. Reconstructed wet season rainfall, on the other hand, reveals influence of the Pacific Decadal Oscillation on the decadal variability of local and regional rainfall patterns. Relative to the late 1900s, our climate reconstructions document cooler and drier (high salinity and low rainfall) conditions during the end of the Little Ice Age, supporting other lines of evidence of a retracted WPWP region during this period. In the late 20th to early 21st century, our climate reconstructions record warming and freshening (low salinity and high rainfall) trends, highlighting the potential impact of anthropogenic forcing in the extension of the WPWP.

High Climate Sensitivity in the Community Earth System Model Version 2 (CESM2)

AbstractThe Community Earth System Model Version 2 (CESM2) has an equilibrium climate sensitivity (ECS) of 5.3 K. ECS is an emergent property of both climate feedbacks and aerosol forcing. The increase in ECS over the previous version (CESM1) is the result of cloud feedbacks. Interim versions of CESM2 had a land model that damped ECS. Part of the ECS change results from evolving the model configuration to reproduce the long‐term trend of global and regional surface temperature over the twentieth century in response to climate forcings. Changes made to reduce sensitivity to aerosols also impacted cloud feedbacks, which significantly influence ECS. CESM2 simulations compare very well to observations of present climate. It is critical to understand whether the high ECS, outside the best estimate range of 1.5–4.5 K, is plausible.

The Sensitivity of Land-Atmosphere Coupling to Modern Agriculture in the Northern Midlatitudes.

Modern agricultural land cover and management are important as regional climate forcings. Previous work has shown that land cover change can significantly impact key climate variables, including turbulent fluxes, precipitation, and surface temperature. However, fewer studies have investigated how intensive crop management can impact background climate conditions, such as the strength of land-atmosphere coupling and evaporative regime. We conduct sensitivity experiments using a state-of-the-art climate model with modified vegetation characteristics to represent modern crop cover and management, using observed crop-specific leaf area indexes and calendars. We quantify changes in land-atmosphere interactions and climate over intensively cultivated regions situated at transitions between moisture- and energy-limited conditions. Results show that modern intensive agriculture has significant and geographically varying impacts on regional evaporative regimes and background climate conditions. Over the northern Great Plains, modern crop intensity increases the model simulated precipitation and soil moisture, weakening hydrologic coupling by increasing surface water availability and reducing moisture limits on evapotranspiration. In the U.S. Midwest, higher growing season evapotranspiration, coupled with winter and spring rainfall declines, reduces regional soil moisture, while crop albedo changes also reduce net surface radiation. This results overall in reduced dependency of regional surface temperature on latent heat fluxes. In central Asia, a combination of reduced net surface energy and enhanced pre-growing season precipitation amplify the energy-limited evaporative regime. These results highlight the need for improved representations of agriculture in global climate models to better account for regional climate impacts and interactions with other anthropogenic forcings.

Low-frequency variability in the Botswana High and southern African regional climate

Decadal variability in the Botswana High and its relationships with rainfall, temperature and circulation over the southern African region are examined. This High exists in the mid-troposphere over subtropical southern Africa from early spring through to early autumn. Although its seasonal and interannual variability have been previously studied, lower frequency variability in the Botswana High has not. An EOF analysis of 500 hPa geopotential height from the NCEP Twentieth Century reanalyses reveals two modes both of which display substantial decadal to multidecadal variability. These modes, which explain almost 90% of the variance, reflect shifts in the summer core position of the High over central Namibia / western Botswana and in its strength. This decadal variability in the Botswana High is associated with sizeable changes in regional rainfall and surface temperature as well as changes in the onshore flow of moist marine air and uplift over many parts of southern Africa. Such changes are large enough to have important impacts on regional society and may also obscure climate change signals over the region.