F. Cheruy

LMDZ5B: the atmospheric component of the IPSL climate model with revisited parameterizations for clouds and convection

Based on a decade of research on cloud processes, a new version of the LMDZ atmospheric general circulation model has been developed that corresponds to a complete recasting of the parameterization of turbulence, convection and clouds. This LMDZ5B version includes a mass-flux representation of the thermal plumes or rolls of the convective boundary layer, coupled to a bi-Gaussian statistical cloud scheme, as well as a parameterization of the cold pools generated below cumulonimbus by re-evaporation of convective precipitation. The triggering and closure of deep convection are now controlled by lifting processes in the sub-cloud layer. An available lifting energy and lifting power are provided both by the thermal plumes and by the spread of cold pools. The individual parameterizations were carefully validated against the results of explicit high resolution simulations. Here we present the work done to go from those new concepts and developments to a full 3D atmospheric model, used in particular for climate change projections with the IPSL-CM5B coupled model. Based on a series of sensitivity experiments, we document the differences with the previous LMDZ5A version distinguishing the role of parameterization changes from that of model tuning. Improvements found previously in single-column simulations of case studies are confirmed in the 3D model: (1) the convective boundary layer and cumulus clouds are better represented and (2) the diurnal cycle of convective rainfall over continents is delayed by several hours, solving a longstanding problem in climate modeling. The variability of tropical rainfall is also larger in LMDZ5B at intraseasonal time-scales. Significant biases of the LMDZ5A model however remain, or are even sometimes amplified. The paper emphasizes the importance of parameterization improvements and model tuning in the frame of climate change studies as well as the new paradigm that represents the improvement of 3D climate models under the control of single-column case studies simulations.

Interannual Coupling between Summertime Surface Temperature and Precipitation over Land: Processes and Implications for Climate Change*

Widespread negative correlations between summertime-mean temperatures and precipitation over land regions are a well-known feature of terrestrial climate. This behavior has generally been interpreted in the context of soil moisture atmosphere coupling, with soil moisture deficits associated with reduced rainfall leading to enhanced surface sensible heating and higher surface temperature. The present study revisits the genesis of these negative temperature precipitation correlations using simulations from the Global Land Atmosphere Coupling Experiment phase 5 of the Coupled Model Intercomparison Project (GLACE-CMIP5) multimodel experiment. The analyses are based on simulations with five climate models, which were integrated with prescribed (noninteractive) and with interactive soil moisture over the period 1950-2100. While the results presented here generally confirm the interpretation that negative correlations between seasonal temperature and precipitation arise through the direct control of soil moisture on surface heat flux partitioning, the presence of widespread negative correlations when soil moisture atmosphere interactions are artificially removed in at least two out of five models suggests that atmospheric processes, in addition to land surface processes, contribute to the observed negative temperature precipitation correlation. On longer time scales, the negative correlation between precipitation and temperature is shown to have implications for the projection of climate change impacts on near-surface climate: in all models, in the regions of strongest temperature precipitation anticorrelation on interannual time scales, long-term regional warming is modulated to a large extent by the regional response of precipitation to climate change, with precipitation increases (decreases) being associated with minimum (maximum) warming. This correspondence appears to arise largely as the result of soil moisture atmosphere interactions.

Role of clouds and land‐atmosphere coupling in midlatitude continental summer warm biases and climate change amplification in CMIP5 simulations

Over land, most state-of-the-art climate models contributing to Coupled Model Intercomparison Project Phase 5 (CMIP5) share a strong summertime warm bias in midlatitude areas, especially in regions where the coupling between soil moisture and atmosphere is effective. The most biased models overestimate solar incoming radiation, because of cloud deficit and have difficulty to sustain evaporation. These deficiencies are also involved in the spread of the summer temperature projections among models in the midlatitude; the models which simulate a higher-than-average warming overestimate the present climate net shortwave radiation which increases more-than-average in the future, in link with a decrease of cloudiness. They also show a higher-than-average reduction of evaporative fraction in areas with soil moisture-limited evaporation regimes. Over these areas, the most biased models in the present climate simulate a larger warming in response to climate change which is likely to be overestimated.

Land Effect on the Diurnal Cycle of Clouds over the TOGA COARE Area, as Observed from GMS IR Data

The diurnal cycle of clouds over the western equatorial Pacific region (158S‐158N, 1308E‐1808) is studied analyzing hourly GMS-4 infrared brightness temperature images during the intensive observation period (Nov 1992‐Feb 1993) of TOGA COARE. Although the area studied is essentially (93%) oceanic, differences of diurnal behavior of the clouds are noticed over different ocean subareas, depending both on the general circulation conditions and on the vicinity of landmasses. This study focuses on the effects of New Guinea and other major islands on the diurnal cycle within the surrounding ocean areas, as for example, the TOGA COARE Intensive Flux Array. The major observable feature of the influence of land is the presence of a diurnal, rather than semidiurnal, average cycle of cloudiness with a high day-to-day repetitivity. The signal is observed up to 600 km off the coast of New Guinea and it is characterized by a variable phase propagating at an average speed of about 15 m s21. For smaller islands, the effect extends over a distance approximately comparable to their size. The genesis of the propagating cloud systems is assumed as due to the low-level convergence between the largescale flow and a possible land breeze. This conceptual model has been previously proposed to explain a similar signal observed offshore of Borneo. Within this framework, the influence of the large-scale circulation on the intensity and spatial organization of the propagating cloud systems is discussed. The diurnal signal vanishes when the expected convergence is weaker or when overshadowed by large-scale disturbances crossing over the considered area. In the first 3 months of the period such disturbances are nearly always cloud clusters accompanying the active phase of the Madden‐Julian oscillation. Finally it is shown that the small islands in the TOGA COARE domain can corrupt the ‘‘oceanic’’ signal by as much as 10% of the diurnal cycle.

Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture‐temperature feedbacks

Regional hot extremes are projected to increase more strongly than global mean temperature, with substantially larger changes than 2 °C even if global warming is limited to this level. We investigate the role of soil moisture-temperature feedbacks for this response based on multi-model experiments for the 21st century with either interactive or fixed (late 20th century mean seasonal cycle) soil moisture. We analyze changes in the hottest days in each year in both sets of experiments, relate them to the global mean temperature increase, and investigate processes leading to these changes. We find that soil moisture-temperature feedbacks significantly contribute to the amplified warming of hottest days compared to that of global mean temperature. This contribution reaches more than 70% in Central Europe and Central North America. Soil moisture trends are more important for this response than short-term soil moisture variability. These results are relevant for reducing uncertainties in regional temperature projections.

Influence of land‐atmosphere feedbacks on temperature and precipitation extremes in the GLACE‐CMIP5 ensemble

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

Combined influence of atmospheric physics and soil hydrology on the simulated meteorology at the SIRTA atmospheric observatory

The identification of the land-atmosphere interactions as one of the key source of uncertainty in climate models calls for process-level assessment of the coupled atmosphere/land continental surface system in numerical climate models. To this end, we propose a novel approach and apply it to evaluate the standard and new parametrizations of boundary layer/convection/clouds in the Earth System Model (ESM) of Institut Pierre Simon Laplace (IPSL), which differentiate the IPSL-CM5A and IPSL-CM5B climate change simulations produced for the Coupled Model Inter-comparison Project phase 5 exercise. Two different land surface hydrology parametrizations are also considered to analyze different land-atmosphere interactions. Ten-year simulations of the coupled land surface/atmospheric ESM modules are confronted to observations collected at the SIRTA (Site Instrumental de Recherche par Télédection Atmosphérique), located near Paris (France). For sounder evaluation of the physical parametrizations, the grid of the model is stretched and refined in the vicinity of the SIRTA, and the large scale component of the modeled circulation is adjusted toward ERA-Interim reanalysis outside of the zoomed area. This allows us to detect situations where the parametrizations do not perform satisfactorily and can affect climate simulations at the regional/continental scale, including in full 3D coupled runs. In particular, we show how the biases in near surface state variables simulated by the ESM are explained by (1) the sensible/latent heat partitionning at the surface, (2) the low level cloudiness and its radiative impact at the surface, (3) the parametrization of turbulent transport in the surface layer, (4) the complex interplay between these processes. We also show how the new set of parametrizations can improve these biases.

A Density Current Parameterization Coupled with Emanuel’s Convection Scheme. Part II: 1D Simulations

The density current parameterization coupled with Emanuels convection scheme, described in Part I of this series of papers, is tested in a single-column framework for continental and maritime convective systems. The case definitions and reference simulations are provided by cloud-resolving models (CRMs). For both cases, the wake scheme yields cold pools with temperature and humidity differences relative to the environment in reasonable agreement with observations (with wake depth on the order of 2 km over land and 1 km over ocean). The coupling with the convection scheme yields convective heating, drying, and precipitation similar to those simulated by the CRM. Thus, the representation of the action of the wakes on convection in terms of available lifting energy (ALE) and available lifting power (ALP) appears satisfactory. The sensitivity of the wake-convection system to the basic parameters of the parameterization is widely explored. A range of values for each parameter is recommended to help with implementing the scheme in a full-fledged general circulation model.

Cluster Analysis of Cloud Properties over the Southern European Mediterranean Area in Observations and a Model

Abstract This paper demonstrates how satellite observations of the cloudiness over a complex area such as the European Mediterranean area can be classified into distinct cloud regimes by application of a K-means clustering algorithm to pixel-level cloud properties. The study contrasts with previous approaches in the fact that the clustering is done on the cloud physical properties at the pixel level and not on statistics of these properties over a coarser grid. A method to choose the number of clusters is described. “Shallow cumulus,” “stratocumulus,” and “frontal” clusters are robustly identified, and associated environmental properties are described. The approach helps to refine the diagnosis of errors in model simulations. In addition to isolated classical errors of climate models (lack of midlevel clouds, overestimation of the cloud optical thickness, and underestimation of the stratocumulus) and a dramatic underestimation of the shallow cumulus clouds over land, an underestimation of the boundary lay...

The role of thermal inertia in the representation of mean and diurnal range of surface temperature in semiarid and arid regions

In this article we show the possible role of thermal inertia in the large spread of the simulated surface temperature over arid and semiarid regions among climate models. The surface-atmosphere interactions are investigated based on single-column simulations of the DIurnal land-atmosphere Coupling Experiment and on global simulations. Low values of the surface thermal inertia increase the diurnal temperature range (DTR) and the daytime turbulent heat fluxes. The diurnal response of surface temperature to the thermal inertia is asymmetric between daytime and nighttime, inducing a change in the daily mean surface temperature that can reach several degrees over large areas. This asymmetrical response to thermal inertia is shown to be due to the diurnal contrast of the stability state of the atmospheric boundary layer. Thermal inertia in dry regions plays a critical role on both DTR and surface mean temperature and needs to be carefully represented in land surface models.