Cloud‐top heights (CTH) from the Multiangle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra constitute our longest‐running single‐platform CTH record from a stable orbit. Here, we provide the first evaluation of the Terra Level 2 CTH record against collocated International Space Station Cloud‐Aerosol Transport System (CATS) lidar observations between 50ºN and 50ºS. Bias and precision of Terra CTH relative to CATS is shown to be strongly tied to cloud horizontal and vertical heterogeneity and altitude. For single‐layered, unbroken, optically thick clouds observed over all altitudes, the uncertainties in MODIS and MISR CTH are −540 ± 690 m and −280 ± 370 m, respectively. The uncertainties are generally smaller for lower altitude clouds and larger for optically thin clouds. For multi‐layered clouds, errors are summarized herein using both absolute CTH and CATS‐layer‐altitude proximity to Terra CTH. We show that MISR detects the lower cloud in a two‐layered system, provided top‐layer optical depth <∼0.3, but MISR low‐cloud CTH errors are unaltered by the presence of thin cirrus. Systematic and random errors are propagated to explain inter‐sensor disagreements, as well as to provide the first estimate of the MISR stereo‐opacity bias. For MISR, altitude‐dependent wind‐retrieval bias (−90 to −110 m) and stereo‐opacity bias (−60 to −260 m) and for MODIS, CO2‐slicing bias due to geometrically thick cirrus leads to overall negative CTH bias. MISR’s precision is largely driven by precision in retrieved wind‐speed (3.7 m s−1), whereas MODIS precision is driven by forward‐modeling uncertainty.

An artificial neural network‐based two‐dimensional ionospheric model (ANNIM) that can predict the ionospheric F2‐layer peak density (NmF2) and altitude (hmF2) had recently been developed using long‐term data of Formosat‐3/COSMIC GPS radio occultation (RO) observations (Sai Gowtam & Tulasi Ram, 2017a, https://doi.org/10.1002/2017JA024795). In this current paper, we present an improved version of ANNIM that was developed by assimilating additional ionospheric data from CHAMP, GRACE RO, worldwide ground‐based Digisonde observations, and by using a modified spatial gridding approach based on the magnetic dip latitudes. The improved ANNIM better reproduces the spatial and temporal variations of NmF2 and hmF2, including the postsunset enhancement in equatorial hmF2 associated with the prereversal enhancement in the zonal electric field. The ANNIM‐predicted NmF2 and hmF2 exhibit excellent correlations with ground‐based Digisonde observations over different solar activity periods. The ANNIM simulations under enhanced geomagnetic activity predict the depletion of NmF2 at auroral‐high latitudes, and enhancement over low latitude to midlatitude with respect to quiet conditions, which is consistent with the storm time meridional wind circulation and the associated neutral composition changes. The improved ANNIM also predicts a significant enhancement in hmF2 around auroral latitudes due to increased plasma scale height associated with particle and Joule heating during storm periods. Further, the ANNIM successfully reproduces the coherent oscillations in NmF2 and hmF2 with recurrent cororating interaction region‐driven geomagnetic activity during the extreme solar minimum year 2008 and can distinguish the roles of recurrent geomagnetic activity and solar irradiance through controlled simulations.

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Our longest, stable record of cloud-top pressure (CTP) and cloud-top height (CTH) are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-Angle Imaging Spectroradiometer (MISR) on Terra. Because of single cloudlayer assumptions in their standard algorithms, they provide only single CTP/CTH retrievals in multi-layered situations. In the predominant multi-layered regime of thin cirrus over low clouds, MODIS significantly overestimates cirrus CTP and emissivity, while MISR accurately retrieves low-cloud CTH. Utilizing these complementary capabilities, we develop a retrieval algorithm for accurately determining both-layer CTP and cirrus emissivity for such 2-layered clouds, by applying the MISR low-cloud CTH as a boundary condition to a modified MODIS CO 2 -slicing retrieval.We evaluate our 2-layered retrievals against collocated Cloud-Aerosol Transport System (CATS) lidar observations. Relative to CATS, the mean bias of the upper cloud CTP and emissivity are reduced by ˜90% and ˜75% respectively in the new technique, compared to standard MODIS products. We develop an error model for the 2-layered retrieval accounting for systematic and random errors. We find up to 88% of all residuals lie within modeled 95% confidence intervals, indicating a near-closure of error budget. This reduction in error leads to a reduction in modeled atmospheric longwave radiative flux biases ranging between 5-40 Wm -2 , depending on the position and optical properties of the layers. Given this large radiative impact, we recommend that the pixel-level 2-layered MODIS+MISR fusion algorithm be applied over the entire MISR swath for the 22-year Terra record, leading to a first-of-its-kind 2-layered cloud climatology from Terra's morning orbit.

Our longest, stable record of cloud‐top pressure (CTP) and cloud‐top height (CTH) are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi‐Angle Imaging Spectroradiometer (MISR) on Terra. Because of single cloud‐layer assumptions in their standard algorithms, they provide only single CTP/CTH retrievals in multi‐layered situations. In the predominant multi‐layered regime of thin cirrus over low clouds, MODIS significantly overestimates cirrus CTP and emissivity, while MISR accurately retrieves low‐cloud CTH. Utilizing these complementary capabilities, we develop a retrieval algorithm for accurately determining both‐layer CTP and cirrus emissivity for such 2‐layered clouds, by applying the MISR low‐cloud CTH as a boundary condition to a modified MODIS CO2‐slicing retrieval. We evaluate our 2‐layered retrievals against collocated Cloud‐Aerosol Transport System (CATS) lidar observations. Relative to CATS, the mean bias of the upper cloud CTP and emissivity are reduced by ∼90% and ∼75% respectively in the new technique, compared to standard MODIS products. We develop an error model for the 2‐layered retrieval accounting for systematic and random errors. We find up to 87% of all residuals lie within modeled 95% confidence intervals, indicating a near‐closure of error budget. This reduction in error leads to a reduction in modeled atmospheric longwave radiative flux biases ranging between 5 and 40 W m−2, depending on the position and optical properties of the layers. Given this large radiative impact, we recommend that the pixel‐level 2‐layered MODIS + MISR fusion algorithm be applied over the entire MISR swath for the 22‐year Terra record, leading to a first‐of‐its‐kind 2‐layered cloud climatology from Terra's morning orbit.