CAREER: Reducing the projection uncertainty for Arctic sea ice loss

在过去的几十年里，北极夏季海冰覆盖面积一直在迅速减少。科学家估计，未来的变暖将导致更大的损失，不仅对北极，而且对整个全球气候系统都有影响。目前，不同的气候模型在对海冰损失的预测中表现出广泛的差异。在这个职业奖中，研究者将评估这些差异的原因，最终目标是减少北极海冰预测的不确定性。她还将在她所在的机构开设一个以气候科学为基础的本科研究经验（CURE）课程，涉及80名学生，为期4年。CURE课程在提高其他学科的学生保留率和自我效能感方面是有效的，对不同类型的学生尤其有积极的好处。课程材料将在CUREnet上提供给其他有兴趣在大气和海洋科学方面实施CURE研究经验的教师。最后，该项目将支持培养一名博士后科学家和研究生，并将进一步发展一名女性终身研究员的职业生涯。该项目将评估北极海冰模式预估和气候模式之间平均状态的大范围传播的物理原因，目标是使基于过程的模式选择能够改进海冰预估。耦合模式比对项目第6阶段（CMIP6）模式为这种基于过程的海冰分析提供了第一次机会，这是由于海冰模式比对项目（SIMIP）为CMIP6提出的新输出要求，并由作为SIMIP联合主席的研究者牵头。该职业奖将提供对海冰动力学、海冰热力学和海洋混合层过程对海冰预测传播的贡献的见解。它还将对模式模拟实际海冰内部变率的能力进行评估，并通过向模拟小组提供有关可以解释模式偏差的重要过程的信息，促进未来气候模式的改进。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Arctic summer sea ice cover has been declining rapidly over the past few decades. Scientists estimate that future warming will lead to even greater losses, with implications not just for the Arctic but for the global climate system as a whole. Currently, different climate models exhibit a wide spread in their predictions of sea ice loss. In this CAREER award, the investigator will assess the causes of these discrepancies with the ultimate goal of reducing the uncertainty of Arctic sea ice projections. She will also develop a course based undergraduate research experience (CURE) class in climate science involving 80 students over 4 years at her home institution. CURE classes are effective in increasing student retention and self-efficacy in other disciplines, with particularly positive benefits for diverse students. Class materials will be made available on CUREnet for other faculty interested in implementing a CURE research experience in Atmospheric and Oceanic Sciences. Finally, the project will support training for a postdoctoral scientist and graduate student and will further the career of a female, tenure track investigator.This project will evaluate the physical causes of the large spread in Arctic sea ice model projections and mean states between climate models, with the goal of enabling process-based model selection to refine sea ice projections. The Coupled Model Intercomparison Project Phase 6 (CMIP6) models provide the first opportunity for this type of process-based sea ice analysis, due to the new output requested by the Sea-Ice Model Inter-comparison Project (SIMIP) for CMIP6 and spearheaded by the investigator as SIMIP co-chair. This CAREER award will provide insights into the contributions of sea ice dynamics, sea ice thermodynamics, and ocean mixed layer processes to the spread in sea ice predictions. It will also provide an assessment of the ability of models to simulate realistic sea ice internal variability and facilitate the improvement of future climate models by providing information to modeling groups on important processes that can explain model biases.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.